Today, more and more organizations are taking advantage of data and the profound and wide-ranging insights that it has to offer. One industry that has begun to utilize data to inform decision-making is the healthcare industry. This is because data has the power to help healthcare organizations improve their processes in a number of critical ways.
Understanding how data can help healthcare organizations thrive is key to gaining a deeper and more nuanced view of how healthcare is evolving in the modern world. Here is how using data can help organizations excel in the healthcare industry.
Data Can Make Treatments More Effective
Improving the health outcomes of patients is one of the main benefits of data analytics in healthcare. By collecting, analyzing, and gleaning insights from patient-related data, healthcare organizations are able to provide better care to patients and reduce errors.
One of the key ways data allows improvement on efficacy of their treatments is by utilizing data to individualize care and identify patients who are more prone to certain ailments.
For example, if many individuals who work in the same industry develop a certain illness, data will allow healthcare organizations to help others from similar demographics stay healthy and, hopefully, avoid the specific illness.
Data Can Uncover New Treatments and Cures
Medical research is one of the important parts of healthcare and keeping the general public healthy. The more effective and efficient medical research becomes, the more new treatments for various ailments will be discovered. Data analytics can help streamline the process of conducting medical research while also allowing researchers to have a larger database to utilize when conducting data.
In today’s world, digital processes have become a normalized aspect of healthcare. One significant benefit of this is the fact that healthcare organizations now have the chance to record the data of scores of patients automatically. Accordingly, the more data is collected and utilized in medical research, the more treatments and cures can be discovered.
Data Can Help Healthcare Administrators Make Decisions
Data-driven decision-making in healthcare — the practice of utilizing data analysis to inform decisions — is a practice that is steadily gaining popularity among various organizations. This is because utilizing data analysis to make decisions helps healthcare leaders take a significant amount of risk out of their decision-making process.
For example, an administrator may assume that longer shifts for healthcare workers are better since it may allow employees to have additional off days for rest. When referring to data, it may be discovered that errors increase significantly among healthcare workers after working for six hours.
As such, healthcare administrators can utilize data to help them ensure that the decisions they make don’t have any surprising negative consequences.
Data Can Help Improve Efficiency
Anyone who has ever worked in a busy healthcare facility understands that it can be hectic given the seemingly endless number of processes and events going on simultaneously. This chaos can cause some processes to take longer amounts of time while also requiring more work for employees to get them done. Data analysis has the power to highlight areas that can be improved while also offering insights about ways to improve the efficiency of various processes.
The power of data analysis oftentimes lies in the fact that it can help one detect things that the human mind can’t detect on its own. These insights can be powerful as they can improve processes in a number of ways, such as by improving the efficiency of certain operations.
In healthcare facilities, becoming more efficient can result in being able to treat more patients while decreasing costs. As such, data analysis is becoming a staple in healthcare organizations keen on improving operations and becoming more efficient.
Data Can Help Data Management
In healthcare, scheduling, training, retaining, and managing staff can be incredibly difficult. To make matters worse, the healthcare industry has been experiencing a labor shortage, exacerbating the situation for healthcare administrators. Data analytics has the power to make managing healthcare facility staff easier and more manageable.
By utilizing data, healthcare facilities can improve in a number of ways when it comes to managing staff. These improvements range from analyzing data to discovering what makes medical staff quit to pinpointing key areas where new staff should be thoroughly trained.
By utilizing data analytics to manage employees, healthcare organizations will have an easier time thriving and operating successfully.
Data Analytics Is the Future of the Healthcare Industry
Data analytics is proving itself to be an incredibly powerful tool in the realm of healthcare. From helping uncover new treatments to improving the efficiency of medical facilities, taking advantage of data offers healthcare organizations a chance to reach their full potential.
As time goes on, it is more than likely that data analytics will become a normalized aspect of healthcare processes throughout the entire world.
Big data can be an intimidating concept. Whether you’ve been using it for a while in your business or you’re just starting to explore the possibilities, there’s a lot to consider.
Large corporations can hire dedicated data experts or even a full big data team, but small businesses have to be more selectively strategic in how they approach collecting and leveraging data.
There are so many ways that data could benefit your business and boost your growth. The best techniques to use will depend on your industry, audience, and other factors.
Here are some niche data tactics and uses to consider when planning your strategy.
Finding out WHEN Your Customers Buy
Ad spending can easily get out of control, especially if you’re not seeing much in terms of return on investment. One way you can use data to get more from your ads is to analyze when your customers do most of their buying.
Different groups of people have different habits, and if you’re serving a niche market, you might see some similarities within the data.
For example, if you’re marketing to mothers with young children, you might notice that they do their buying in the middle of the day when the kids are napping.
Leveraging data about the time orders are placed can allow you to adjust your marketing strategies for greater profitability.
Taking a Closer Look at Your Expenses
Every business has expenses, and it’s easy for those expenses to pile up. While some expenses can’t be reduced or cut, you likely have some that are unnecessary.
Data can tell you how much you’re spending and on what. Once you know, you can take a closer look and find out where you might be able to make cuts without sacrificing too much.
Figuring Out Your Most Profitable Product
Regardless of the products or services you offer, there are some that will be more or less profitable than others. But do you really know which of your products are your top performers?
There are lots of factors that go into profit, including factors like materials, labor, price, and margin.
Collecting data on these different factors can help you zero in on the products that are making you the most money overall. That information can be used to boost your marketing efforts, focus, and other strategic decisions.
It also might help you decide when and if to drop products or services that are taking more time and investment than they should.
Improving Your Customer Service
Data is important for getting to know your customers. This is critical for success in business — you need to know your audience if you want to cater to their needs.
Using big data, you can discover all sorts of important information about your best customers, such as how they prefer to communicate, what they’re buying, and how often they try to contact you.
That kind of information can help you improve your customer service efforts, without simply hiring more people. You can use data in different ways to optimize how and when you’re communicating with customers and how you handle complaints. This will help your business grow and help you build valuable loyalty.
Personalizing Your Marketing
Personalization in marketing continues to grow, and it’s not a niche reserved just for big companies. Small businesses can break their email lists down into different segments and send different deals and emails to each segment, catering to individual tastes.
Or, you can send different content to customers depending on their preferences. There are lots of tools available that can help automate these processes and make them more accessible for small businesses!
Figure Out Your Priorities
To effectively use data, you need to start with strong data mining practices. You have to continuously collect data from your business and organize it so it can be used to improve your business decisions.
However, that’s just the beginning. Once your data is prepped and ready for analysis, you need to set your priorities.
Begin by yourself how your data could best serve your business. Where are you seeing the biggest problems or opportunities for growth? Working on one niche area of your business at a time will help ensure that you don’t get overwhelmed.
Effectively using data isn’t always easy, but it’s well worth the effort!
Data is often perceived as a luxury of big business. It costs money. It also costs time and expertise. People go to college specifically to learn how to manage and interpret data.
What’s a layperson thinking trying to step up to the plate without the right credentials?
It’s true that data implementation at the highest level comes with barriers built in. Skills that need to be learned. However, small business owners can still learn a lot from numbers that are easy to interpret and use.
Data’s most natural application is to assign a number to questions. Using the numbers, you can better interpret tangible things that are happening in your business. Let’s say you are a coffee shop café. Using sales data, you learn that your paninis are underselling. Well, problem solved. Let’s cut them from the menu and— But wait, says Facebook.
When you post pictures of your paninis online, they get more engagement than any other food item on the menu. Well, that is a head-scratcher, isn’t it? People like to look at paninis, but not eat them?
You scratch your head, look around. There on the menu, which is posted above the cash register as always, you notice it. Paninis are listed at the bottom right corner of your board. Customers need to read every single other menu item before they can even know you serve paninis. Instead of being the best seller they could be, they are barely an afterthought.
When data is used the right way, it helps to piece things together in a way that you otherwise couldn’t. Without a more robust set of tools, the café owner probably would have discontinued the menu item. Now, they are using it to drive up sales.
Evaluate Success Relative to Goals
This same coffee shop that we mentioned in the last heading is on a bit of a mission. They want to create a Facebook group for their store. A hub of sorts where eager customers can come to learn about specials, and maybe get the occasional discount or secret menu item reveal.
Their goal is not only to have a lot of followers but gain five hundred impressions a day. They want their posts to hit and hit hard.
A surface-level glance makes it look like they are doing well. This restaurant hands out links to the Facebook groups on all their receipts and offers a small discount on a menu item for joining. And so people do join.
They have seven hundred and fifty group members, which would lead one to assume that five hundred impressions are well within reach.
But it isn’t. They get eight hits a day at best. Why? Well, a look at the numbers gives the answer. They aren’t posting at the right time. Their posts fail to follow a pattern. They don’t use the same sort of language with every post.
They don’t capitalize on momentum because they don’t recognize that they have it. Looking at the data, they recalibrate their post-scheduling. Now, they make sure to send something out very early into the world — stop in before work — and something a little later — stop in for lunch.
They focus on word choice, use more images, and bang! That impression goal is not only met but exceeded.
When data is used properly, it can paint a very vivid picture of what you need to do to meet and exceed your goals.
Keep Up with the Competition
Uh-oh. Another café is opening up right across the street from the one we talked about in our earlier heading. That seems rude. And also very problematic. Now, for the first time in his professional career, John — the store owner — has to field off a little bit of competition.
Let’s see what the data says about this. Using social media numbers, John can compare his numbers to those of local cafes, restaurants, and coffee shops. Through this information, he not only finds out that he is leading in post-engagement — thanks no doubt to his previous data implementation efforts — but also that there are still ways he can improve.
That’s one of the big benefits of data. Not only does it help you meet your goals, but it also makes it easy to redefine them. John’s impressions are high, but he realizes through comparative sales data that his conversions could be better. There’s always a little more to do in business, but with good numbers, your job becomes much easier.
A data pipeline is a technical system that automates the flow of data from one source to another. While it has many benefits, an error in the pipeline can cause serious disruptions to your business. Thankfully, there are ways to prevent them and avoid this company wide disruption. Here are some of the best practices for preventing errors in your data pipeline:
1. Use Automated Testing
Automated testing can help you identify and eliminate many potential data errors before they become an issue. These tests look for discrepancies between data sets and any unexpected changes in the flow of data. Automated testing can also help you identify and fix problems quickly before they become significant issues.
2. Monitor Your Data Sources
Data sources can be the most unpredictable part of a data pipeline. It’s essential to keep an eye on them and ensure they send valid data. For example, collect customer information from a satisfaction survey. You should check that the survey collects all of the data, including the customer’s name, email address, and other relevant data pieces. If you experience any unexpected changes or irregularities in your data sources, it’s best to investigate and address them immediately.
3. Check Your Data For Accuracy
Because the data you collect will be used to make company-wide decisions, staff must be diligent with checking for accuracy. Teams should double-check all data sources, ensure no data is omitted or incorrect, and conduct manual tests to ensure the information is accurate.
Data accuracy can be managed manually or with automated tools. Automated tools can help you quickly spot errors and fix them before they become an issue. When considering an automation tool, look for one that is reliable and easy to use.
4. Create A Backup Plan
No matter how much preparation this company does, there’s always a chance of an error. To protect against this possibility, it’s crucial to have a backup plan in place. This plan will help you quickly recover from a data pipeline error without too much disruption.
Creating a backup plan is essential, but it’s only effective if the team knows what to do in an emergency. Regular training sessions can help keep everyone up-to-date on the company’s contingency plans and familiar with new procedures.
5. Utilize Data Governance Policies
Data governance policies are essential for preventing errors in the data pipeline. These policies help ensure that everyone follows the same set of rules when collecting and handling data.
It’s essential to create these policies with all team members’ input and review them regularly. Data governance policies should also be communicated to all staff and enforced with appropriate consequences.
6. Invest In Quality Tools
Quality tools are essential for monitoring and managing data pipelines. Automation tools, such as ETL software, can help you quickly identify and fix errors before they become an issue. These tools also often offer real-time feedback to ensure that data is always accurate and up-to-date.
By investing in quality tools, you can quickly identify and resolve errors and avoid disruption to your data pipelines. Spending time researching and investing in the right tools can help ensure that your data pipeline is always running smoothly.
7. Use Logging And Auditing
Logging and auditing are essential for monitoring data pipelines. Logging can help you quickly identify any errors or irregularities, while auditing can ensure that the data is accurate and secure.
Logs should be regularly reviewed, and any anomalies should be investigated immediately. Auditing tools can also help to make sure that data is secure and compliant with industry standards. By using logs and auditing tools, teams can quickly identify and fix any issues before they become significant problems.
Data pipeline errors can be costly and disruptive, so it’s essential to take steps to prevent them. By following the tips above, you can keep your data pipelines running smoothly and ensure that the data is accurate and secure. Investing in quality tools, utilizing data governance policies, checking for accuracy, creating a backup plan, and using logging and auditing are all essential for managing data pipelines. With the right tools and practices in place, you can ensure that your data is always reliable and up-to-date.
Do you think a small business owner need not worry about cyberattacks? 46% of all cyberattacks impact businesses with less than 1000 employees. Small businesses have fewer resources to invest in the security paradigm. That’s why; hackers find it easy to attack such vulnerable systems instead of large corporations who have spent millions of dollars on cybersecurity.
A well-throughout cybersecurity plan will help your small business prepare for the worst, comply with the regulations, and show customers that their information is secured. Let’s get started with a comprehensive cybersecurity strategy for your small business.
Identify Threat Vectors
The first step of a well-planned cybersecurity strategy is identifying the avenues of attack in your system. Some most common areas where hackers tend to attack are;
1. Lack of encryption
This is something that you should not overlook if you are running any sort of business. Ensure the information you transmit to or from the network is encrypted to protect your sensitive information.
2. Malicious outsider
Sometimes, you do not need an external attack because you are nurturing a virus within your company. So it is always best to identify anyone with a malicious employee in your system.
3. Weak credentials
The cost of credential theft has increased by 65% since 2020. Never secure your credentials with weak or repetitive passwords, as it invites attackers to access your intellectual property and sensitive information.
4. Unpatched or outdated software
Keeping up-to-date with software patches is time and money-consuming but is extremely important to manage your security framework. If your information is stored in outdated software databases, add it to the list of vulnerabilities.
Misconfigurations are always a favorite venue for attackers, whether they are network configurations or application security controls.
Ensure your Legal Compliance
Before prioritizing your threats, risks, and remedies, determine the rules and regulations that your company is obliged to follow. If you already know about compliance standards, understand how they affect your security solutions.
Once you are done with enlisting your threat vectors, it is important to go through a risk assessment and create a prioritization list of your assets. Simply put, you must identify which components of your business hold the utmost importance and the level of vulnerabilities to those components. You can easily formulate the countermeasures for each identified threat by doing so.
Formulate Security Policies to Eliminate Risks
The next step is to ask, “how can I protect my business from listed threats? You must understand which countermeasures are effective for your system and how to incorporate them into your existing infrastructure. Protecting the network and utilizing access control protocols can make your system secure.
A firewall is a primary source to protect your network from hackers by making a wall between your system and network. All the information flowing in and out of your system is protected, and any suspicious actor trying to intrude into your network is prevented. Businesses make use of Virtual Private Networks to secure their applications and devices.
Access control protocols
The most basic protection is to secure the gateway so that no one can get access to your system without permission. That’s why Zero Trust infrastructure is getting traction in the mainstream. Zero Trust states that both internal and external environments can threaten your system, hence should not be trusted.
This approach was once a part of cloud data security but is now getting into endpoint security. Get a deeper insight into Zero Trust Endpoint security and understand how this integrated approach will help your plan cybersecurity for your small business.
Conduct In-Depth Training of Employees
Human error is always the main concern in a business’s cybersecurity plan. No matter how compelling and secure your plan is, unaware employees can cause havoc. Train your employees about your cybersecurity plan. They should be aware of potential threats within your system and how to respond in case of a cyberattack.
They should understand which security measures can put your business’s data and information at stake. ( do not open malicious or suspicious sites, do not log in with a business account on an insecure Wi-Fi connection, do not send sensitive information without confirming in person or over the phone, etc.)
Test Out Your Plan
Now that you have mapped out your security vulnerabilities and addressed the weak points, developing a plan comes the fun part. Plan your test to check if it’s worthy of implementation or not. An ethical hacker can access your business information or bring your network down.
There are several types of penetration tests you can consider.
White box test: A hacker is given information about the target business’s secret information.
Blind Test: A hacker is provided with the target company’s name only.
External Test: A hacker is tasked to attack the target company’s external technology, such as its website or external network servers.
Internal Test: hacker performs the task from the internal network of the target company.
Monitor and Update your Plan:
Although your security plan is effective, you should continually monitor your system to protect your digital assets. Ensure all the network and devices are encrypted, firewall settings are optimized, antivirus and anti-malware are installed, and everything is up to date. Cybersecurity is not something you do at once; it is a living document that must adapt to ever-changing security trends.
Create a Robust Response Plan:
A basic security framework will protect 98% of attacks, which means hackers can still get in through the cracks in your armor. In such cases, an effective response plan will reduce the losses if an incident happens. Moreover, ensure all your system’s critical components are backed up.
Hackers attack weak security infrastructure, so protecting your small business is a must-have. Now that you know the steps of a comprehensive small business cybersecurity plan, all you have to do is get started. Your small business might have limited resources. However, the aforementioned steps have highlighted key areas which will help you create a simple security plan for your small business.
Data is valuable to businesses of all sizes. Companies can use big data to assess performance, pinpoint problems, and identify opportunities. Businesses can also leverage big data to support machine learning by training AI and sophisticated models.
Although big data can be advantageous, the sheer volume of computer power and software services needed to support big data initiatives can impose a serious burden.
Companies need large, powerful storage solutions in order to collect, secure, and manage massive big data sets. The five most popular solutions include:
Many businesses fulfill their massive data storage needs with cloud technology. Cloud storage isscalable and affordable. Through the cloud, businesses can safely store data online so that authorized users can access it whenever and from anywhere.
Cloud services providers operate data centers all over the world. Users can upload or access their data through a secure web portal, website, or mobile app. Businesses hand over control of the majority of the data storage-related issues to the cloud-storage vendor. This includes capacity, security, data availability, storage servers, and processing power, and network data transmission.
Cloud storage providers also offer flexible plans that companies can scale up or down. This can save costs, as companies do not need to make significant upfront investments for storage capacity they do not use.
Cloud storage provides several benefits, such as endless capacity. Further cloud-based storage doesn’t require on-site devices which reduces downtime caused by broken equipment. Companies also do not need to purchase additional infrastructure to scale their storage or keep unused gear operational if demand declines.
Data storage on local hardware, such as servers, PCs, or other devices, is referred to as “on-premises storage.”
With on-premises storage, the company is in charge of all maintenance for the storage hardware. On-premise storage must be constantly upgraded to ensure security and effectiveness.
On-site storage has numerous advantages. For example, since data remains on site, there is a lower risk of data breaches. This may be of particular importance to businesses handling highly sensitive or classified data.
One major drawback to on-site storage is the lack of flexibility. Businesses scaling up their processes must increase their physical storage on-site. The company will need to install new hardware and hire IT professionals to build a new system. For a developing company, installing onsite storage solutions can be time-consuming and costly.
Colocation architecture is an innovative, secure storage solution. Through colocation, companies can store, operate, and manage hardware in “colo” data centers. These centers may be private or shared servers located on off-site third-party hosting platforms.
These off-site locations are becoming the new home for servers, firewalls, and other equipment for enterprise and mid-level businesses. There are several reasons why businesses choose colocation over other data storage options.
Colocation providers offer the choice between private or public cloud connectivity options. Companies can increase or decrease their storage easily and with minimal cost. Colocation also facilitates connectivity between businesses and supports technological integration and collaboration.
Additionally, colocation facilities often include redundant cooling systems to safeguard equipment and offer greater bandwidth than the average workplace. Click here to read more about the advantages of colocation.
Private colocated cloud-based storage can boost IT security and dependability. Pairing colocated and other forms of cloud-based storage enables technology administrators to be able to quickly increase resources in response to changing needs. This tactic reduces security risks while maintaining productivity.
Hard Disk Drives
A computer’s hard disk drive (HDD) can also store big data. These discs contain rotating parts that etch data onto a magnetic coating.
HDDs are one of the most cost-effective storage options for smaller businesses. Unlike cloud-based solutions, HDD storage is not volatile. This means that power outages or other system disruptions will not lead to data loss.
However, HDDs contain moving parts and are therefore more susceptible to damage than cloud-based storage systems. HDD also processes data more slowly. Portable HDD sticks can be lost or damaged, which would make any data stored inside irretrievable.
A solid-state drive (SSD) is a type of semiconductor-based storage system that typically stores permanent data in NAND flash memory. They operate at a higher speed than HDDs and do not contain moving parts. This makes them more durable. However, they are more expensive. Since SSDs process data more quickly than HDDs, they can reduce data processing bottlenecks and increase overall productivity. They also use little power and are resistant to power interruptions. They are best for storing frequently used data sets.
Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures.
The Global BPO Business Analytics Market was worth nearly $17 billion last year. This market is growing as more businesses discover the benefits of investing in big data to grow their businesses.
Unfortunately, some business analytics strategies are poorly conceptualized. One of the biggest issues pertains to data quality. Even the most sophisticated big data tools can’t make up for this problem.
Your business analytics strategy can only be as good as the data you’re using to feed them. If that data is tainted, inaccurate, or just plain wrong, your whole operation could be thrown off course. That’s why data cleansing is so important – it’s the process of making sure your data is clean, complete, and consistent before you use it for anything critical.
Here’s a closer look at what data cleansing entails, and why it’s essential for any business that relies on data analytics.
Data cleansing and its purpose
Data quality is vital to the viability of any business analytics model. Therefore, it is important for businesses to take reasonable steps to remove inaccurate, outdated and irrelevant data from their data sets.
Data cleansing, or data scrubbing, is the process of analyzing and improving the quality of data stored in a database or other system. Its purpose is two-fold: first, to ensure that all data meets its intended specifications; second, to identify and remove invalid or erroneous records that can disrupt the analysis process.
This rigorous process involves identifying duplicates and incomplete records, removing outdated entries, formatting data according to regional or design standards, correcting misspellings and typos, coding open-ended answers into predetermined categories, verifying values against external sources where applicable, and filling in missing fields where possible. Data cleansing activities incorporate techniques such as data deduplication and data standardization to ensure data is accurate and valid.
In summary, data cleansing helps organizations obtain reliable information that can be used with confidence in decision making.
Basic steps of the data cleansing process
Data cleansing is an essential part of data processing operations. It involves a four-step process: identifying, standardizing, removing unneeded data, and validating results.
First, identify the potential errors or inconsistencies in your data sets. This can be done using a data cleansing solution like WinPure that lets you identify the noise affecting your data. You can identify fields with odd characters, with typos, errors, and much more.
Second, standardize the way you are presenting the data so that each field is formatted correctly for analysis. Also known as data standardization, this process ensures all your records have the same standards – for example, all dates have a DD/MM/YY format.
Third, perform a data matching process to ensure there duplicates are treated or removed to ensure the data set does not have duplicates affecting accuracy.
Finally, the treated records are saved into a master record which acts as a unique dataset for teams to work on.
When all these steps are complete, organizations can be confident in the insights their analyses provide.
How does data cleansing improve business analytics
Data cleansing is an invaluable element for any organization looking to get accurate results from their business analytics. By standardizing, validating, and enriching data in a system, the organization’s data quality can be improved significantly which ensures that the analytics results produced provide an accurate picture of the current situation.
This kind of intelligence puts organizations at an advantage when making important decisions, giving them the power to recognize patterns and trends quickly without questioning the accuracy of the data. Data cleansing can also help boost the speed of analysis — by removing redundant or incorrect records, this tedious process becomes more efficient and worthwhile. As such, knowledge about data cleansing is essential for maintaining excellence in analytics-based decision-making.
The consequences of not cleansing data properly
Not properly cleansing data can be a costly mistake. Without cleansing, data sets may contain duplicated or outdated information, which could lead to flawed conclusions if used for analysis.
In addition, software that relies on organized and easily accessible databases may be compromised due to incorrect formatting. Even worse are potential security risks associated with leaving sensitive personal data within a dataset without proper cleansing.
Data that is unsystematic and includes unnecessary information can not only needlessly strain IT systems but can also attract cyber attackers who seek out weaknesses in network infrastructures. Companies should therefore always make sure to have procedures in place during their data collection process that ensure efficient and secure cleaning of datasets.
Tips for successful data cleansing
Data cleansing isn’t a one-time activity. It is a strategic activity that demands an understanding of the data and its sources, including causes of errors and what can be done to minimize the transition of poor data into downstream applications.
Companies can improve on the efficacy of their data cleansing efforts by first creating a series of data governance rules such as establishing data validation rules to ensure users don’t type in extra letters or numbers.
Additionally, providing data quality training to business users can help them identify as well as prevent errors – such as dealing with duplicate entries with the use of automation tools.
Staying organized, having clear objectives for each task and implementing an automated procedure for reviewing data will also help streamline your data cleansing successes.
A case study on how data cleansing impacts businesses
To demonstrate the impact it can have, two case studies are worth mentioning. The first belonged to a business providing marketing services. The company’s analytics always showed inaccurate customer acquisition figures. They always thought they were underperforming while in fact, they had been doing quiet well, which meant they were always changing strategies because the data did not reflect the effort they were putting in. The team decided to do a deep-dive into their data and identified that they had been obtaining duplicate entries caused by a flaw a web form! On rectifying the source of error and removing duplicates, the company was able to identify its best performing strategies and were able to amplify business outcomes.
To Conclude – clean data makes for reliable analytics
Big data strategies are only valuable if they are built on quality data. Therefore, companies need to take stringent measures to ensure the data they store is accurate, valuable and relevant.
By cleansing your data, you can improve its quality, which will have a positive impact on various aspects of your business such as decision making, customer satisfaction, and analytics. There are several common methods of data cleansing, including manual correction, standardization, de-duplication, and validation. When carrying out a data cleansing project, it is important to first assess the state of your data, identify objectives and KPIs, select appropriate methods based on those objectives, execute the project according to plan, and track results afterwards. With these tips in mind, you should be well on your way to improving your organization’s data quality.
Big data technology has become critical for modern life. A growing number of data scientists are being employed in various industries to help solve many challenges. The IT and cybersecurity sectors are heavily dependent on people with an expertise in data science.
You have so many opportunities available to you when you get a degree in data science or a related field. Keep reading to learn more about the career options that you can pursue in IT and cybersecurity if you have a background in data science.
Data Scientists Are Discovering Opportunities in Cybersecurity and IT
IT and cyber security are two of the fastest-growing career paths on the planet. They are two great fields for people with training as data scientists. Pretty much every business needs someone to help manage their technology needs. This demand will only grow as the world of business continues to drift into a decidedly digital direction.
Tech industry salaries also are usually very high, making this a great career path to consider. In this article, we take a look at IT and cyber security jobs that data scientists can do from home.
A Remote-friendly Career Path?
It makes sense that cyber security and IT can be handled remotely. After all, cyber threats can come from all corners of the globe. Why shouldn’t stopping those threats be the same? Since the pandemic, businesses everywhere have become increasingly receptive to hiring remote workers for several reasons.
If you have a degree in data science, then you will have a unique edge over other people pursuing a job in this sector. There are a number of benefits of using big data to prevent cyberattacks. You can use big data to improve risk scoring models and use real-time analytics to stop threats. You can also use predictive analytics tools to identify threats before they occur, so you can create a more robust cybersecurity system.
You will also get to enjoy the flexibility of working from home. For one thing, remote flexibility gives them the flexibility they need to enjoy talent from all over the globe. Historically, a St. Louis-based marketing firm (as an example) would more or less need to do all of its hiring from its general geographical area. That leaves them several hundred thousand people to choose from, but with only a small margin of that population being qualified for the job, the real numbers are actually very small.
By hiring remote staff, this marketing firm is no longer limited to local talent. They can get the best cybersecurity and IT specialists in the industry.
Cyber Security Analyst
Cyber security analysts essentially audit a business’s cyber security infrastructure. They look for points of vulnerability, make minor updates and modifications to the existing systems, and may even provide training recommendations for the staff.
This is one of the best opportunities for people with a background in big data. You will stand out better than other applicants, because you will be able to emphasize your knowledge of analytics. Analytics technology is the entire basis of this job, so a background in big data gives you an edge.
Hackers do not need to be close to a business to access its computer network. Attacks can happen from continents away, with the perpetrators never even knowing what the physical location they’ve attacked looks like.
The same goes for the “ethical hackers.” Ethical hackers are the lovable rogues of the cyber security industry. They essentially help businesses improve their cyber security networks by doing everything they can to break into them.
On a typical working day, they will assume the perspective of a cyber-criminal. As they work, they will try to determine natural points of entry into the business’s computer network.
Once they have completed their task, they will give the business a list of recommendations for how to improve their security, and they may even make minor repairs and updates to the network.
The actual responsibilities of this job are very similar to those of a security analyst. The only difference is that the job description reads a little bit like a 21st-century remake of To Catch a Thief.
The average ethical hacker salary hovers around $100,000. Like most cyber security jobs, the demand is very high, with job listings expected to grow by as much as 33% in the next several years.
You will have a lot of opportunities to do a great job with a background in big data. You will have a better understanding of artificial intelligence, which is going to help you mimic the AI-driven strategies hackers use.
Computer Support Specialist
Computer support specialists are essentially typical IT personnel. Almost every sizeable business has at least a few of them on staff to troubleshoot tech problems and keep the systems up and running nice and smoothly.
Most IT work can be done remotely, though there are situations in which physical proximity can at least be beneficial to their work.
Because virtually every business requires IT support, demand is always high. The average salary is lower than most of the other job entries on our list at $50,000. Still, it’s a rewarding career path for those with an interest in working in the tech industry.
Big data technology is going to be very important in this field as well. Modern tech support relies heavily on data analytics to perform better diagnoses, so you can do a better job with a background in data science.
IT Project Managers
IT project managers work to coordinate complex IT projects. For example, if a business is trying to build its own billing network to automatically send out invoices, it will need a vast network of programmers, but they will also need someone to coordinate the project.
In this scenario, the IT project manager essentially represents both sides of the project. Not only are they there to help make sure the company gets the exact finished product they are hoping for, but they also ensure that the development team has all the resources they need to get the job done.
It’s a challenging job. It can also be very rewarding for the right person. Growing at around 10% annually, these positions aren’t experiencing the same crazed demand as some of the other entries on our list. Still, the need for IT project managers is consistent, and with a median salary of around $90,000, it’s very lucrative work.
This is yet another field where big data is going to be very important. You will want to learn as much as possible to do the job right.
Data Scientists Have a Lot of Great Career Opportunties
It’s easy to sound paranoid when talking about cyber security. Threats actually are everywhere. In your local coffee shop. Lurking on the first page of your favorite search engine. In your email inbox. One small mistake can bring business empires to their knees. It happened to Marriot. It happened to Yahoo. It happened to the Irish healthcare system.
It can happen to anyone.
Supply chains happen to be a particularly appealing target to cyber criminals because they have many points of access, and they serve an important role. A cyber criminal interested in creating fear or instability can do so easily by preventing supply chains from putting products on shelves.
In this article, we talk about how vulnerable supply chains are to hacking. We also look at a few ways they can reduce these vulnerabilities.
The Short Answer:
How vulnerable are supply chains to hacking? Very.
There are several reasons for this. The main one is that supply chains consist of many small parts. The links in the supply chain are, in actuality, just people and businesses, each one of which is just as vulnerable to cyber crime as the rest of us.
When one link in the supply chain is disrupted, the problem can spread quickly. Cyber criminals can access entire systems just by getting into the computer of one person. The more people there are, the more vulnerable a network will be if it hasn’t taken appropriate measures to protect itself.
That’s precisely why companies like Yahoo, and Marriott have experienced major breaches, despite their incredible resources.
Supply chains are also naturally enticing targets for cyber criminals — particularly cyber terrorists.
One of the first high-profile incidents of this occurring happened to Target in 2013. Cyber criminals managed to access Target’s network, access sensitive data, and then remove it from their system.
This “kill chain” procedure harmed Target’s operations and resulted in millions of people having their personal and financial information compromised while also disrupting the mega-chains ability to serve thousands of communities.
How, you might ask, could a store as large as Target be so sloppy as to have its system compromised in such a significant way?
They used the wrong HVAC company.
That’s right. The mega retail chain contracted an HVAC company to do work in some of their stores. That company required access to its network. Unfortunately, their cyber security was very lax. Cyber criminals accessed their network and were able to piggyback into Target’s.
Supply chains are vulnerable in exactly this same way. With dozens, sometimes hundreds of links making up a single chain, there are many points of entry for criminals. With all this risk, what can supply chains do to minimize the threat?
Reduce Third-Party Vulnerability
In addition to the people working directly with the chain, each supply network will have thousands of thirty-party vulnerabilities — individuals and corporations not directly working for the supply chain, but working with it in a way that allows them access to its computer network.
Unfortunately, supply chains are only as strong as their weakest link. Any one of these third parties could potentially lead to a breach.
There are, of course, limitations to what can be done about this problem. Supply chain managers can mitigate the problem by standardizing their cyber security expectations, even among third-party vendors.
By requiring anyone to access the supply chain network to understand and follow best cyber security practices, it is possible to at least reduce the chances of experiencing a compromise.
It’s also important for anyone involved in the supply chain to be regularly trained on best cybersecurity practices. These lessons can be tedious and boring, but they are important. A significant number of breaches happen because of human error. Someone opens the wrong email, or logs onto a dicey wifi hotspot, and that’s all it takes to give cyber-criminals an in.
Train everyone to understand the gravity of best cyber security practices, and make sure they understand everything that is expected of them.
Regularly Audit and Update Security
It’s also important to keep in mind that cyber threats are constantly evolving. A cyber security network that was top of the line three years ago probably won’t stand up to some of today’s more significant threats.
If you want to make sure that your network is doing what it’s supposed to, consider the services of a cyber security analyst.
These professionals will examine your system for weak points — places a cyber criminal could use to gain access. They might patch small vulnerabilities, update firewalls, and provide general recommendations for how you can further fortify your network.
These services can be expensive, but they will ultimately be significantly less costly than a breach.
Cloud computing offers a number of important benefits for healthcare providers. One of the biggest advantages of cloud technology is that it helps make medical billing more efficient.
A cloud-based medical billing software program automates billing in order to help practices get paid faster, improve workflow efficiencies, help practice the IT solution for healthcare and keep patient information up-to-date. Moreover, it facilitates smooth digital workflows by reducing paperwork.
What Are the Benefits of Cloud-Based Medical Billing Technology?
Simply put, medical billing involves third parties in payment processes. As soon as the billers receive the necessary information, they prepare a claim for the insurance company. Managing claims, payments, and billing are all part of the billing cycle. Revenue Cycle Management is also known as RCM.
Medical billers and coders generally perform similar duties. In other words, their employment facilities are not as important as they once were. Patients’ diagnoses and treatments are documented with medical codes in clinics, hospitals, and physician’s offices.
The medical billing process can be very complicated. Fortunately, cloud technology has helped make it more efficient, as a recent report by McKinsey indicated. Some of the reasons that cloud-based medical billing technology is beneficial are that it reduces the need for an onsite IT infrastructure, it allows medical billers to seamlessly collaborate, can take advantage of machine learning technology and it has greater data security.
Medical billers can use cloud technology to do the following tasks more efficiently:
Records of patients are read and scanned
Code patient reports correctly
Providers can be billed using codes (the providers can be connected to insurers through the same cloud infrastructure)
Maintain accurate communication with physicians and assistants
Ensure patient data is kept up to date over time (the cloud makes it easier to update data from any location)
Keep detailed, coding-specific records (cloud technology makes it easier to store larger amounts of data, which allows for greater datail)
Ensure the confidentiality and security of patient information (cloud hosting services can be much more secure)
Search for information when coding is complex or unusual
Analyze and reassess patient records and documents
Examine and code the patient notes from the previous day
What are the Medical Billing Processes that Can Be Completed with Cloud Software?
The medical billing process consists of a series of steps that are completed by billing specialists in order to ensure that the medical professionals will receive reimbursement for the services they have provided. As a result, it may take as little as a few days, or it may take several weeks or even months to complete this process, depending on the circumstances. Medical billing workflows can vary somewhat from practice to practice, but the following is a general outline of what can be expected in a typical medical billing workflow.
Fortunately, new cloud-based applications enable medical billers to complete these processes much more quickly. Some of the steps that can be handled through these applications that are hosted on the cloud include the following.
A medical billing flow chart begins with patient registration. Patients’ basic demographic information includes their name, birthday, and reason for visiting. A medical biller verifies insurance information, including the policy number and the name of the insurance provider. During the medical billing process, the patient file will be referred to using this information.
In the next step, we determine who is responsible for paying for the visit. By doing this, we can determine what procedures and services are covered by the patient’s insurance. A patient is informed of the financial responsibility for procedures or services that aren’t covered.
At check-in, the patient completes forms for their file or confirms or updates information already on file, depending on whether it is a return visit. During the appointment, identification and a valid insurance card will be required, as well as copayments. Medical coders translate medical reports from the patient’s visit into diagnosis and procedure codes once the patient checks out. All the information gathered so far may be compiled into a report called a “superbill.”. Providers and clinicians will be identified, as well as demographics, medical history, and information regarding the services and procedures performed, along with diagnosis codes and procedure codes that apply.
Once the superbill has been generated, the medical biller will use it to prepare an insurance claim for the patient. When a claim is created, the biller must check it carefully for compliance with payer and HIPPA guidelines, including medical coding standards.
The next step is to submit the claim once accuracy and compliance have been verified. Most health insurance claims are sent electronically to clearinghouses, which are third-party companies that connect providers and insurers. Medicaid, which accepts direct claims from healthcare providers, is the exception to this rule.
Monitor Claim Adjudication
By adjudicating a medical claim, payers assess its validity and compliance and determine whether a provider will receive reimbursement. There are three possible outcomes during this process: acceptance, rejection, and denial. Depending on the insurer’s agreement with the provider, accepted claims will be paid. It is necessary to correct errors found on a rejected claim and resubmit it. When a payer refuses to reimburse a claim, it is called a denied claim.
Patient Statement Preparation
In the event that there are any outstanding charges, the patient is billed once the claim has been processed. Patients should receive a detailed statement that lists the procedures and services they received, the costs of those procedures and services, the amount paid by their insurance, and the amount the patient is responsible for.
A medical billing process concludes with the payment of bills. If necessary, medical billers must send accounts to collection agencies when patients’ bills are delinquent.
Write about top medical billing technologies
There are several medical billing technologies and top of them are the following.
As a medical billing software system, Kareo Billing has been developed for independent practices and specialties with medical billing needs. There are many health organizations that use this type of solution in order to build relationships with patients, while at the same time providing the best possible healthcare.
This system helps to manage a wide range of daily operations within a clinic, such as scheduling, claims management, billing, payment processing, revenue management and a lot more. It is used by a wide range of specialty clinics. It is estimated that over 60 million patient records are being managed by this platform at present
As Praxis EMR learns from its users, physicians are not restricted by built-in templates but can practice medicine uniquely. The application has been known for providing consistent user satisfaction and faster charting as a result. Document management, knowledge exchange, patient portal, and more are all included.
The company is one of the fastest-growing healthcare solution providers on Inc. The magazine names them among its fastest-growing companies among America’s private companies. Providers and medical billing professionals can use it to manage the practice, create health records, e-prescribe medication, engage patients, and bill patients.
The IT Solutions and Android apps on mobile devices allow medical professionals to easily handle clinical and practice activities on the go.
A cloud-based and customizable EHR system, NueMD is designed for a wide variety of healthcare organizations. Medical specialties utilize the software to manage scheduling, reporting, billing, health records, and more in order to provide improved daily operations, as well as a rapid return on investment for their investment.
Behavioral and mental health facilities can use TherapyNotes as an EHR system that is cloud-based. It automates tasks, streamlines daily operations, and optimizes workflows to help treatment centers improve the quality of care.
Nextech automates and streamlines administrative processes and workflows for specialty practices. While maintaining compliance with laws, it seeks to enhance the patient experience while increasing productivity and revenue.
There are several solutions it offers, including EMRs, practice management systems, revenue cycle management systems (RCMs), patient engagement systems, and compliance systems. A patient portal and billing automation are some of the key features.
What are the most common denials in medical billing?
It is extremely frustrating and disheartening to have your medical claims denied. There is no doubt that revenue cycle management (RCM) is an important and important part of your business. With the right digital solutions in place, your RCM process can be automated and streamlined, so it’s easier for your team to catch errors before a claim has even been submitted. With all-in-one electronic medical record (EMR) systems like Raintree, you can get operational efficiency, reduce denials, and get specialty-specific clinical documentation, to name a few. Using an all-in-one EMR system like Raintree will help you meet all your operational needs.
It is important, however, to acknowledge and understand the reasons why claim denials occur if we are to address them. Here are the three most common reasons why you might be experiencing denials in your practice:
Eligibility and registration
The claims are not submitted on time
Errors in medical coding
Why Are Denials So Bad for Business?
It’s not uncommon for an insurance company to terminate its contract with your organization if it receives multiple denials. Furthermore, an appeal can be an expensive and time-consuming process, so you should avoid getting denials as much as possible.
Insurance companies rarely provide explanations of benefits (EOBs) to help therapists understand why their claims have been denied, leaving them to research complicated coding criteria without much guidance. As a result of research time and the appeals process, payments can be delayed, extra duties for overworked office personnel are imposed, and sometimes even reimbursement deadlines are missed.
An RCM system that can generate an EOB with every claim can prevent therapy and rehab practices from losing income due to claim denials. You can ensure timely appeals of denials by using Raintree’s billing tools.
What’s Remittance Advice (RA)?
The remittance advice is a document that proves payment has been made by the customer to the business. It’s generally used by customers to inform businesses when invoices have been paid. A remittance slip is similar to a cash register receipt in a sense. Especially helpful when matching invoices with payments, they keep track of invoices.
As online payments become more popular, remittance advice slips are becoming less necessary. It is always appreciated to send a confirmation email after an invoice has been paid.
What should a remittance advice slip include?
The remittance advice slip must contain several key pieces of information. Among the most important information on the slip is:
Details of your address and name
Address and name of the supplier address and name of the supplier
The amount of the payment
Number of invoices
Your remittance advice slip should be printed on company stationery and include the contact information of a member of your team who can respond to inquiries from suppliers.
What is an EOB in medical billing?
In the medical world, “EOB” is a common abbreviation. The benefits explanation stands for that. A document showing how your health plan and you split your care costs arrives in the mail or to your secure online account. Your insurance provider may charge you out-of-pocket charges for certain services.
Your health plan will send you an EOB after you have had medical services or purchased equipment with your insurance card. You will receive an EOB when you receive a bill or bills, but it is not a bill itself.
What does HCFA 1500 mean?”
Health insurance providers use this form to bill healthcare providers. Medicare, part B, as well as Medicaid are billed using this form. In the United States, this form is maintained by the National Uniform Claim Committee (NUCC).
In the HCFA, you will find all the essential information needed to submit a precise claim. The healthcare provider must include the following information in this form;
The demographic information of the patient
An overview of the patient’s insurance
Codes for medical records
This form should contain accurate and factual information. Healthcare providers should be honest when filling out the form to avoid disputes. Insurance companies may refuse to honor claims if they detect irregularities.
Each health provider has a specific box. There might be different instructions provided by the payer on how to fill out some boxes. It is important for medical coders and billers to understand the requirements of certain payers.
Cloud-Based Medical Billing Technology is Changing Healthcare
Cloud technology is changing the healthcare sector. One of the many benefits is that it helps make medical billing more efficient. The purpose of medical billing is to generate healthcare claims for submission to insurance companies for payment for services rendered by providers. Cloud-based medical billing software should be used by all healthcare organizations and individuals for the growth of their business.