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AI Technology Helps Consumers Improve Access to Financial Capital During Current Recession

AI Technology Helps Consumers Improve Access to Financial Capital During Current Recession

In April, a new report showed North American banks could use AI technology to save over $70 billion within the next three years. This is just one of the many reasons that financial institutions are investing more heavily in artificial intelligence.

It is easy to see why. Artificial intelligence is shaping the future of the global economy in significant ways. Moreover, the changes it is creating are more crucial than ever since the world is currently in the midst of one of the worst recessions in decades.

One of the problems with the recent economic setback is that many people struggle to access financial capital. Fortunately, new advances in artificial intelligence are helping improve this problem. This is one of the best ways AI is improving the financial sector.

AI helps consumers and businesses access financial capital more easily during the current recession

New advances in AI are going to be essential for people looking for personal loans. This is going to be especially important as the economy continues to experience stagflation.

Financial exclusion has been one of the consequences of the recent economic downturn. Many financial institutions have been forced to limit financing opportunities due to the ensuing credit crunch.

Unfortunately, many potentially creditworthy customers have been unnecessarily affected. In their attempt to be more cautious with lending decisions, financial institutions have implemented actuarial standards that deny funding to people that might be able to repay it.

Banks use AI to be more inclusive

Artificial intelligence technology offered promising opportunities to improve funding inclusion despite the ongoing economic challenges. For example, in April, the U.S. Chamber of Commerce held a seminar on AI applications that can help improve access to capital markets.

The keynote speakers pointed out that financial institutions are more willing to lend money to consumers and businesses after getting a better understanding of their spending and financial management habits. In addition, they are collecting more information on consumers to make better decisions about financing. Big data is unquestionably valuable to the financial sector.

Chris Cartwright, the president and CEO of Transunion, has pointed out that big data and artificial intelligence are helping level the playing field for consumers and organizations that have been denied financing in the past. They can get more meaningful insights by accessing other data points, such as rent history, driving records, and insurance payments.

AI leads to smart banking in cities

We have talked in detail about the sudden popularity of smart cities in recent years. Most of the discussions center around using smart technology to improve transportation and make buildings more efficiently run.

However, there are other important applications of artificial intelligence in smart cities. For example, one of the most important ways companies can use AI is by creating smart banking opportunities.

A recent symposium hosted in Korea talked about the benefits of using AI to make smart banking possible. One of the most significant opportunities is helping people use financial institutions without compromising their privacy. The CEO of one blockchain advisory group pointed out that 70% of the world does not trust their governments or banks, so this new banking approach will make things easier.

As more people take advantage of smart banking as an alternative to their traditional financial institutions, they will have an easier time qualifying for loans. Many of these people previously did not have any credit history due to their reluctance to use thanks. This change will help improve their access to financial capital.

AI creates opportunities with nontraditional lenders

Artificial intelligence is also helping consumers and businesses secure funding through nontraditional financial channels. A growing number of Fintech companies are making it easier for people to find lenders that will give them access to funding.

Many nontraditional lenders are able to provide loans that would otherwise be rejected because they have fewer expenses. However, they obviously couldn’t simply give loans to every person that applied. Therefore, they use sophisticated AI algorithms to assess the financial risks of potential borrowers. As a result, these fintech companies have found that AI has made their lending practices far more efficient and cost-effective.

As a result, many consumers have been able to get loans from them that they would not have received from traditional banks. This is helping improve financial inclusion.

Consumers and businesses should be optimistic about getting funding access during this recession as AI becomes more promising.

The recent economic downturn has put a damper on the economy. As a result, many consumers are frightened about their financial situations and seeking funding. Banks and other traditional financial institutions have been forced to taper back on financing opportunities.

However, they are coming up with new solutions. For example, artificial intelligence has made it easier to ensure consumers can get the financing they need. These changes should help make it easier to get loans or other capital.

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Top 7 Data-Driven E-Learning Trends Changing the Face Of Education

Top 7 Data-Driven E-Learning Trends Changing the Face Of Education

Big data has led to some major changes in the field of education. We have covered some of these trends in the past, but new changes are still emerging each year.

You should pay close attention to developments in big data in academia. Keep reading to learn more.

How is Big Data Affecting the State of Education?

The e-Learning industry is currently undergoing a revolution due to recent technological breakthroughs. E-learning began in the early 1990s as a means to enhance face-to-face teaching. Over the years, it has evolved into a new approach toward learning and development that outshines the methods it was supposed to promote.

While numerous businesses were affected by COVID-19, the eLearning industry grew significantly and demonstrated significant promise for technological advancement. Big data has been especially influential in the field of education. Experts anticipate the the market for big data in education will be worth nearly $48 billion by 2027.

The world is in awe of the potential of online learning. Organizations, educational institutions, and non-profit groups are now adopting online learning, usually delivered via a learning management system, or LMS.

With the growing interest in online education among the worldwide economic community, eLearning trends have shifted, resulting in significant technological advancements in the industry. Academic institutions are going to have to rely more on big data than ever.

In this piece, we will look at the top eLearning trends driven by big data that are taking hold in 2022, which will be the most useful in implementing eLearning programs across enterprises without taking a break from your learning and development process.

1. AI (Artificial Intelligence)

Artificial intelligence is one of the hottest e-learning trends. For better or worse, it is changing the state of education forever. The use of AI in online learning is becoming increasingly crucial, as it has demonstrated noteworthy potential in personalizing e-learning.

Learners’ competencies, weaknesses, preferences, and expertise are collected and analyzed using AI from LMS platforms. Learning platforms that use AI to make intelligent recommendations also help students absorb and gain knowledge more effectively.

Corporations and large educational institutions are utilizing artificial intelligence to create voice-enabled bots to make content searching easier. It will help the learners find the courses they want and enhance their learning experience.

2. Immersive Technologies.

Immersive technologies, like Artificial Intelligence (AI), have the potential to transform the e-learning landscape. They include Augmented Reality (AR), Virtual Reality (VR), and Extended Reality (ER).

Augmented reality (AR) is the most widely used immersive technology in e-Learning. This technology uses captivating pictures and graphics to supplement existing training materials.

Virtual reality incorporates 360-degree images, real-time interactions, and other intriguing components. These elements work together to bridge the gap between theory and practical application.

These innovations are still in their infancy, but the results they provide are impressive.

3. The Metaverse

The emergence of the metaverse opens up a whole new realm of possibilities for learning and development. Virtual reality is already one of the most popular eLearning innovations. An article published in ED Tech Magazine last month discussed some of these developments.

Technological breakthroughs in big data allow learners and instructors to communicate as lifelike avatars in a digital realm. Employees can access the learning area via VR headsets, smartphones, or PCs from anywhere in the world and benefit from group learning.

The metaverse also provides the kind of hands-on interaction that helps learners retain what they’ve learned.

4. Microlearning

Microlearning is a way of delivering bite-sized content to learners in order to encourage rapid knowledge consumption and retention. Small learning nuggets (2–7 minutes) generally replace long, text-heavy content in this form of learning.

As the flow of information has significantly increased, the average learner’s attention span is getting shorter. An employee has an average of 24 minutes a week to devote to professional growth. This innovative learning method has proven to be incredibly beneficial in L&D in combating the problem of short attention span and information retention.

5. Video-Based Learning

Static e-learning content is being challenged by video-based learning. Videos have recently become an important feature of online courses and will continue to be a focus of e-Learning.

Demos, tutorials, discussions, and how-tos in video format are preferred by today’s learners above plain text instructions.

There are numerous reasons to assume that video is the way of the future in education. For starters, videos are more aesthetically appealing, dynamic, and entertaining than text. These factors contribute to video content retaining the learner’s attention for longer than other types of learning. Even better, it encourages rapid information dissemination, improves content consumption, and boosts retention rates.

The widespread use of interactive videos, in particular, is causing waves in the e-Learning sector. The most effective thing about such videos is that they break the passiveness of conventional videos.

6. Adaptive Learning

Donald Taylor conducted the L&D Global Sentiment Survey in 2017. Adaptive learning emerged as the most popular L & D trend, knocking out AR & VR, Microlearning, and social learning.

Personalized learning is emphasized in this form of e-learning. In this type of learning, learners can learn at their own speed and leisure.

It uses powerful analytics, confidence-based evaluations, and pre-learning tests to assist businesses in avoiding the pitfalls of generic learning.

Adaptive learning, now being merged with artificial intelligence, is predicted to reach new heights in 2022. Learners are able to pick and select the learning paths they want to take based on their training requirements. It allows the learner to enjoy the process and get the most out of it. Organizations, on the other hand, can actively utilize resources to achieve optimal training ROI.

7. Mobile Learning

Mobile learning is becoming a part of many companies’ learning and development strategies. It allows learners to consume content whenever and wherever they wish.

The advantages of mobile learning, such as flexibility and adaptability, will ensure that this e-learning trend holds for many years.

E-learning will progress from mobile-friendly to mobile-first. The process of creating learning material for desktops and then customizing it for smartphones will be reversed so that a high-quality mobile experience is achieved.

It is especially significant because, as a result of the pandemic, more and more people are resorting to working and learning from home.

Big Data is Changing the Future of Education

With the widespread adoption of Learning Management Systems, education has become inextricably linked to big data technology, both now and in the future. Big data is going to be even more important to the future of education as new technological breakthroughs emerge.

Trends come and go, but the e-learning trends that we have mentioned above aren’t going away anytime soon. While we can’t predict exactly where e-learning will go in the future, these trends give us a good idea of where the sector will go in the following years. With online learning management systems, learning will be more interactive, mobile, customized, goal-oriented, and flexible in the near future.

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Ways Businesses Can Boost Logistics Performance with Analytics

Ways Businesses Can Boost Logistics Performance with Analytics

Smart companies realize that analytics technology needs to be at the core of their business models. One of the most important ways that analytics can help companies thrive is by improving their logistics.

Analytics Technology Helps Companies Bolster their Logistics Strategies

If you were cryogenically frozen twenty years ago, upon awakening, you’d probably be more shocked to learn that you can place an order on the internet and get it the same day, than you would about the world’s billionaires attempting to conquer space.

You would also discover the big data is at the heart and soul of modern organizational practices. More companies are using data analytics to optimize their business models in creative ways. This is particularly true with logistics processes. The IoT has helped improve logistics, but big data has been even more impactful.

Indeed, shipping and logistics operations have come a long way in recent times, so much so that Finances Online claims top-tier management of the supply chain “isn’t just believed to be one of the top drivers of customer service improvement. It is also a case of business survival”. This wouldn’t have been possible without more companies investing in data analytics.

Some of the ways that data analytics can help companies improve their logistics include:

Optimizing transportation routesImproving shipment schedulesReducing errors with delivery and pickup

On the journey from the click of your customer’s mouse to them opening the door to their delivery, convenience and efficiency are big factors that determine whether consumers will come back to you. For one, ensuring that delivery is as swift as possible is at the heart of current consumer expectations.

Analytics technology has been invaluable for improving the customer experience. Companies can identify transportation issues that lead to delays, find employees that are prone to make mistakes to retrain them and better track inventory with the use of data analytics.

But what else can firms do to make sure their operations are well-oiled? How can data analytics help with these other processes?

We’ve narrowed down the key strategies modern companies are using to enhance logistical management with data analytics technology.

1.      Vertical integration

Vertical integration is by no means a new concept, but it’s all the rage these days. As Investopedia spells out, this refers to when a company “streamlines its operations by taking direct ownership of various stages of its production process rather than relying on external contractors or suppliers”. In short, involves a business acquiring or creating its own production line and supply chain.

Cutting out the middleman allows companies to reduce their fixed-costs per unit, in what is known as economies of scale or diminishing marginal costs. Vertical integration optimizes operations for efficiency, and as the Balance suggests: “a company that’s vertically integrated can transfer the cost savings they create to the consumer” — although this comes at the price of a sizable initial investment. Alternatively, lower production costs mean that you can lower prices to incentivize more customer purchases.

Analytics tools make it easier to make better vertical integration strategies. You can mine data on potential supply-chain partners to make sure you aren’t acquiring a business that is not efficiently run. You can do this by using web scraper tools to collect data from company review websites and financial information on the company if it is publicly traded.

Enhanced outsourcing

The next best bet for those who cannot immediately establish their own distribution is through stronger collaboration with courier companies. Courier service CitySprint, for instance, has “34 dedicated hubs across the UK”. Using such a service allows companies to emulate the perks of vertical integration by having localized distribution networks, enabling them to offer services like same-day delivery. As a result, a firm that is unable to achieve full vertical integration straight away can still meet the current consumer expectations elevated by e-Commerce giants like Amazon

Again, you will want o use data analytics to make better outsourcing decisions by collecting data on potential contractors.

2.      Rationalizing SKUs

Analytics has also made it much easier to track inventory. This is often accomplished with the use of SKUs.

In the definition given by BigCommerce, “Stock Keeping Units [SKUs] are unique alphanumeric codes used by merchants to identify product types and variations”.

These are used by online companies to manage inventory, warehouse logistics and item specs with the use of inventory management systems with sophisticated analytics features. Your average supermarket will have, for instance, 15,000 of these — compared to the fast delivery services that use micro-warehouses and centers, and only have around 500-2000.

Simplified business processes

In simple terms, rationalizing SKUs means deciding whether the selling of specific products ought to continue. This way, businesses can streamline their offerings and reduce the overall complexity of their operations through the use of analytics.

While it might seem the more sensible choice is to have a diverse range of items for customers to choose from, holding too many SKUs can complicate logistics. If you have an excess of suppliers, data or you need greater amounts of storage space, this can make inventory management increasingly difficult and hamper the efficiency of deliveries.

Optimized inventory management

ShipBob clarifies that large retail companies use analytics tools to “keep track of all inventory in their large fulfilment centers and easily locate each SKU, so they can be accurately picked, packed, and shipped as orders are placed”. A popular analytics solution for this is through warehouse management systems (WMS), that organize data, including photos and other information, for fast retrieval.

By eliminating unnecessary SKUs at the delivery stage, businesses can limit back and forth communications with other parties like suppliers, as well as storage requirements, time and energy needed to create and package products that could be used in other parts of production.

3.      Integrated software and IT

The immediate perks of integrated business software revolve around efficiency, which is crucial for meeting customer expectations through the use of analytics technology. Most firms will rely on at least one or two business-critical platforms (such as digital banking, online shopping carts and/or cloud-based data storage), but any failure often results in a drop in productivity and revenue.

Transparent communications

For instance, the inability to provide proper transaction information (such as receipts and invoices) due to loss of data will damage a company’s reputation. To insure against this and other issues, more and more firms are turning to software and communications integration to reduce business-critical risks.

One of the perks of integrating software solutions is also the reduced risk of these scenarios occurring. Akibia argues that software integration helps track communications with clients, so that “you can efficiently resolve as soon as possible. The quicker you address your clients’ queries and issues, the more favorable view your clients will hold about the organization”.

Automation and efficiency

In logistics, a popular route to achieving better delivery results is through what’s known as carrier integration. While vertical integration consolidates the entire logistics process, carrier integration focuses on managing fulfilment processes and shipping data through a unified software and digital control center.

Once the shipper provides the location of origin and destination, the integrated software can identify what services are needed for each delivery and select the best packaging and carrier. This allows for the best possible response times since these processes are automated, saving time and user effort as well as eliminating the hidden costs of shipping execution.

Analytics Helps Companies Improve their Logistics

There are countless benefits of analytics in business. One of the biggest benefits is that data analytics can improve your logistics strategy. You should follow the guidelines listed above.

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8 Reasons Data-Driven Companies Are Utilizing Email Marketing

8 Reasons Data-Driven Companies Are Utilizing Email Marketing

Big data is at the heart of all successful, modern marketing strategies. Companies that engage in email marketing have discovered that big data is particularly effective.

When you are running a data-driven company, you should seriously consider investing in email marketing campaigns. Keep reading to learn more about the benefits.

Data-Driven Companies are Discovering the Benefits of Investing in Email Marketing

Allocating your marketing budget requires you to be careful, especially if you are a small business. A great marketing strategy can help you become a part of the big league society. After all, one of the factors that make a brand’s name big is its marketing.

Email marketing has proven to be a great tactic that helps boost your marketing efforts. This is among the most cost-effective methods, busting all the small business myths with regards to time and money. Many believe that emails are a secret weapon only for the big names in the industry. That’s not true. Even the smallest of businesses can use email marketing because of its accessibility and affordability.

Email marketing is even more effective when you use big data to optimize your strategy. There are a lot of reasons that big data can make your email marketing strategy more effective.

You don’t need several thousand dollars if you are using email marketing for your small business. That’s perhaps the true beauty of this method. You can get an even higher ROI if you know how to use data to personalize your content and refine your customer mailing list.

Another reason why emails are a great way to connect with your audience is their importance. Emails have entwined themselves in our lives so much that most people are known to check their emails even before they have gotten out of bed. You don’t want to miss out on this opportunity.

If you are still not convinced about why you should be using email marketing as a data-driven business, below are a few of the many reasons.

Cost-effective method

When you are a small business, the two biggest constraints that you have are time and money. While looking at your advertisement on a big billboard or on a television or a radio might seem very tempting, it is often quite costly.

If you are considering targeted flyer campaigns where you send flyers to the mailboxes of your prospects, you must also consider the money that you will be paying at the end of the day. The cost of designing, printing, and then mailing these flyers shouldn’t be overlooked; especially when these can cost quite a few dollars.

Such forms of marketing also require your precious time; the time that’s never enough anyway.

That’s where email marketing can do wonders. It’s quite a cost-effective method in terms of both time and money. Crafting an email and sending it to several prospects neither takes long nor does it cost too much.

You also get a chance to directly hit the prospect’s inbox, without spending all that money on the flyers!

You can make sure your email marketing strategy is even more cost-effective by investing in data analytics. You will be able to make sure that you identify the audience that is most likely to convert and provide the highest ROI. This can save you money that would be wasted on advertising to build your mailing list by targeting customers that are not likely to convert.

The best way to do this is by using the conversion reports and audience insights in the analytics dashboards of your email marketing platform. The data here will help you optimize your list-building strategy.

Establish yourself as an authority

In this world of cutthroat competition, you’ll not be able to participate in the race if you are not perceived as an expert. But the good thing is that email marketing helps you position yourself as an expert, especially in your area of business.

There are two ways for you to do this.

Firstly, share the content that is of value to the customers. Your emails don’t always have to be promotional or talk about discounts. You can share content that’s educational. The best way to do this is by sharing a newsletter, a blog, or maybe video content.

When you send value-added emails to your customers, it makes them understand that you are not just here for selling your product or service. This not only helps build your reputation as an expert but also makes business communications easy.

Secondly, you can try quality blogger outreach. To establish yourself as an authority, you can try guest posting, which is nothing but sharing content related to your business in collaboration with other bloggers on their website. You can add links to your website in these guest posts. This will make it easy for readers to visit your business site if they like what you have shared.

Guest posting allows you to target the blogger’s audience and establish yourself as an authority among that group.

A number of data mining tools make it easier to find quality content on the web, which you can use to optimize your own marketing strategy. You can also use data mining tools like SEMRush to identify the best blogs to submit guest posts.

Build strong customer relationships

Who doesn’t like to know that someone else is thinking about them? This can be your business for your customers.

When your customers feel that you care or at least you think about them whenever there’s some progress, it makes them feel special. As a result, it can make it easier for you to build strong relationships with them.

Whenever there’s an update, you must share that with your customers. Whether it’s a new product launch, any event that’s coming up, or big news related to your business, you can share it all with your customers.

Of course, if you sit and start calling them individually, it will take hours. Similar is the case with mailouts; they are costly and also a waste. That’s where sending emails can do wonders. Use emails to share more than the news of discounts or sales.

Moreover, if you have invited prospects to sign up for newsletters, you must leverage that fully.

Building customer relationships is a great practice for your business. It helps keep them around for longer than you might have anticipated.

You can build stronger relationships with data-driven CRM applications. As we pointed out in the past, data-driven CRM tools make it easier to build strong relationships with customers.

Improve brand recognition

Email marketing is a great method to improve your brand’s recall value.

When you strategize well, you will have particular days and time for reaching out to your prospects via emails. When you are continuously sending an email with your name and popping up in their inbox, there will come a day when they will be expecting your emails, or at least they will know from where do they know you.

Secondly, you can always add your logo, brand colors, and graphics in adherence to your brand manual/elements. When you add your brand elements to your emails, it improves your brand’s awareness. Consequently, it boosts brand recognition. This is because if you keep coming across certain elements, again and again, it does create an impact.

Hence, email marketing is not only to let your prospects know about your promotions but also to help them get ready for future interactions.

One of the benefits of email is that it has powerful data-driven AI algorithms that make it easier to automate your engagement with customers. You can specify when emails should be sent out, which makes it easier to remind customers at the right times to keep your brand fresh in their mind without annoying them.

Increase brand credibility

Increasing your brand’s credibility is perhaps of utmost importance, especially when the competition out there is overflowing.

After all, when you are new, selling your services over those that have been standing their ground for years can get a little tricky. One of the major reasons for your prospects to trust the big names is because of their marketing tactics. They have been hearing that name for much longer than yours. They are bound to get customer’s attention.

With the help of email marketing, you can build connections with your customers. Use this form of marketing to stay in contact and to keep them updated with all the exciting news about your business. Help them grow with your brand.

The more they hear about your business and the more they are aware of your progress, the easier they will find to trust your business over others.

An additional source of income

Yes, we know you already have a business that’s earning enough. But let’s be real, we all want more.

Several entrepreneurs out there are always in search of ways to make more money than they can invest back into their primary source of income. And email marketing can help you with that, without actually having to spend a penny.

You can use email newsletters to recommend products, services, or affiliates to your customers.

In return, for every sale that the other business makes with your referral, you can earn commissions. Just make sure that you are being genuine and recommending products that you yourself have tried. You don’t want to spoil your reputation just to sell others’ products.

Once you have enough audience, you can sell ‘ad space’ to businesses and earn commissions. Email marketing believes in a give and take relationship, which can turn out to be beautiful if managed well.

Expand your audience

At the end of the day, we all want to make more sales. And to make more sales, we need more audience.

Sometimes, performing an SEO audit to find practices that will help your website rank better and get in front of more people isn’t enough. You need more than that. That’s where email marketing comes into the picture.

With every visitor that shares an email using your ‘opt-in’ box on the website, you are expanding your database. This database is a true gold mine for you to do everything that we have discussed above. This includes building relationships, sharing knowledge, and improving your brand recall value. You can do this even with those that have only visited your website once and have shared their information.

Just keep in mind that for this to truly become fruitful, you must promote your email newsletter well. This means you must share about your newsletter via social media, on your website, and in your email signature. Basically, wherever and whenever possible. This is because people will only sign up if they know about its existence.

Track your progress

The best thing about email marketing is all the data that you receive and can analyze. In other forms of marketing, you don’t really know who actually looked at your ads or who skipped them.

With email marketing, you get to know everything that you want to. You get data that talks about who has opened your emails and those who haven’t. From those who have opened it, how many of them replied, what time did they open it, and how many times was your email opened.

You can use this data to tweak your follow-up emails, make them more tempting, and make your subscribers want to open your emails. You can also use this data to understand who is not interested at all. This saves you from sending emails to those doors that you know will never be opened, no matter how many times you knock.

This makes it easy for you to track your progress as well. You can easily run tests, see what’s working and what needs to be changed. Honestly, emails are a blessing in disguise.

This is the most important benefit of big data for email marketing. You will be able to use sophisticated data analytics features to test and optimize your email marketing strategy.

Email Marketing is a Great Option for Data-Driven Companies

Big data has become very important for marketing. One of the best ways companies can use big data to reach new customers and build their brand is with email marketing.

To wrap it up, we can say that email marketing can turn out to be quite beneficial, irrespective of the size of the business. You can use big data to get even more bang for your buck with email marketing. It helps you enjoy the best of all the tactics; from building customer relationships to sharing valuable content, small businesses can use emails as much as large-scale businesses. The best thing about this form of marketing is that you don’t have to spend too much time or money on reaching out to your prospects. Who wouldn’t want that?

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Built with BigQuery: How Exabeam delivers a petabyte-scale cybersecurity solution

Built with BigQuery: How Exabeam delivers a petabyte-scale cybersecurity solution

Editor’s note: The post is part of a series highlighting our awesome partners, and their solutions, that are Built with BigQuery.

Exabeam, a leader in SIEM and XDR, provides security operations teams with end-to-end Threat Detection, Investigation, and Response (TDIR) by leveraging a combination of user and entity behavioral analytics (UEBA) and security orchestration, automation, and response (SOAR) to allow organizations to quickly resolve cybersecurity threats. As the company looked to take its cybersecurity solution to the next level, Exabeam partnered with Google Cloud to unlock its ability to scale for storage, ingestion, and analysis of security data.

Harnessing the power of Google Cloud products including BigQuery, Dataflow, Looker, Spanner and Bigtable, the company is now able to ingest data from more than 500 security vendors, convert unstructured data into security events, and create a common platform to store them in a cost-effective way. The scale and power of Google Cloud enables Exabeam customers to search multi-year data and detect threats in seconds

Google Cloud provides Exabeam with three critical benefits.  

Global scale security platform. Exabeam leveraged serverless Google Cloud data products to speed up platform development. The Exabeam platform supports horizontal scale with built-in resiliency (backed by 99.99% reliability) and data backups in three other zones per region. Also, multi-tenancy with tenant data separation, data masking, and encryption in transit and at rest are backed up in the data cloud products Exabeam uses from Google Cloud.

Scale data ingestion and processing. By leveraging Google’s compute capabilities, Exabeam can differentiate itself from other security vendors that are still struggling to process large volumes of data. With Google Cloud, Exabeam can provide a path to scale data processing pipelines. This allows Exabeam to offer robust processing to model threat scenarios with data from more than 500 security and IT vendors in near-real time. 

Search and detection in seconds. Traditionally, security solutions break down data into silos to offer efficient and cost-effective search. Thanks to the speed and capacity of BigQuery, Security Operations teams can search across different tiers of data in near real time. The ability to search data more than a year old in seconds, for example, can help security teams hunt for threats simultaneously across recent and historical data. 

Exabeam joins more than 700 tech companies powering their products and businesses using data cloud products from Google, such as BigQuery, Looker, Spanner, and Vertex AI. Google Cloud announced theBuilt with BigQuery initiative at the Google Data Cloud Summit in April, which helps Independent Software Vendors like Exabeam build applications using data and machine learning products. By providing dedicated access to technology, expertise, and go-to-market programs, this initiative can help tech companies accelerate, optimize, and amplify their success. 

Google’s data cloud provides a complete platform for building data-driven applications like those from Exabeam — from simplified data ingestion, processing, and storage to powerful analytics, AI, ML, and data sharing capabilities — all integrated with the open, secure, and sustainable Google Cloud platform. With a diverse partner ecosystem and support for multi-cloud, open-source tools, and APIs, Google Cloud can help provide technology companies the portability and the extensibility they need to avoid data lock-in.   

To learn more about Exabeam on Google Cloud, visit www.exabeam.com. Click here to learn more about Google Cloud’s Built with BigQuery initiative. 

We thank the many Google Cloud team members who contributed to this ongoing security collaboration and review, including Tom Cannon and Ashish Verma in Partner Engineering.

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3 Smart Technologies Boosting Energy Efficiency Worldwide

3 Smart Technologies Boosting Energy Efficiency Worldwide

The growth of smart technology is one of the most beneficial trends brought on by advances in AI. It is projected that there will be over 77 million smart homes in the United States by 2025. Smart technology is also being used by businesses and government institutions around the world.

Many factors are driving the demand for smart technology. The quest for efficient and sustainable energy usage is one of the defining technological challenges of the modern age — especially as we find ourselves in the throes of the world’s first truly global energy crisis. Fortunately, data scalability has made smart technology more accessible.

Although this is a structural problem, it’s vital for individuals, families and businesses to optimize their energy consumption, both to mitigate the staggering prices and initiate a widespread move towards more mindful and responsible energy consumption.

Technological innovation has proved incredibly useful for this purpose, so we’ve compiled a list of smart energy inventions that are helping us all save energy costs and reduce our reliance on finite resources.

1.      Smart grids

We’re starting off big with the smart grid. This creation, which has been around for about a decade, is an electricity network (these power millions of homes at a time) that permits a two-way flow of electricity, using data-driven technology to detect and adjust energy usage.

The impact

One of their key benefits is that they can manage electrical transmissions and limit the amount of electrical losses in the distribution of energy. Not only does this improve overall efficiency, but it also reduces the risk of equipment failure and encourages the use of renewable energy by promoting the tracking and regulating of consumption. Around the world, more and more government administrations are increasing funding for grid modernization and the development of smart technologies.

The future

While the smart grid has been around for a decade or so, innovations abound. New alternatives to AC powered grids are being proposed, such as hybrid AC/DC smart microgrids. Studies have shown how these allow for greater flexibility and reliability, with research suggesting that the convergence is not only foreseeable but also necessary.

As it stands, many of the industrial converters that would be involved in a hybrid system are designed for “high active mode efficiency and low no-load power consumption, complying with the latest global energy efficiency standards”, as XP Power explains.

2.      Smart meters

We know this next innovation might not necessarily be news to you. After all, how many times have you received a letter in the post demanding that you “consider” switching to a smart meter?

The impact

On an individual level, these let individuals monitor their energy usage in real-time and automatically generate readings that can be easily communicated to consumers. Not only does this give them the option to find cheaper tariffs, but it also helps them identify the energy usage levels for different household appliances.

So far, it looks like this is working. Evidence suggests that there is a strong correlation between owning a smart meter and consistent changes in behavior in terms of attitudes towards energy usage and savings.

The future

A gradual incorporation of smart meters in households has been advocated by the EU, for similar reasons to the role of smart grids. Speaking with Smart Energy International, WiFore Consulting CTO Nick Hunn claimed that smart meters must be designed and implemented in all future energy security plans: “as we move to more renewables, distributed storage and an all-electric future, energy becomes a two-way process. That needs a completely different approach to meter design”.

3.      Battery storage

Following a similar principle to the household batteries in your TV remote, battery energy storage systems (BESS) play an increasingly valuable role in maintaining and supporting renewable energy. These storage systems accumulate and control energy generated from various sources of renewable energy, such as wind and solar, and reserve it using much larger battery technology.

The impact

Smart battery storage works by using intelligent software to coordinate the production of energy. This includes choosing when to store it to create reserves for future use, or allow it to be distributed into the grid. That way, energy can be released from the storage system when demand is at its highest, which limits total costs and removes the superfluous flow of electricity. Among other benefits, these help with peak shaving, whereby the storage systems “guarantee that no power above a predetermined threshold will be drawn from the grid during peak times”, as Ideal Energy Solar explains.

The future

Looking ahead, their wide-scale application seems inevitable. Power and Beyond argue that “with the rise of electric vehicles bringing lots more innovation in the battery space and the growth of solar power significantly driving down cost, now is the time when energy storage matters.” In the meantime, energy storage solutions could reach a new high in terms of overall market share by 2025, with the new pan-European automatic frequency restoration reserve market (aFFR) set to launch in 2022.

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10 Essential Data-Driven B2B Email Marketing Strategies

10 Essential Data-Driven B2B Email Marketing Strategies

Big data technology is leading to a lot of changes in the field of marketing. A growing number of marketers are exploring the benefits of big data as they strive to improve their branding and outreach strategies.

Email marketing is one of the disciplines that has been heavily touched by big data. If you want to make the most of your big data strategy, you should keep reading to learn how to incorporate data into email marketing.

How to Use Data to Improve Your Email Marketing Strategy

Email is one of the oldest and most reliable digital marketing tools around for good reason—it works. In fact, a recent study by the Direct Marketing Association showed that email marketing produces an average return on investment (ROI) of $44 for every dollar spent. That’s why it’s so important for businesses to get their email marketing campaigns right.

You can get even more value from email marketing if you leverage data strategically. Here are 10 essential strategies for email marketing success with data analytics.

Always Provide Value

Providing value means delivering content that educates, entertains, or both. It could be a helpful blog post, an insightful whitepaper, or just a quick tip. It should always be worth the reader’s time. If you’re not providing value, you will not get very far with your email marketing campaigns.

Yo can use big data to make this easier. One option is to use data mining tools to learn more about the challenges people are making. You can assimilate data from various polls to learn more about the pain points of your target customers and create content that addresses them.

Keep it Short and Sweet

In the age of information overload, people are bombarded with content from all channels. It’s important to ensure that your emails can be quickly scanned and digested. This means keeping your emails short, sweet, and to the point. Get straight to the point, and don’t ramble on.

Personalize Your Emails

Big data technology has led to advances in personalization. You can use AI technology to personalize content to give the best possible experience.

Personalization is key when it comes to email marketing. You want to make sure that your emails are addressed to the individual recipient by name. If you have any other relevant information about them (such as their company size, location, or pain points), be sure to include that in the email as well.

Test Different Calls-to-Action

Every email you send should have a call-to-action (CTA) included. This could be as simple as “Download our new eBook” or “Register for our upcoming webinar.” Your CTA should be relevant to the content you’re providing, and it should be clear what the reader needs to do next.

You will need to test different CTAs, which is going to require data analytics tools. Many email marketing solutions such as Hubspot and Aweber have analytics interfaces that make it easier to test different elements in your marketing funnels, such as CTAs. You want to use these analytics interfaces to optimize your CTAs for the best CTR and conversion rates.

Test Different Professional Email Signature

You should also use data analytics to test different email signatures. A professional email signature is a must-have for any B2B marketer. It’s a simple way to promote your brand and increase awareness about your company, products, or services. Plus, it can also drive traffic back to your website or landing pages. Be sure to include links to your social media profiles so people can connect with you through multiple channels.

Generate Timeless Content

Timeless content is content that will be just as relevant and valuable 6 months from now as it is today. This is the type of content you want to include in your email marketing campaigns. It’s evergreen content that will continue to generate leads and sales long after you hit “send.”

You can use data mining tools to find the best content on the web for your niche. Tools like SEMRush can make this a lot easier, since they have sophisticated data analytics tools. This will help you create the best content for your email funnels.

Use Alt Text for Images

Alt-text is the text that appears when an image fails to load. It’s also read by screen readers, which are used by visually impaired people. Including alt text with your images is a great way to make your emails more accessible and improve your deliverability rates.

You will want to use data mining tools to find the alt tags of similar images on the web. Tools like BeautifulSoup and Screaming Frog SEO use data mining algorithms to find the alt tags of different images, which you can use in your own content.

Test, Test, Test

Email marketing is all about experimentation. You must constantly test different subject lines, calls-to-action, images, and email templates to see what works best for your audience. Only through testing will you be able to optimize your campaigns and get the best results possible.

Again, you can’t possibly do this without the data analytics interface of your email marketing platform. Make the most of it!

Pay Attention to the Details

The little things matter when it comes to email marketing. From the “From” field and subject line to the design and layout of your email, all of these details can affect your open and click-through rates. Take the time to ensure that every detail is perfect before hitting “send.”

Automate Your Emails

Another huge benefit of big data is that it has made it easier to automate your email marketing funnels. With email automation, you can send triggered emails based on specific actions that your contacts take (or don’t take). For example, you can set up an automated welcome email to be sent to new subscribers or a follow-up email for people who don’t open your first email. Automating your emails can save you a lot of time and help you stay in contact with your leads and customers.

You can also hire Advertas to help you reach your email marketing objectives.

Big Data Has Made Email Marketing Easier than Ever

Email marketing is a critical part of any successful B2B marketing plan. Big data technology can help immensely. By following these strategies, you can ensure that your campaigns are successful and that you can generate the leads and sales you need.

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Fintech App Development Discover the Benefits of Using AI

Fintech App Development Discover the Benefits of Using AI

The rapid pace of digitization has caused fintech markets to boom around the world. The market for Fintech was over $112 billion last year, but is projected to be worth over $333 billion by 2028.

During this wave of disruption, successful business owners and startup founders need to understand the technologies that are driving the industry forward. Artificial intelligence is one of the most important trends pushing the envelope of what’s possible with fintech. Let’s talk about AI’s benefits in fintech, especially in terms of app development and how you can use it to maximize the success of your business.

When Fintech Meets Artificial Intelligence

AI can benefit financial technology in a number of ways. It can result in more active user engagement, secure payments, and efficient workflows. From these benefits ultimately come cost savings. Since the tasks AI can perform reduce time significantly, teams can invest more in other aspects of a project. So it is not surprising that AI use ​​in the fintech market is growing. Mordor Intelligence predicts that the technology’s value in the industry will grow at a CAGR of 23.17% until 2025.

Fintech app developers are adopting AI in their applications to solve a number of business challenges, such as providing a high level of customer support. Since AI can automate customer service to a degree with chatbots, AI assistants and other methods, teams can spend less time on repetitive questions and focus on more complex cases.

Artificial intelligence is also adept at data processing and analytics, both useful tools for financial applications. It can be leveraged even more effectively with Agile technology. Interpreting data to generate valuable insights on analytics for consumers can help users improve their financial habits and achieve their financial goals easily. It can also help businesses plan for the future and make wiser investing choices. That’s why artificial intelligence is widely used in budgeting apps, financial assistant apps and investment platforms. For example, the world’s popular money management apps such as Cleo and Fyle have AI at their core and leverage the power of this technology to provide intelligent financial tools. This gives them competitive advantages and opens additional business opportunities.

Top Use Cases of AI in Fintech

Let’s review some use cases to get a deeper insight into how AI can empower the fintech app development process.

OCR for Processing Receipts and Invoices

Document digitization is one of the most time-consuming tasks that finance teams face. In addition to this, often the concept of a fintech application includes fast and automatic recognition for receipts, invoices, and other financial documents to enable accurate spending tracking, KYC/AML processes, reporting, and so on.

Based on Optical Character Recognition (OCR), apps like Extracta, and Klippa solve these challenges by converting financial documents into accessible text in minutes. All the user has to do is take a photo of the invoice with their phone and run it through the program. Simplifying the process like this makes it easier to keep track of costs and reduces the manual effort required to do so. This can also reduce the cost of data entry for businesses, as this process becomes automated with OCR.

Using OCR for KYC processes allows you to automate the verification of documents such as an identity card, driver’s license or passport. The AI ​​should be able to determine the required data like name, photo, address, and contact details and extract that info for further validation. All this is done in a matter of minutes and significantly speeds up the identity verification process.

Natural Language Processing for Speech Recognition and Voice Assistants

One of the many challenges fintech has had to overcome in the past few years is how to automate financial assistance. With the rise of consumer assistants like Siri, Amazon Alexa, and Google Assistant, it seems possible that AI can provide financial assistance and advice as well. Many banks have already begun to utilize chatbots powered by natural language processing, also known as NLP. This technology leverages AI to communicate with humans more seamlessly.

NLP chatbots can automate the workflow and collect valuable data through these interactions. They are also sensitive to details like mood and satisfaction. With NLP, AI can also search through documents more effectively and present them to users in a streamlined form. By taking complex documents and simplifying them into a more digestible format, AI can help users understand how to improve their financial behaviors.

AI Biometrics for Authentication

Keeping financial data secure is essential to prevent fraud. That’s why AI biometrics in fintech applications are becoming more common. It’s a misconception that biometrics are impossible to trick. Many hackers aren’t using complicated console commands to hack into your system. Instead, they’re using printed-out selfies to fool facial recognition and fake fingerprints. While traditional biometrics may be fooled by these spoofing methods, artificial intelligence is more resilient. AI can detect unusual patterns in behavior to prevent threats.

Predictive Analytics

Artificial intelligence works best when paired with real-time data. With financial technology apps, predictive analytics has a number of benefits. For example, users can get forecasts on their income or expenses in the future. This is a useful feature included in many budgeting and financial assistant apps.

Predictive analytics is helpful not just for consumers. In fact, there are more profound applications of predictive analytics for fintech businesses. Being able to forecast demand and revenue, improving cash flow management, and predicting financial risks are all ways that fintech companies can remain relevant in the modern market.

Key Challenges of AI in Fintech

As exciting as the benefits of artificial intelligence for fintech app development are, to be successful, you need to understand all the challenges of implementing AI in fintech. Partnering with expert fintech developers will help you get around these complexities and create a quality AI-powered fintech app.

Bias

Many assume that artificial intelligence is the most objective way of completing tasks. However, this isn’t true. Although AI may act autonomously, it relies on our instructions. That data is provided by humans and is subject to bias. Good engineers know how to mitigate this bias. The first basic step is to compare and test different samples of training data for representativeness.

Compliance and Privacy

Regulations are another important challenge. Since AI relies on high-quality and high quantity data, staying compliant with data collection laws is crucial. A few laws that firms will need to pay close attention to are SOC2 Type II, HIPAA, GDPR, and CCPA. The full list of regulatory frameworks will depend on your region and what kind of data your application will handle.

Success Metrics

Metrics of success for one fintech firm may be different than another. Users may not check the app every day and instead have different behaviors, such as once a month or during an important financial change. Just because they aren’t using the app as often doesn’t mean the app has failed. Seeing if the app has helped change their behavior while offline may be even more important. The user should feel more in control of their finances as a result of using the application.

Wrapping Up

The development of fintech is closely related to the adoption of AI technology. Artificial intelligence helps create smarter applications that can improve the efficiency of financial management and compete with traditional financial agents.

However, implementing AI in fintech requires deep technology expertise, so don’t hesitate to enlist the support of experienced fintech developers. With the right team, you can leverage the power of AI to maintain your fintech application’s relevance for the foreseeable future.

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Use Data Analytics to Benefit from Fibonacci Retracement Levels

Use Data Analytics to Benefit from Fibonacci Retracement Levels

Data analytics has led to some major changes in the field of finance. Financial institutions invest heavily in big data technology in order to offer the highest ROI to their clients.

However, individuals are also using big data to improve their own financial strategies. One of the ways that savvy investors are leveraging big data is through the use of technical analysis. This helps them increase the ROI of their own trading strategies.

You can use data analytics to build neural networks to take advantage of Fibonacci retracement. This is one of the best ways to grow your portfolio through using data analytics as a financial trader.

Using Data Analytics to Improve Your Trading Strategy with Fibonacci Retracements

You can use data analytics to improve your technical analysis strategy with Fibonacci retracements. However, you first need to understand what these are.

How can you use Fibonacci retracements? Fibonacci retracement levels are horizontal lines that indicate where support and resistance are likely to occur. They are based on Fibonacci numbers, which are a series of numbers in which each number is the sum of the previous two.

You can use data analytics technology to make the most of these technical analysis tools. Towards Data Science has a great guide on this, which entails building neural networks to handle them.

The most popular Fibonacci ratios are 23.6%, 38.2%, and 61.8%. These ratios can be found by dividing one number in the series by the number immediately following it. For example, 21 divided by 34 equals 0.618, or 61.8%.

Traders use Fibonacci retracement levels to identify potential support and resistance levels on a price chart. They will get more value from them if they use data analytics effectively.

How to Use Fibonacci Retracement Levels?

Fibonacci retracement levels are typically used as a larger technical analysis strategy. For example, a trader may identify a stock in a long-term uptrend and then use Fibonacci retracement levels to time entries during pullbacks.

The most important thing to remember when using Fibonacci retracement levels is that they are not exact numbers but rather zones where support or resistance is likely to occur. Therefore, using them in conjunction with other technical indicators or chart patterns is often best.

It can be difficult to identify these zones on your own, which is why data analytics tools can be so helpful. They have AI algorithms that can identify important data points and help you determine the right buy and sell points to boost profit.

Fibonacci Retracements vs. Fibonacci Extensions

How to use Fibonacci retracement? While Fibonacci retracement levels identify potential support and resistance levels, Fibonacci extensions are used to predict potential price targets.

Fibonacci extensions are based on the same Fibonacci numbers as Fibonacci retracement levels. However, instead of dividing one number in the series by the number immediately following it, Fibonacci extensions use division by two numbers further down the sequence. So, for example, 23.6% is found by dividing 21 by 89 (21/89=0.236).

Fibonacci extension levels are typically used as a larger technical analysis strategy. For example, a trader may identify a stock in a long-term uptrend and then use Fibonacci extension levels to predict potential price targets.

What Do Fibonacci Extension Levels Tell You?

Fibonacci extension levels can help you predict potential price targets. However, it is important to remember that they are not exact numbers but rather zones where the price is likely to reach. Therefore, using them in conjunction with other technical indicators or chart patterns is often best.

Fibonacci Retracements vs. Fibonacci Arcs

How to use Fibonacci retracement? While Fibonacci retracement levels and Fibonacci extension levels are based on the Fibonacci numbers, Fibonacci arcs are based on the Fibonacci ratios.

Fibonacci arcs are half circles drawn from a price move’s high to the low. The most popular Fibonacci ratios used for Fibonacci arcs are 23.6%, 38.2%, and 61.8%. These ratios can be found by dividing one number in the series by the number immediately following it. For example, 21 divided by 34 equals 0.618, or 61.8%.

How to use Fibonacci retracement? Fibonacci arcs are typically used as part of a larger technical analysis strategy. For example, a trader may identify a stock in a long-term uptrend and then use Fibonacci arcs to predict potential price targets.

What Do Fibonacci Arcs Tell You?

Fibonacci arcs can help you predict potential price targets. However, it is important to remember that they are not exact numbers but rather zones where the price is likely to reach. Therefore, using them in conjunction with other technical indicators or chart patterns is often best.

The Formula for Fibonacci Retracement Levels

The Fibonacci retracement levels are based on a mathematical formula to calculate the Fibonacci numbers. The formula is as follows:

Fn = Fn-1 + Fn-2

where

Fn = the nth Fibonacci number

Fn-1 = the previous Fibonacci number

Fn-2 = the Fibonacci number before that

The first two Fibonacci numbers are 0 and 1, so the formula starts with:

F0 = 0

F1 = 1

Each subsequent Fibonacci number is the sum of the previous two. So, the next Fibonacci number would be:

F2 = F1 + F0 = 1 + 0 = 1

and the one after that would be:

F3 = F2 + F1 = 1 + 1 = 2

Why are Fibonacci Retracements Important?

How to use Fibonacci retracement? Fibonacci retracement levels are important because many traders use them to predict potential support and resistance levels.

The Fibonacci numbers are a sequence of numbers first discovered by Italian mathematician Leonardo Fibonacci in the 13th century. The sequence starts with 0 and 1, and each subsequent number is the sum of the previous two. So, the next number in the sequence would be 1+0=1, followed by 1+1=2, 2+1=3, 3+2=5, 5+3=8, 8+5=13, and so on.

The Fibonacci numbers have been found to occur naturally in many places, including in the arrangement of leaves on a stem and the spiral of a seashell.

The Fibonacci ratios are derived from the Fibonacci numbers and are used by traders to predict potential support and resistance levels. The most popular Fibonacci ratios are 23.6%, 38.2%, and 61.8%. These ratios can be found by dividing one number in the series by the number immediately following it. For example, 21 divided by 34 equals 0.618, or 61.8%.

Fibonacci retracement levels are important because many traders use them to predict potential support and resistance levels. However, it is important to remember that they are not exact numbers but rather zones where the price is likely to reach. Therefore, using them in conjunction with other technical indicators or chart patterns is often best.

Use Data Analytics Tools to Create Neural Networks to Spot Fibonacci Retracement Levels

Data analytics technology can be very effective at creating neural networks, which is invaluable for financial traders. You will want to make the most of them, especially if you are depending on Fibonacci retracement levels as indicators for your technical analysis trading strategy.

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4 IT Management Best Practices Data-Driven Businesses Must Practice

4 IT Management Best Practices Data-Driven Businesses Must Practice

Data-driven businesses are far more successful than companies that don’t utilize data to their advantage. Unfortunately, they often find that managing their data effectively can be a challenge.

Companies that rely on big data need a reliable IT department. You have to make sure that your IT infrastructure is adequately equipped to handle the volume of data your company will be processing and that it will be properly secured.

Companies that Rely on Big Data Must Have a Functional IT Department

Due to modern advancements in big data technology, the IT sector is becoming more competitive with each passing day. Companies leverage modern technologies to streamline business operations and gain a competitive edge in this competitive marketplace. According to EasyVista, more than 70% of companies worldwide will have invested in digital technologies in 2022, which will increase in the coming years. This figure will increase as big data becomes even more important.

These numbers indicate that embracing IT organizational structure best practices 2021 is the key to staying competitive, streamlining business operations, and outperforming competitors.

While businesses are constantly looking for ways to grow as a whole, sometimes they often invest in the technology that generates no results. In fact, according to Gartner, it is expected that business owners will spend $750 million on investing in ineffective features of IT tools, up from $600 million in 2019. Thus, it is wise to implement a few essential ITSM best practices to combat overspending.

You have to make sure that you invest in the right technology to make the most of big data. Keep reading to learn how to do this.

What Is the Role Of IT Management In a Data-Centric Organization?

IT management plays a crucial role in every organization. Companies that rely on big data have to use it even more. IT managers are responsible for planning, coordinating, communicating, and leading computer-based activities in an organization. Moreover, they are also responsible for researching new technologies and understanding how they can help the business grow.

In short, they help determine the department’s needs and implement the best practices to fulfill the organization’s system requirements. Besides researching new technologies and streamlining the tech operations, they also seek to mitigate IT risks, such as threats to cybersecurity and misalignment between IT professionals and business requirements.

The IT department in an organization focuses on meeting the following objectives:

Enhance the overall IT processDeveloping employees’ skills to meet the future organization’s needsMaintenance of transparency within the companyControl the financial aspect of the IT department

IT management is also responsible for organized IT business operations. They implement the best practices and regularly measure the performance to understand which areas need improvement. This will help you make the most of your data resources.

4 Best Practices For IT Management in Companies that Rely on Big Data

Companies that depend on big data will need to follow these practices to create a functional IT department.

1.      Build A Clear Strategy

Initiate your journey by defining your business goals and vision. Develop a roadmap vision for your IT service management goals, as well as the types of data that you intend to store. Then, create a systematic approach to measure your efforts, define KPIs, and the state at every stage of the implementation process.

A roadmap should cover all three essential domains, including:

Front-end IT: It includes service design, service operations, and service transition. The perfect example of front-end IT is Service Desk applications.Middle IT: It includes business frameworks and automation efforts.Back-end IT: It includes leveraging modern technologies such as AI, IoT, robotics, etc., to help executives make informed business decisions.

You have to get this part right as a company that depends on big data.

2.      Invest In The Right Technology

A business that invests in the right technology invests in its overall growth. It will also make employees more efficient at work, resulting in streamlining business operations. However, choosing the right tool can be challenging, especially for startups.

The reason is that they don’t determine their business needs, and they have a tight budget, too. However, it doesn’t mean investing in cheap tools and regretting later. Instead, it is wise to monitor your business needs and invest accordingly.

Digital transformation has taken over the corporate world like a storm. Most businesses have embraced digital transformation technologies to automate tasks and improve the employee experience. Artificial Intelligence performs human-like tasks like problem-solving, speech, and text recognition.

Moreover, it can accomplish specific tasks by analyzing vast amounts of data and recognizing recurrent patterns in these data recurrent patterns. According to Transparency Market Research, the global market for AI is estimated to gain 36.1% CAGR between 2016 and 2024. It is expected to reach a soaring height of $3,061.35 billion by 2024. Thus, investing in such technologies can benefit your business a lot in the long run.

3.      Seek Help from Top Management

Your decisions can make or break your business. To ensure business sustainability and revamp the business operations, involving senior management in the process can be a better option. They are well-experienced executives and know what’s good and bad for a business.

Without the involvement of senior management in the business decision process, revamping the IT department for business success may become an enormous challenge.

4.      Remote Work Expansion

It would be almost impossible to discuss the recent changes in the corporate world without mentioning the importance of remote working. Thanks to the pandemic; it introduced the remote work or work-from-home model across companies worldwide.

Today, companies must adapt to modern corporate world changes to boost employees’ productivity and overall business growth. However, if you believe that returning employees to the office will enhance productivity, you are mistaken. According to Flexjobs, more than 94% of companies report that their productivity has been the same (67%) or higher (27%) since employees started working remotely.

Another benefit of embracing the remote work model is that you are no longer limited to hiring local IT talent. You can boost your business efficiency by hiring talented folks across boundaries.

IT Management is Crucial for Companies that Depend on Big Data

Adapting to modern changes is challenging, even for companies that utilize big data effectively. You can’t create a successful data-driven company without a dependable IT department. You need to be clear about your goals and accordingly plan, communicate, and implement the right strategies that contribute to your business growth.

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