One of the most buzzing terminologies of this decade has got to be “data analytics.” Companies generate unlimited data every day, and there is no end to the data collected over time. This content can be in the form of log content, transactional content, social media data, and customer—related data.
Companies need all of this data in a structured manner to improve their decision—making capabilities. Additionally, one can derive the most value out of this data by using it to boost their career performance. Data analytics helps in meeting these goals.
Data analytics consists of processes examining data sets to find trends and conclusions from the information. The speed and efficiency of your business improve once you notice patterns and discover insightful data needed for business predictions. Therefore, data analytics is undoubtedly the most sought—after science field today.
How can data analytics be used for bolstering career performance?
It never hurts to have extra skills to make work easier, which is why professionals seek the help of data analytics to recognize work patterns. The analysis helps them understand how the quality of work can be improved and change the present circumstances in the workplace. For career prospects also, companies are turning towards analytics to make safer decisions.
The following reasons make it easier to understand why more businesses are incorporating data analytics to enhance performance:
1. Data analytics is prevalent in all sectors
The top industries that rely heavily on data analytics are Information Technology services, Manufacturing and Retail businesses, and Finance and Insurance companies. However, data analytics is now used across all domains and sectors.
For better career prospects, data analytics can aid in predicting upcoming developments in different industries. As a result, you can look for opportunities in the sector you are interested in. You can avail yourself of the benefits of career development before anyone else.
2. Data analytics acts as a catalyst for artificial intelligence
Artificial intelligence is another buzzing terminology of today. Most people don’t know that data analytics serves as a foundation for companies that want to develop artificial intelligence—related projects. This is because AI uses the same techniques and processing capabilities that data analytics resources use.
3. Data analytics makes marketing strategies successful
Data analytics takes a big chunk of information, derives valuable insights, and tests the results on a sample audience group. Marketing strategies can use the same method to understand consumer trends and behaviors. Companies can thereby produce compelling pitches for their products/services and develop sure—shot marketing strategies.
4. Data analytics increases the revenue of the business
As data analytics helps see the changing dynamics much ahead of time, companies can upgrade themselves accordingly. This ensures that the company is always at the top of its game and never loses brilliant opportunities. Eventually, everything works towards generating more revenue for the business.
How can companies use data analytics for their employees?
If you are running on a money and time budget, using data analytics to speed up work is the best call you can take. When you bridge the gap between job tasks and quantitative abilities, you will get a tangible input of what level of performance is required to accomplish the job.
Organizations can use the following strategies to apply data analytics at work for better performance management:
1. Generate accurate employee feedback
The future of performance management includes both employee feedback and data analytics. For example, instead of providing work reviews at scheduled times during the year, companies can apply real—time reviews and check—ins to improve engagement.
Resources like HR assessments and PR reviews can help employees understand their shortcomings and biggest strengths. Additionally, Leapsome’s feedback examples can be used for effective employee feedback management. The human touch will always be an integral part of the process, even if data analytics takes over completely.
2. Measure employee performance
Companies can use data analytics tools to set benchmarks for employee performance. Apart from professional data, inputs on travel data and billing hours can help them plan both professional and personal priorities, significantly when it impacts their wellness. Employees meeting those benchmarks can guide others in an optimal career performance.
3. Apply analytical diligence
You can apply data analytics to plan talent and work on the performance management of your employees. With the results, you can invest in the right tools needed to sharpen the skills and enhance the productivity of those falling back. In addition, this analysis can help the HR department describe their job requirements accurately and find the right people for the job.
4. Personalize workforce environment
Data analysis can help understand employee data and provide them with a unique workplace environment. Letting people know that their data is used for analysis helps retain their trust. Eventually, you will be able to create a safe space for your employees where they can work as per their suitability.
5. Perform unbiased recruitment processes
Data analytics can help in recognizing those groups that face unconscious bias. By representing those groups, you will be able to broaden the talent pool in your workspace. In addition, analytics and digital engagement can help understand those algorithms and decisions concerning the company.
6. Inform employees about promotion and salary decisions
Nothing puts off an individual more than seeing an undeserving candidate get what they deserve, especially in a workplace. However, promoting the wrong candidate can demotivate the rest of the team members. Data analytics can help managers rate the proficiency and the capability of those employees who either deserve a promotion or a raise.
7. Understand attrition and increase retention
Performance—based analytics can be applied to foresee those employees that are likely to leave their jobs and what factors can contribute to attrition. For example, money may not always be the factor to be blamed. Other factors like smaller teams or longer wait for promotions or raises can be equally responsible.
Summarizing data analytics and its effect on career performance
While intelligent data analytics metrics certainly help HR professionals, it still doesn’t take away the importance of the human role in upgrading career performance. The most successful way of integrating data analytics is through a proper organizational design. This design will guide future decisions, specify skillsets needed and upskill employees to perform well in their chosen career path.
One of the most stunning facts revealed by the new coronavirus pandemic (COVID-19) has been our acceptance of polluted air. Skies in the world’s largest cities turned a color that astonished many residents when personal vehicle miles plummeted dramatically. At the same time, scientists discovered that poor air quality might raise coronavirus susceptibility.
Big data technology has helped us make these findings. It will also help develop solutions.
These findings underscore how years of awareness-raising about the dangers of climate change have turned into action to protect public health. It also reveals how little we still understand about how our air quality affects our health. In the wake of the pandemic, it is more important than ever to invest in research to improve our understanding of the link between air quality and health so that we can take steps to protect ourselves from future pandemics.
Now that some parts of the world are starting to look like they did before the lockdown, people are talking about trying to keep this improvement in air quality. Lots of people want better air quality, so cities might need better data on air quality to make new decisions about policy.
Fortunately, the past five years have seen significant progress in air quality monitoring for smart cities. Big data is going to make or break smart cities and it can help solve environmental challenges they face. Smart cities should follow the guidelines outlined below when capturing air quality data:
1. Increase data resolution
In order to improve air quality, cities need to have better data resolution. This means that cities need to measure the air quality at many different locations instead of just a few. This is important because the concentrations of pollutants can vary a lot from one place to another in a city.
For years, the only way to measure air quality was to take samples of the air and send them to a laboratory for analysis. However, this process was slow and expensive. In recent years, sensors that can measure air quality in real-time have been developed. These sensors are typically small and portable, making them easy to use in a variety of settings. In addition, they are relatively inexpensive, making them a valuable tool for monitoring air quality.
While many cities rely on physically deployed sensors to collect data, there are other options available that come with their own advantages and disadvantages. One option is mobile surveying, which can provide a much larger albeit less complete profile over time. These surveys usually involve the use of car-mounted sensors, but some cities are breaking the trend by using municipal trucks, drones, and bike-share bikes for mobile surveying.
As cities wrestle with the problem of air pollution, some are looking to cutting-edge technology for help. Air quality sensors are becoming increasingly commonplace, providing valuable data on local conditions. However, these sensors can only cover a limited area, leaving gaps in the data. Environmental data companies are now using fluid dynamics models to fill in these gaps and predict air quality for any point. This method is still in its infancy, and there are concerns about its accuracy. However, it is an inexpensive option that could be used in conjunction with other methods to improve air quality data.
2. Measure ROI of air quality sensors
Air quality monitoring is an important tool for cities to protect public health, but the question of how to pay for it can be difficult to answer. There are many different air quality measurement technologies available, and each has its own benefits and drawbacks. Some technologies are more expensive than others, but they may also be more accurate or provide more data. Ultimately, the decision of which technology to use depends on the specific needs of the city and the availability of funding. Here isa good guide on how to measure air quality.
There are many options for financing air quality monitoring projects, including grants, loans, and private investment. The best option for any given city will depend on the available resources and the level of need. Whatever the method of financing, it is important that cities invest in air quality monitoring to protect public health and improve air quality.
ROI can be measured in different ways. One way is to look at the economic benefits that come from people not getting sick as often. This includes things like less time spent at the doctor or hospital, and less money spent on medicine. Another way to measure ROI is to look at how much air pollution costs our economy every year. Air pollution cost the US economy around $900 billion in 2019, equivalent to 5% of GDP.
Reducing air pollution could therefore have a significant positive impact on a city’s economy. In addition, improving air quality would also lead to better health outcomes for residents, which would also reduce healthcare costs. As cities continue to grapple with the effects of air pollution, it is important to consider both the human and economic costs of this public health crisis.
3. Explore new ways to put data to good use
Data from air quality sensors can be used in a number of innovative ways. For example, the city of Leeds in the U.K. has equipped its fleet of hybrid vehicles with quality sensing and geofencing technology. This allows the vehicles to automatically switch to electric-only mode when they enter areas with poor air quality. As a result, the city’s fleet of hybrid vehicles is able to significantly reduce emissions in areas where air pollution is a problem.
Similarly, cities can use data from their air quality sensor network to map hot spots of fine particulate matter. They can then work with residents in these areas to identify sources of the pollution and develop strategies for reducing emissions. By finding innovative uses for data from air quality sensors, cities can take steps to improve air quality and protect public health.
Big data technology is changing our lives in countless ways. Due to the many benefits that data provides, more companies are investing in it. Global companies are expected to spend over $234 billion by 2026. This is a great opportunity for companies that develop big data applications for customers and businesses alike.
If you are interested in creating a successful big data application, then you could have a very profitable business model on your hands. However, profitable big data companies are not born. They require a lot of planning and hard work. You have to have the right elements of success before you launch your company.
As you know by now, running a company is no easy feat. Creating a successful big data company can be even harder, since there is so much competition and the barriers to entry are so high.
You need to have the right mindset, the right tools, and most importantly, the right team. To make it through the day, you’ll need to focus on tasks and not worry about your company’s goals. You also need an impeccable understanding of big data.
In this article, you will learn about four areas of running a company that you can master.
1. Mission Statement
A mission statement is something that every business needs because it gives your company a purpose and direction. If you are selling a data analytics platform for financial traders, you need to have a mission statement that will help your company figure out what it is trying to accomplish.
Your mission statement also helps employees understand how they can contribute to your company’s success. If working hard and being diligent is one of the core values in your company, an employee who works hard but not diligently may feel like they are not contributing enough to the success of the company.
As a big data startup, you should emphasize the importance of technological development. Your company needs to make technological competence a core part of its mission statement, since your brand won’t be able to survive without it. You should emphasize how you will use big data to stand out, since this is crucial for modern companies.
2. Business Brand
Your brand is the image that your business has created for itself. This can also include the logo, advertising campaigns, and other marketing material. A good way to create a good brand would be to have an employee who is creative create a logo and make it available to all employees so that they can use it in their official business cards and other company materials.
When you are creating a brand for a big data startup, you have to make sure it emphasizes the technological competence of your team. Customers won’t trust a technology startup that doesn’t demonstrate the importance of big data.
You can also learn how to design a logo and create what you love most, and something that clients can resonate with.
3. Core Values
Big data technology is constantly changing, so your business will always have to adapt to these changes. However, your company’s core values will remain the same, regardless of trends in the big data sector.
Core values are important for every company as they set the standard for your employees and customers. These core values should not just be written on a piece of paper. They should be ingrained into every employee and customer’s mind so that they can become part of your company’s culture.
For example, if honesty is one of your company’s core values, every employee and customer should know that they can trust you with their money or their life savings because they know that you are honest with them at all times. Additionally, core values help employees understand what is expected of them at work and outside work.
4. Culture
You might rely heavily on automation to run a big data startup. However, the employees running your company are still humans. They will create a company culture that will affect the future of your business.
Company culture is the set of values that your business and your employees live by their beliefs and morals. It can be tough to create a good culture because every business is different, and every employee is different.
However, if you want to ensure that your employees are happy where they are working, you need to know how they feel about certain things in the company so that you can create a good culture. It also contributes to a good working environment.
Do Your Due Diligence When Creating a Data-Driven Business
Running a data-driven business doesn’t have to be a daunting experience. You only have to take all of the information you have gathered during this process and put it to good use.
You should be able to create a plan for your business, brainstorm ideas for new products, and set up your finances to make your business successful. Hopefully, this article has helped you get started on the right foot.
Blockchain is one of the most disruptive technologies of the 21st Century. A growing number of industries are using blockchain to operate more efficiently or boost security.
However, blockchain is still most important in the realm of cryptocurrencies. Bitcoin has become very popular since its inception in 2008 and that is largely due to the power of blockchain. Blockchain has made investing in bitcoin much more secure than ever.
Are you interested in buying bitcoin? You need to understand the general process and the role that blockchain plays in it.
How Does Blockchain Fit into the Process of Buying Bitcoin?
It may seem a complicated task to invest in bitcoin. However, it can be easier with the proper knowledge and breaking it down into steps. You will need to understand the general process, as well as the role that blockchain plays in it.
If you want to trade or invest in bitcoin, you need to have a cryptocurrency service account, secure internet connection, method of payment, and personal identification documents. Initially, things may seem confusing to you, but you will surely not regret buying the bitcoin.
You also need a personal wallet outside in addition to your account with a bitcoin exchange if you want to buy bitcoins. The valid payment methods for the process include credit cards, debit cards, and bank accounts. Also, you can buy bitcoin through P2P exchanges and specialized ATMs that connect directly to the blockchain.
Security and privacy are important factors that you need to consider before buying a bitcoin. You need to get private keys to a public address as it will enable you to authorize transactions on the bitcoin blockchain. The blockchain has made trading bitcoin extremely secure, but you still need to protect your digital coins by securing your wallet and account.
Keeping private keys secret is a must as criminals and scammers can attempt to steal them. You have to be careful while using the balance of a public address. Without further ado, let’s explore how you can buy bitcoin over the blockchain.
1. Choose Crypto Trading Service
Initially, you have to choose a crypto trading venue or service. Some of the well-known trading services that you can choose to buy BTC include payment services, brokerages, and cryptocurrency exchanges. You need to make sure that these are legitimate services that actually connect to the blockchain. Out of all these options, you should go for cryptocurrency exchanges as it has a wide range of features that ensures a great level of convenience.
By signing up for a cryptocurrency exchange, you can sell, buy, and hold cryptocurrency. Usually, bitcoin buyers prefer this option because it allows them to withdraw crypto from their personal wallets safely. As long as it is a service that legitimately connects to the blockchain, the transactions themselves will be highly secure. However, it is still important to make sure that the bitcoins stored on the exchanges will be secured as well.
There are different types of cryptocurrency exchanges. Some exchanges allow users to not provide personal information while some need it. The exchanges that enable users to stay anonymous are decentralized and operate autonomously. It means they do not have any central point of control. Such systems can serve the unbanked population of the world. Refugees or people living with no banking structure can use anonymous exchanges that can help them enter the mainstream economy. The blockchain has given them the opportunity to use a much more efficient currency.
2. Connect your Exchange to Payment Method
Once you have chosen the exchange, you need to connect the exchange to the payment option. You need to ensure that you have all the required documents to do that. It includes a driving license picture or social security card that depends on the type of exchange that you choose. You may also have to provide information about your employer and source of income. The exact process depends on your region where you live and the laws that apply there. The procedure is almost the same as setting up a brokerage account.
Once the exchange verifies your identity, you can connect to the payment option and will be ready to start placing transactions over the blockchain. You can directly connect to your bank account, debit, or credit card in most exchanges. Although, it is not a good idea to buy bitcoin through a credit card because price volatility can inflate the overall purchasing coin cost. Bank can also ask you some questions, so you have to be prepared. You should check in advance to ensure that your bank allows deposits at the exchange you have chosen. The deposit fees of banks through debit, bank account, and credit cards can vary.
3. Place the Order
After choosing the exchange and connection payment option, you are all set to buy bitcoin. In the recent past, cryptocurrency exchanges have become mainstream as they have grown massively in terms of features and liquidity. The cryptocurrency exchanges have reached a point where they have the same features as stock brokerage. The blockchain is so efficient at processing these transactions that bitcoins can be purchased nearly instantaneously.
Crypto exchanges offer many order types and methods to invest. Apart from different types of orders, exchanges also allow clients to set up recurring investments. For example, Coinbase enables users to set recurring purchases on a daily, weekly, and monthly basis.
4. Safe Storage
The blockchain has made the process of buying, selling and transferring bitcoins very secure. However, there are security issues that it can’t address, because it only plays a role during the transfer process. Namely, the blockchain can’t protect coins in your wallet. You have to have a secure storage option.
Bitcoin wallets allow you to keep your digital assets secure. If you have cryptocurrency outside of the exchange, then your personal wallet ensures that only you have access to the private key to control your funds. It also enables you to store funds from the exchange and also mitigates the risk of getting your exchange hacked. In this way, it ensures security, so you do not lose your funds.
Most of the exchanges offer wallets for their users, but security is not their major preference. You should not use such type of exchanges wallet that does not guarantee security. Some wallets have more storage features as compared to others, so you should take a look at each of them. You can consider choosing from different types of bitcoin wallets. The hot wallets are known as online wallets, while cold wallets are known as hardware or paper wallets.
You can access hot wallets on internet-connected devices, including phones, tablets, and computers. It can cause vulnerability because these wallets produce the private keys to your coins on devices that you use. Although using a hot wallet is a convenient option that allows you to make transactions efficiently and quickly with your assets.
Also, it allows you to store your private key on internet-connected devices. On the other hand, cold wallets are not connected to the internet, so there is less risk involved in it. You may consider these wallets as hardware or offline wallets. These wallets store your private keys on anything which is not connected to the internet.
According to experts, cold wallets are a more secure option for storing bitcoin or any other cryptocurrencies. You can generate these wallets by using certain websites that provide you with private and public keys.
The Blockchain Plays a Crucial Role in the Process of Buying and Selling Bitcoins
The blockchain has a very important role in the process of buying bitcoin. Trading and buying bitcoin has become one of the major trends that have completely transformed many people’s lives, due to the benefits the blockchain has provided. It provides you with a great opportunity to attain financial freedom and change your lifestyle. But you need to have complete awareness before buying the bitcoin to avoid any risks of losing the funds.
Getting professional assistance from bitcoin or crypto experts can make the bitcoin buying process easier for you. It will also help you know about the different aspects that can be beneficial for you in the long term.
Data has become one of the most valuable assets to modern organizations. Some companies are still in denial of its importance, but their hesitance to embrace it is subsiding. One poll found that 36% of companies rate big data as “crucial” to their success.
However, many companies still struggle to formulate lasting data strategies. One of the biggest problems is that they don’t have reliable data collection approaches.
Data Collection is Vital to Companies Trying to Make the Most of Big Data
In the world of business, data collection is very important. Quality data can be used to solve many different types of problems that may occur, such as improving financial efficiency, identifying the best customers to target with their marketing campaigns and exploring new ways to improve productivity. Therefore, data must be collected, vetted for quality and preserved for future use. However, data does not just collect itself. It has has to be gathered efficiently and legally.
The data collection process should be carried out methodically. Different data collection processes might be ideal for different types of data. Some common data collection methods are shared below.
Surveys
When it comes to data collection, nothing beats a good old-fashioned survey. Surveys can come either in a physical or digital form. In a business, conducting a survey is very easy. A survey will allow customers to share their opinions on the services they receive. Therefore, a business can now use this useful data to improve its efficiency and bolster customer engagement.
Interviews and Focus groups
Interviews and focus groups can also be effective for gathering data. This process involves assembling a small group of people and asking them questions about a topic. You are looking to collect data about their sentiments around a particular brand or product.
After a new product or service is released, it can be difficult to understand the public’s perception about it. Focus groups or interviews are modern data collection approaches to get a better perspective on their views. They provide valuable feedback from users, which is collected as data. This data is in turn saved and used to solve problems relating to the product or service.
Online forms
Data collection forms are a great way to collect useful data in any business. A data collection form is a cheap but effective way to get data about customers. Another benefit is that customers can be asked to fill in these forms when they want to purchase the product or service. Most of these forms are usually available online for people that want to register for a service. Data collection forms are very useful when an existing customer needs to receive information about a new product or feature. There is also a data collection forms app that helps to make this easier.
Social media or websites
In the age of digital media, the vast majority of businesses require social media platforms or websites to run their business efficiently. There are actually a multitude of benefits of social media. While social media is very useful for advertising new products or services, that is not all that it is good for. Companies can use social media to field complaints made by people using their services or their competition to improve their business models. Besides, this is a good way to gather data without necessarily paying for it.
The Importance of Data Collection in Business
A business that wants to strive must have an effective data collection strategy. Let’s see why data collection is key to business development below:
Decision-making
In a business, a lot of important decisions have to be made on a regular basis. Many of these decisions are influenced by data that has been shared from users. Properly executed data collection processes help provide useful information that can be used to make good decisions.
Detect problems
When a business is facing a challenge, no matter how visible it might be to the decision-makers within the company, it is usually going to be reflected in their data. Data includes complaints and comments made by customers. As the data is collected, it shows the areas where the business must make improvements. This is the first step in fixing the problem.
Develop strategies
Every business requires a strategy that would be used to achieve the business’s goals. What many businesses fail to understand is that data about customers can be incredibly valuable for articulating strategies on bolstering customers satisfaction. Quality data shows what the customers want, and this will decide what strategy to use.
Saves time
A great data collection strategy saves time because you would otherwise need to waste a lot of effort by executing poorly thought-out, ad hoc data collection strategies. By collecting and storing data, you will never waste your time finding some data. As part of the data collection definition on Simplilearn, saving time is one of the crucial importance of collating data for a business.
Conclusion
Data collection has become a very important process, because data is vital to the decision-making process in many companies. Every business needs a methodical approach to collecting and storing valuable data. This will surely improve the efficiency of the business.
Data collection is the new normal. Data scientists or analysts are highly sought-after by tech companies. It is almost impossible to do without data these days. No wonder, a lot of companies spend millions to collate data. Finally, plan an effective data collection that will suit your business. You can get data collection forms on pareto to collate information.
Advances in data analytics have raised the bar with QA standards. Companies need to invest in higher quality data analytics solutions to make the most of their QA methodologies. This entails creating robust, all-in-one solutions, rather than relying on a fragmented set of big data tools.
All-in-One Big Data Platforms Are Key to Successful QA Systems
QA engineers use a variety of big data tools in their work. All of these solutions are designed to make work more efficient, but in practice very often there is confusion. In this case, it is expected that each new tool will complicate things. This is not entirely true.
A high-quality testing platform easily integrates with all the data analytics and optimization solutions that QA teams use in their work and simplifies testing process, collects all reporting and analytics in one place, can significantly improve team productivity, and speeds up the release. Let’s figure out what a testing platform is and why it is beneficial to use it. This is an important part of big data testing for teams.
Why is a testing platform a necessity for Agile-teams? Hint: It’s all about release speed
QA teams need a data analytics platform that would help them work effectively in a number of areas:
Run simple automated tests.Writing scripts and running complex automated tests.Data reporting.Deep data analysis.Communication with developers, as well as with management.
A significant role in this matter is played by the fact that more and more companies are implementing Agile and DevOps methodologies. They do this to speed up software development and get to market faster. Integrating testing into these software delivery models requires new QA tools that can be easily integrated into open-source test automation solutions for data engineers and QA specialists.
Thus, the presence of an all-in-one platform that integrates the entire workflow of QA engineers allows you to strengthen the potential of the team, simplify and significantly speed up many processes.
Top crucial capabilities of good testing platform
One place of truth
High quality test automation platform allows QA engineers to plan and complete all the required work. The platform easily integrates with a variety of tools and collects all data in one place.
Orchestration: Set up one synchronous process
Test Orchestration is the setting up of a well-defined sequence of automated test activities. For example, at the end of a development sprint, when the software is ready to be released, there are several steps that take place before the application is made available to users.
Each of these test actions can be individually automated, but manual intervention is still required to run all tests at the right time with the correct input. Orchestration helps link each of the individually automated test activities into one synchronous process.
With orchestration, you can run multiple rounds of testing within a limited amount of time and still achieve the desired level of quality. Test orchestration can be used by commands to perform several use cases:
Comprehensive testing of complex business scenarios that include multiple combinations of APIs and services.Upgrade testing a release candidate against multiple upgrade paths. A certain version of the software may be upgraded from several previous versions. Testing each of the possible update paths helps to avoid a number of problems for users in the future.Special security testing to identify security vulnerabilities in software or vulnerabilities with software dependencies.Testing compliance with predetermined standards and rules.
The right data analytics algorithms help with all of these steps.
Launcher: Don’t worry about the execution environment
A launcher is a predefined configuration associated with a specific test repository that allows you to perform parameterized tests. The test run configuration should be available for any testing frameworks. You can configure presets for your team and run tests in one click.
Today, more and more companies have QA teams. The main responsibility of these teams is to automate the execution of test cases using the programming language. But having automated test suites is only part of what is needed. The most important part is to run these tests regularly to get instant feedback on software quality.
This is not as simple a task as it may seem at first glance.
At a minimum, this requires setting the environment for the programming language in which the tests are written. As the number of automated tests increases, the test suite becomes more time consuming, requiring some kind of scaling for the execution.
Test automation platform allows you not to worry about the execution environment. QA teams can focus on the test automation. Good platforms provide a tool that can be used to execute test suites stored in a Git repository and get comprehensive reporting at the same time.
Analytical capabilities: Take advantage of AI/ML
Test automation platform should provide a centralized place for reporting and automatically collect and analyze data from test launches, as well as report results in real time. A platform integrated into DevOps and CI/CD pipelines can do much more than just provide basic reporting. Test automation platform collects and links information from git-repositories, test launches, and a range of Agile tools to provide deep analytics of test activity such as requirements coverage, release readiness, test flakiness.
Test automation platform provides correct information for employees considering their role on the project. So, QA engineers get the information they need to work on product quality assurance, developers get the information that points to the problem spots in the code, and managers get the analytics and metrics, which allow them to evaluate the effectiveness of work on the product and its readiness for release.
High-quality test automation platform provides data processed with AI-technology. Thus, key decisions such as product release will be made on the basis of data rather than intuition. You can also train AI by yourself to improve the accuracy of its operation and facilitate the identification of failed tests in the future.
Reporting: Get all information in a few minutes
Creating a high-quality report for the C-level can take a lot of time: you need to collect statistics from various resources, analyze it, identify trends, build charts, and calculate the necessary metrics. Test automation platform will create a high-quality report in a few minutes.
Zebrunner Testing Platform as the optimal solution
Zebrunner Testing Platform is an efficient test automation management solution. The platform significantly accelerates test execution, provides instant reporting and deep analytics, ensures full transparency and availability of test results.
Zebrunner is an advanced solution for scaling test execution, smart and transparent reporting, and QA team management. The tool helps save time and effort and makes automated testing as productive as possible.
There are critical capabilities of the Zebrunner Testing Platform:
Fast test execution and scalable testing environment. Many companies run tests in their own runtime environments with limited scalability. This is time-consuming. If a product, for example, is covered by 1000+ automated tests, their execution can take over 8 hours. As a result, the release is delayed and the project team is overloaded. Zebrunner Selenium Grid helps you run tests in parallel in the cloud or on-premise (locally). You can execute up to 1000 threads in 15 minutes. The team gains time to fix the bugs, and managers can be confident in the release.
Transparent reporting. Preparation of a high-quality report on the results of the tests can take lots of hours. Zebrunner Testing Platform does this automatically. Users can customize numerous widgets and dashboards to fit their metrics and create reports within minutes.
Analytics. Zebrunner helps QA engineers check for failed tests, find their causes, and provides many test artifacts (test logs, screenshots, videos). It is a perfect data analytics tool.
After running automated tests, a lot of time can be spent analyzing the causes of failures. Zebrunner Testing Platform solves this problem by using AI/ML automatic classification of test failure reasons. You can add links to bugs directly to Jira and GitHub so that the developer understands where and what needs to be fixed. Recurring problems can be identified using the test history.
Test process monitoring. Zebrunner Testing Platform gives management access to the QA process 24/7. Managers see release timelines, test coverage, ROI, KPI, so they can easily identify gaps in team productivity and optimize workload.
QA Teams Need the Best Data Analytics Platforms
Data analytics is crucial for QA processes. These companies need to invest in the right data tools to do their jobs successfully.
Healthcare organizations benefit from collecting greater amounts of data on their patients and service partners. However, data management is just as important. Smart healthcare providers are using ePCRs to facilitate data management.
ePCRs Help Healthcare Providers Manage Patient Data
Since they were widely introduced, Electronic Patient Care Reports (ePCR) systems have proven to be one of the most vital assets available to emergency medical service (EMS) providers. These systems have dramatically cut down the amount of paperwork for EMTs, paramedics, and other EMS personnel. More importantly, they have empowered EMS operations to save more lives with fewer resources by better organizing patient data.
However, most ePCR software have been around for decades and require an update. To date, some software developers specializing in ePCR for ambulance services have come up with many innovative updates, following the larger trends of big data, secure cloud hosting, and customizations, to name a few. If it’s been a while since your organization acquired its current ePCR solution, an upgrade is likely going to give you substantial benefits.
That said, not all ePCRs for ambulance services are made equal. To truly benefit from an upgrade, it’s worth considering these things before upgrading your system with an ePCR to manage patient data better. This is a way for emergency services to use data to improve patient care.
1.) NEMSIS and HIPAA compliance
The healthcare sector has to take data security and privacy very seriously. All ePCR software sold in the US needs to be compliant with the National Emergency Medical Services Information System (NEMSIS) and Health Insurance Portability and Accountability Act (HIPAA). Additionally, the vendor maintaining the software should have a good track record of maintaining compliance with both federal and state requirements. This will help your organization avoid potential legal issues related to the handling of sensitive patient data.
2.) Appropriate Customization Levels
Earlier generations of ePCR software for ambulance services still had plenty of kinks to work out, particularly in their customization features. For one thing, it was often too easy or too difficult to create data fields, with either situation causing all kinds of problems from errors and difficulty completing ePCRs to fraud and false claims. Thankfully, this problem has been solved with newer ePCR solutions, such as the one offered by Traumasoft. Whichever solution you do choose, it’s important that it could be customized to meet your organization’s needs while still maintaining the required standards for data security.
3.) Scalability
To address all issues with scalability, EMS providers should consider ePCR solutions hosted on cloud servers. Cloud-hosted solutions not only eliminate the need to maintain onsite servers and a large IT team, but they also tend to be less expensive to use and offer superior uptimes compared to most traditional locally-hosted solutions. Cloud hosting also simplifies operations for EMS organizations that are located in multiple geographic areas.
4.) Requires Minimal Training to Use
Given the lifesaving mission of EMS, onboarding users to a new system should not be something that uses up too much time and resources. If you’re going to choose a new ePCR solution, a functional one that’s easier to use and requires less training is usually a better pick than a fully-featured one that gives users a hard time.
5.) Vendor Reputation
Before going through with any big purchase, it’s important to check the vendor’s reputation. It’s no different when you buy ePCR systems or any other kind of essential software. Doing your homework helps you understand the level of service you can expect should something go wrong or should you desire any customization. And, as mentioned earlier, learning more about the vendor can also give you an idea of how well they maintain legal requirements and standards.
6.) Enables Seamless Data Standardization
Ideally, data documentation and formats should be standard throughout an organization. In practice, this is not always possible because of the specific needs of different departments of EMS organizations. Unfortunately, this situation can lead to a lot of accuracy problems when consolidating data for reports or data.
Thankfully, current ePCR solutions enable ambulance crews, back-office workers, and other stakeholders to easily draw data from one system. This removes the need for manual data wrangling and vastly improves data transparency and accuracy. Additional time savings could also be gained, thanks to the straightforward automation this standardization allows.
7.) UX Is Optimized for Field Conditions
One of the issues EMS providers had with first-generation ePCR solutions was the poor user experience (UX) for ambulance crews. Paramedics and EMTs work under very different conditions from personnel working in the station or back office. Given the practical constraints faced by ambulance crews, the relatively crude UX design of older software often-times led to frustration with ePCR systems and its underutilization.
Current systems that have addressed most of these problems are thus better suited for the common challenges faced by EMS workers. The improved UX also allows the organization to reap the full benefits of its ePCR solutions.
ePCRs Are Crucial for Managing Data in Healthcare Organizations
Vendors focused on ePCR for ambulance services now understand the needs of EMS providers better than they did a decade ago. This is an important part of using big data for healthcare providers. As a result, modern ambulance ePCR solutions are easier to use, more resistant to fraudulent activity, and enable a wider degree of synergy within the organization and with insurance providers. All of these translate to very real benefits for ambulance crews, healthcare stakeholders, and the communities served by EMS organizations.
Big data technology is incredibly important in many aspects of modern business. The sales profession is one of the areas most affected by data. Companies spent $2.8 billion on marketing analytics in 2020 alone. That figure is growing substantially each year.
There are many ways that big data is helping companies improve sales. One of the biggest benefits is that it can help automate many aspects of the sales process.
Big Data is Helping Improve Sales Processes Via Automation
It requires hours upon hours to establish relationships and constantly communicate with consumers to keep them happy. This could involve phone conversations, appointment setting, emails and much more. That’s a significant amount of time spent learning about your customers and their interests, gathering information, collecting data, and checking up. As your lead and client lists become longer, managing your workflow becomes more difficult.
Keeping track of login details, transaction data, openings, salesforce, goods, services, leads, and clients manually is a massive burden to the employees. Many traditional companies continue to gather data mechanically and run their sales operations using spreadsheets.
Every part of the business is affected by technological advancements, from how we present and scout to how we complete transactions. Due to the benefits of automated technologies powered by artificial intelligence and data analytics, sales staff may now concentrate on the most vital aspects of the sales cycle.
Sales automation is a pot of gold for marketing and sales organizations aiming to increase productivity and profitability. Smart companies are using big data to make it possible. They can get a lot of value from it by using big data to understand the sales pipelines and automate many processes. In this article, we will discuss how sales automation works and how to use automation to optimize your sales process.
Use big data to facilitate automation to save time during the sales cycle
When automating a sales process, it’s important to keep an eye on how well the system is working. You’ll inevitably make some poor judgments and allowing irresponsible blunders like emailing unsuitable responses or using the wrong contact name could damage your reputation.
This is where data analytics is going to come in handy. You can carefully review data to see how different aspects of your funnel are performing, which will increase the ROI of your funnel and help you identify ways to improve efficiency.
You must also ensure that your potential buyers don’t feel like communicating with the robot. If it’s clear that the interaction that’s supposed to be personal has been automated, or if you’re not answering a user’s inquiries or worries accordingly, they could lose trust in your brand.
Therefore, strengthen your existing protocols and technologies with automation. It should support what you’re already doing and make it smoother, not take over entirely. There are a lot of data-driven tools that can make this easier. Salesforce combines data analytics and AI to help sales professionals automate many important processes.
Try to incorporate automation throughout your entire sales cycle, from identification and getting familiar with your prospects to how you interact with them via emails, appointments, or phone conversations. Then, leverage lead assessment and selection to reach out to relevant potentials at the perfect time.
Handle your leads efficiently
Lead generation: By automating your lead generation, you’ll never have to worry about keeping your funnel full of fresh leads. You can control every operation by using cold email advertising, social network sales, personalized promotions, etc., rather than investing hours in attracting prospects.
Lead prioritization: After you’ve generated leads, which is typically the first step in the sales cycle, there’s usually a big pile of them. Now, how can you determine who is truly ready to pay for your goods or services? You must develop a framework of the ideal consumer and specify the criteria by which leads will be scored. You can use artificial intelligence-based lead scoring tools to sort them out. They assist salespeople in prioritizing leads and direct their efforts in the right direction.
Lead enrichment: Having more knowledge of the leads at the hunting stage is always beneficial. When it comes to B2B business, considering the prospect’s organization and what it offers, as well as its vendors and online presence, can assist salespeople in interacting with them effectively. They’ll appreciate the fact that you did your homework before pursuing them, and it will help you make a positive impression on potential clients and close more deals.
Close CRM can assist you in prioritizing leads and boosting income. With easy, user-friendly contact filtering, you can increase your reach rate. Create dynamic Smart Views that match relevant lead data, and then automate email and phone workflows around them. Identify your most promising leads, as well as those that have suddenly gone dark and more.
Nurture clients through email
Email lead nurturing means forming a tight connection between a company and its clients via email. There are many email marketing software that enables you to automate your emails. You can use it at any point of the process, and they benefit both parties in a transaction. Businesses have access to a low-cost, simple, and effective technique of reaching out to their users, and customized, well-timed communication makes consumers feel appreciated.
Email lead nurturing is effective not only for purchases but also for driving open rates, reminding prospects about your brand, providing quick results, and giving a platform to educate and engage leads. It’s a no-lose situation.
Thanks to sales automation solutions, creating drip campaigns is as simple as it seems. Usually, when a new entry for an inbound client is formed, an email is sent to greet them and to introduce the suggestion of booking a product demo. Then there’s a time gap to give the possible buyer some space. After that, they receive a persuasive email that’s supposed to push them into the next sales cycle phase.
Assaf Cohen, who runs Solitaire Bliss, a company that makes games for publishers, explains, “Follow up emails are incredibly important. My reponse rate improves with every successive follow up. However, it’s time consuming. Finding what to automate this allows you to do so much more.”
Close CRM ensures that you stay on top of your pipeline. Take advantage of automatic follow-up reminders, personalized templates, bulk emails, and other features. Send email sequences on a pre-determined timetable over the course of days or weeks. Design unique initiatives for your customers using a range of recommended pre-built features. You can monitor the delivery and reception of your emails, which helps your team assess the performance of each campaign and connect with potential customers.
Automate the scheduling and monitoring of sales calls
This is only useful for people who make a lot of outbound calls, which has become less of a focus for many businesses these days. If you’re still employing telemarketers, this can be beneficial because it eliminates a lot of complications from your operation.
Close’s CRM tool comes with an auto-dialer, but it isn’t necessarily a function that CRMs have. If your CRM doesn’t have an integrated auto-dialer, you can still use call center software that has that feature.
Handle RFP generation
The RFP outlines the project, its objectives, and the funding organization, as well as the tendering and contract conditions. Systems based on natural language processing/generation and robotic workflow control can assist cut the amount of time needed to generate requests for proposals (RFPs) by up to roughly 2/3 while eliminating human error.
For instance, it can analyze the unanswered questions and recommend solutions in a personalized document that you can automatically send to your lead. This type of technology can improve corporate version control and storage of key RFP material while also speeding up RFP response time and productivity.
Post-sales customer journey optimization
There are many reasons to use big data in marketing. One of the most important benefits is that data analytics can help you get a better understanding of your customers’ experiences. You can use this data to improve the funnel and boost customer satisfaction.
You can employ process automation to redefine the user experience and establish a smooth online purchasing, tracking, and dispute management procedure. Brands can utilize data technology to communicate with clients after the transaction in a lot of formats, for example:
Keep an eye on online reviews: In this era of technology, people do not call or write an email when faced with an issue. They use online comment sites and social networks to express their dissatisfaction and notify others. Furthermore, a single social media message can reach tens of thousands of people before a company can respond. A company’s failure to reply can give the impression that it doesn’t care about its customers. Businesses can use social media monitoring to receive notifications of any online comments, allowing them to respond swiftly and hopefully turn a dissatisfied consumer into a repeat customer. One of the tools that can come in very handy for keeping an eye on online reviews is justLikeAPI.
Special deals: Offering a discount on a client’s next order is a good strategy for increasing customer retention. This can be included in the follow-up message or completed at the time of the transaction. Every voucher should be valid for a limited time after the original purchase in order to entice customers to return, at which point they will be given a new coupon. It will not attract every buyer, but those who can’t resist a great offer will return.
Support is crucial
Even the best companies will have some difficulties now and then. Users should be able to seek support in different formats, whether it’s through a site, chat support with client care agents, email, or telephone conversation. The level of service provided to a customer will determine whether or not that client returns. It will also most likely define whether or not you will create a brand ambassador who will promote a company to their peers and social media contacts. Businesses should invest in a mix of automated technical support tools and personnel capable of offering clients prompt, polite responses when they encounter problems because this is a very important part of the sales process.
Characteristics of the best sales automation tools
All of your quotes and transactions are together: Custom quotations can be generated, maintained, and shared straight from your sales automation platform. Enable customers to confirm a section with a single click, transfer money, automatically turn quotes into sales, and send email alerts to sales representatives when offers are taken or denied.
A simple landing page maker: Go with a user-friendly interface that allows you to develop landing pages without knowing how to code. You should optimize your landing pages for smartphones and make them load as fast as possible. If possible, look for a landing page builder that includes first-rate royalty-free photos.
Automate and customize interactions: Take advantage of the information you’ve gathered in your customer database to nurture leads and increase revenue. Send a series of tailored emails using autoresponders, or create nurturing series based on specific activities.
Funnel management: Automated follow-up notifications, modeling depending on potential customer demands and trends, and statistics by product, main source, and other variables can help you simplify your sales process.
Merging with third-party systems: Consider the solution that works with the toolkits you already use. Do you have an online shop? Sync with Shopify, BigCommerce, WooCommerce, etc. Would you like to make your financial reporting more efficient? Sync with Xero or QuickBooks.
Visual appearance: The best sales automation tools are only as good as the graphics and design that they utilize. You need to make sure that your templates or slides are easily customizable and that you have the right fonts and images before you release them to your audience. Sales automation tools can be a great way for businesses to improve their company culture, but only if the slides and templates aren’t too difficult to customize. For example, including fonts and graphics is a great way we can make our templates more appealing for clients.
When not to use sales automation
Even though sales automation brings a lot of benefits, it cannot replace humans. AI has not yet evolved to the extent shown in sci-fi films. We’ve only recently begun to witness talking robots.
There are specific activities where software is no match for a person, no matter how advanced machine algorithms are. While AI can assist in making the client experience more personalized, it cannot produce new sales techniques. We use tools to execute rather than create sales strategies.
A fully automated client journey is neither recommendable nor possible to achieve. While chatbots can assist salespeople, they can sometimes feel somewhat impersonal. They can deliver user experiences that are robotic and monotonous. Your customers will eventually prefer to speak with a human over a robot.
Also, have in mind that automation tools are usually sophisticated software. You might not be ready to use them right away after acquiring them – you will have to learn first. Always have a well-thought-out strategy to examine each UI screen of the tools under review. Luckily, there are free trial periods because of this.
Customer relationship management system
CRM system is the most powerful digital tool you can use. These tools use data to help companies built the best relationships with their customers. It’s where most of your user information will be stored, and it will also serve as the hub of your sales pipeline. Everything your workforce must have about buyers can be found in your CRM or CRM-integrated software.
Investing in a CRM and moving your data there should be one of the first steps. If you still work with paper-based data, think about what can be transferred to a new system. This will allow automatic customer data updates and corrections and categorize by demographics or lead qualification characteristics.
Close CRM allows you to keep track of all of your sales operations in one place. Emails, calls, voicemails, assignments, and notifications are automatically arranged, so you always know what’s going on and what to do next.
Everything that requires attention is in your Inbox. Whenever you fulfill a task or return a missed call, that activity will disappear from the list. Close syncs everything you do to Inbox, ensuring you stay on top of your workflow.
Your CRM should speed up your sales process, not slow it down. Close was built with the salespeople in mind – it works the way you do.
Most of the manual processes that employees would have to handle – like altering contact details, arranging meetings, and possible closing deals – are eliminated by sales automation. It maximizes your productivity and performance while also saving your time. As a result, you are free to do business without worrying about administrative responsibilities.
Big Data Helps Automate Sales Processes
There are many great benefits of using big data to improve your marketing strategy. One of the biggest advantages is that it can help automate your sales processes. The tips listed above will go a long ways towards streamlining these functions.
Big data has become a very important part of modern marketing practices. More companies are using data analytics and AI to optimize their marketing strategies. This is especially true for companies using digital marketing practices, such as social media.
LinkedIn is one of the platforms that helps people use big data to facilitate online marketing. You can use their sophisticated analytics dashboard to improve your marketing strategies. Sprout Social has a blog post on accomplishing this.
However, there are other ways to use big data to get the most of your LinkedIn marketing strategy. One option is to use data analytics to improve your LinkedIn Ads targeting.
Data Analytics Can Improve the Performance of Your LinkedIn Advertising
It is well known that LinkedIn is built on big data. This creates a lot of advantages for its advertisers.
LinkedIn is essential for any business focusing on B2B outreach or trying to reach decision-makers in other organizations. With a formidable strategy, you can target your ideal audience, convert them, and increase sales. Fortunately, including LinkedIn’s audience targeting options in your marketing strategy helps you optimize your budget and reach potential clients and audiences with higher chances of converting.
Consequently, this article discusses six targeting options on LinkedIn and how you can use them to drive better results in your campaign strategy. You will get a lot more value out of them by using big data to improve your targeting strategies.
What Are the LinkedIn Audience Targeting Options?
Most experienced digital marketers are familiar with different targeting options across several social networks. They also realize that data analytics helps you improve your digital marketing strategies. Although most of these social platforms allow you to target people based on demographics or interests, LinkedIn retargeting options do more.
This section looks at the six LinkedIn targeting options available, including the following. If you pay close attention to the data in your reporting panel, then you can optimize your ad targeting for optimal conversions.
#1 – Location
LinkedIn makes the location targeting option mandatory for all ads. When using this option, your targeting can be specific or broad. For example, targeting people by city or metropolitan area is specific, while targeting people by state or country is broad.
Furthermore, with the location targeting option, you can reach people based on their IP address or the location listed on their profile. Also, if you are trying to reach people unfamiliar with your business, this targeting option allows the exclusion of locations.
You want to look at the data in your reporting panel. You may be surprised to find some regions convert much better than others, which will help you optimize your campaigns best. Always let your data guide you.
#2 – Company
One of the biggest benefits of the data infrastructure provided by LinkedIn’s marketing platform is that it allows you to target different companies. LinkedIn has extensive data on the companies in its network.
You can actually target your ads to people working at different companies. If you track your conversion data carefully, you will see which companies tend to drive the highest conversion rates.
Unlike Location, Company is an optional targeting method, and it contains several other options. These options include company connections, name, industry, size, and followers. Now, let’s look at these.
Through the company connections targeting option, you can reach any 1st degree employee connections at the companies you select. However, you can only use this option for companies having more than 500 employees.
Company name targets users based on their listed employer. The targeting option focuses on the company employees who maintain LinkedIn pages.
The company industry targets the primary sector where a user is employed, while company size targets users based on the size of the company that employs them. Similar to the company name option, company size is based on the number of employees listed on the company’s LinkedIn page.
Furthermore, the company followers targeting option focuses on people following your LinkedIn page. Therefore, before using this targeting option, you have to link your ads account to your LinkedIn page. Otherwise, your ads will reach both your followers and non-followers.
#3 – Demographics
LinkedIn demographics targeting option has two categories – member gender and member age. Member gender depends on what a user puts on their profile, while member age estimates the user’s profile information.
Data-driven marketers will take the time to review their conversion data to see which genders are most likely to convert. They can also use data mining to take a deeper look at the factors that drive conversions. They might find that women in some regions or age groups convert better than men with similar demographic factors and vice versa. You don’t want to make blind demographic targeting decisions without detailed data to guide you.
#4 – Education
The education targeting option targets users based on their field of study, degrees, and member schools. The field of study category focuses on a member’s degree’s major area of study. This option also targets people based on their selected degrees.
On the other hand, member schools target schools, colleges, or universities where users have completed courses. At the same time, degrees let you target the users based on their achieved rank at a learning institution.
You will also want to use data analytics to get better insights into the behaviors of people with different educational backgrounds. You will be able to make better data-driven decisions about your educational targeting. For example, you might find that STEM majors convert very well, while people with degrees in liberal arts do not. Nuanced insights like this can be derived from data analytics, which is better than just haphazardly targeting anyone with a bachelors degree.
#5 – Job Experience
Like the company targeting option, job experience also has several options for targeting users. Through job experience, you can target users based on their job functions. Please note that the job function is a standardized grouping of the job title a user enters.
Other targeting options under job experience include job seniority, job title, member skills, and years of experience.
Job seniority targets users based on their rank and position in their current position, while job title targets users based on their currently listed title. Fortunately, when users update their profile roles, LinkedIn algorithms group the titles and organize them into standardized ones.
The member skills function targets users with relevant keywords in the skills section indicating their expertise in such areas. This option is broad, and it includes skills entered by members, the skills they mention in their profile text, and the skills inferred based on what they list.
In addition, the years of experience option target users based on their accumulated years of experience. Because experience gaps may affect your ads, LinkedIn excludes them. Furthermore, the platform does not double count overlapping experiences.
#6 – Interests and Traits
The interests and traits targeting option reaches users based on shared group interests and individual member interests and traits. It is important to note that users’ interests and traits depend on their profile information, online engagements, and actions.
Data analytics can also give you more insights into the behavior of people with different traits and interests. You should keep detailed records, since there are so many variables to look at.
Use Data Analytics to Optimize Your LinkedIn Ads
There are several ways of targeting users with LinkedIn ads. Because of the several ad formats available, you can be creative with your ads, creating the ones suiting your target audience.
You don’t want to make these decisions without detailed insights derived from big data. Data analytics technology can make it a lot easier to get a high ROI from your LinkedIn Ads.
Furthermore, the audience targeting options discussed allow you to reach different users with higher chances of conversion. Nevertheless, you have to be strategic, flexible, and learn what works best for your business.
Human-operated ransomware attacks have threat actors using certain methods to get into your devices. They depend on hands-on-keyboard activities to get into your network.
AI can protect you in the event of these and other attacks. Since the decisions are data-driven, you have a lower likelihood of falling victim to attacks. The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience.
With AI, the risk score for a device doesn’t depend on individual indicators. Instead, it is influenced by a variety of features and patterns. They alert you when there is an imminent attack.
Even if attackers use an unknown or benign file, the AI system will ensure that the process or file isn’t launched. Here are a few ways that AI will supercharge your ransomware defense in 2021.
1. Predicting If a Device Is at Risk
Ransomware removal is great but preventing attacks is even better. If your device comes under attack, there are a few indicators to look out for. While they wouldn’t mean much in isolation, they are very meaningful when put together over time.
AI-driven protection assesses your device when a new signal is detected. Therefore, the risk score is always being adjusted accordingly. Signals to look out for include malware encounters, behavior vents, and threats.
If a device has wrongly been scored as ‘not at risk’ when it is really at risk, attackers could conduct activities that detection technologies will have a hard time catching. On the other hand, if a device is determined to be at risk when it really isn’t, customer experience will suffer.
AI technology finds the perfect balance. You get to find out if a device is at-risk without compromising on customer experience.
2. Identifying and Blocking Out the Abuse of Legitimate Files and Processes
Human-operated ransomware attacks have a hands-on-keyboard phase. During this phase, attackers take advantage of legitimate files and processes.
Network enumeration, for example, is naturally a benign behavior. However, observing it on a compromised device could prove that attackers have been performing reconnaissance activities.
Adaptive protection is designed to block network enumeration behavior. It cuts off the chain of attack, preventing more attacks.
3. Personalized and Contextual Protection
The blocking mechanism on the cloud is very responsive to real-time risk score computation. This means that the system can make informed decisions. They result in stateful or contextual blocking in your device.
The protection customization that comes with AI ensures that every device has a unique protection level. For example, process A may be permitted on one device and blocked on another. It all depends on the risk score.
The personalization feature is especially helpful for customers. They are unlikely to get false negatives or positives. Unlike ML models trained on datasets, every device gets the level of protection it needs.
4. Stopping Ransomware Payloads
Some attacks aren’t detected or blocked until they get past the mid-stages. With AI-driven adaptive protection, you can still get a lot of value on the final ransomware payload.
If your device has already been compromised, AI-driven protection systems will automatically use aggressive modes to block out ransomware payloads. They will prevent the encryption of essential data and files. It would be impossible for attackers to demand ransom.
Are you trying to improve your ransomware defense in 2022? Consider using AI to supercharge your efforts. It works by predicting if your device is at risk, stopping ransomware payloads, and offering personalized protection. Preventing these attacks is a lot easier on your business than dealing with actual attacks. Successful ransomware attacks can cost you your time and data.
Conclusion:
Ransomware has become a very serious problem in recent years. The good news is that advances in artificial intelligence have helped companies protect themselves. You should not overlook the importance of using AI as a first line of defense.
