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8 big data use cases for businesses and industry examples

As the understanding of big data requirements increases, so do big data use cases. Here are eight ways businesses are using big data to improve operations.

Data is all around us and multiplying rapidly. In fact, data seems to be one of the only resources that can grow without limit, as long as we have enough places to store it and the computing power to handle it. Yet, big data is about more than size. Data volume is just one of the "V's" of big data. We also need to deal with the fact that the data can come in many varieties, change at different velocities and have different levels of data quality or veracity, among other attributes.

For businesses, the ability to deal with all these aspects of big data is important: Mastering the use of big data can bring companies significant business value, from enabling cost optimization and improved efficiency to providing better insight into customers and a world that is changing at an increasingly faster rate.

Many organizations have done just that. In this article, we'll explore eight use cases that show big data's profound impact on businesses across different industry sectors.

1. 360-degree view of the customer and better business intelligence

As technology becomes ubiquitous, our digital footprints are everywhere. From clicks and views on websites and mobile apps, to sensor data gleaned from real-world and virtual systems, the digital trail keeps growing. Organizations that use sets of big data effectively are learning more about their customers, users, patients and citizens, and then applying that understanding to serve individual needs. Advanced analytics software and dashboards powered by big data provide a more complete view of customer interactions and behaviors; many enterprises are combining data from a variety of internal and external sources to upgrade customer service, improve sales, optimize marketing, enhance products and services, and in general inject more real intelligence into their operations.

Rather than using traditional, slower methods of moving data into and out of data warehouses with static reports that take a long time to generate and even longer to modify, smart organizations are utilizing distributed, automated and intelligent analytics tools that sit on top of data lakes designed to collect and synthesize data from disparate sources at once. This has transformed business intelligence and analytics from a heavy, C-suite initiative to a widely enabled process that even lower-level managers can make effective use of.

  • In addition to applications across the private sector, governments and politicians are realizing the benefits of big data analytics. Big data is increasingly being used by political organizations and action groups to evaluate public opinion, craft effective messages and target their best supporters for financial support. During electoral campaigns, big data is used to spot trends ahead of polling, pool donor resources and get people to the polls when it matters most.

2. Improved customer acquisition and retention

By using big data, organizations have a better handle on what customers are interested in, how products and services are being used and reasons why customers stop purchasing or using offerings. Through big data applications, companies can more accurately identify what customers are really looking for and observe their behavioral patterns. They can then apply those patterns to improve products, generate better conversions, improve brand loyalty, spot trends earlier and find additional ways to improve overall customer satisfaction.

  • One of the best illustrations of this sort of use of big data is from Amazon, which implemented data-driven decision-making in the earliest days of the company's formation in the 1990s. Amazon measures everything, from how customers are browsing for products to which products end up in shopping carts and how various buttons are clicked. Other retailers quickly followed suit, and today most of the large online e-commerce companies are using insights powered by big data to inform the operations of the entire business and to keep customers coming back for more.
8 big data use cases for businesses
Enterprises across industry sectors are using big data to improve business operations.

3. Better fraud prevention and cybersecurity

Tackling fraud is a never-ending challenge for businesses. Organizations use big data analytics to identify patterns of fraud or abuse, detect anomalies in system behavior and thwart bad actors. Big data systems can comb through vast quantities of transaction and log data on servers, databases, applications, files and devices to identify, prevent, detect and mitigate potential fraudulent behavior. These systems can also combine internal data with external data from third-party sources to alert companies to cybersecurity threats that haven't yet shown up in their own systems. Without big data management and analysis capabilities, this would be impossible.

  • The financial services industry, especially credit card processors, can attest to the power of using big data in fraud detection. American Express, Visa, Chase Bank and similar companies use real-time big data processing to comb through billions of transactions on a minute-by-minute basis to identify and mitigate potential issues. Prior to deploying big data systems, these processors used complicated rule sets to determine whether a given charge was valid. However, the rule sets quickly became difficult to manage, especially in the world of online transactions.

4. Improved forecasting and price optimization

While it might not be possible to know what will happen tomorrow with certainty, big data is giving organizations the power to spot patterns and trends early. Spotting shortages early in the production of products, for example, gives organizations the ability to adjust accordingly, saving costly missteps all the way down the supply chain. Knowing demand for products early on can help improve sales forecasting or help determine the optimal price before a product even goes on the market. Indeed, big data has helped companies make better decisions by giving organizations information about the likelihood of what could happen in the future.

  • The retail industry, in particular, has been sensitive to volatility in costs, supply chain disruptions and variability in pricing and demand. As a result, retailers have increasingly turned to decision-making driven by big data to spot trends in customer behavior, analyze a variety of factors to determine optimal pricing, and better manage volatility in the supply chain as early as possible to optimize inventory, shipping and logistics. Retailers are even using devices and sensors to monitor customers' shopping behavior, look at the vacancy rates in parking lots, measure traffic in and out of the store, track which products are being selected and scanned, and monitor various product return rates. This data is then used to improve overall retail performance.
  • Walmart, for example, collects real-time data from its point-of-sale system for pricing, inventory and supply chain management -- roughly 2.5 petabytes of data an hour. The result is a highly optimized retail operation that can buy inventory almost just-in-time, managing its level of out-of-stock or overstock inventory, while also helping to optimize pricing and advertising promotion, as well as product selection and offerings.

In addition to helping organizations optimize pricing and forecasting, big data analytics is helping them streamline their operations and maximize profits. Big data provides opportunities to spot inefficiencies, identify areas for process improvement, reduce or remove bottlenecks, lower costs and reallocate resources in ways that can dramatically optimize overall performance.

Previously, organizations had to rely on reports, charts and not-so-real-time dashboards to get visibility into this data. The use of real-time big data analytics combined with flexible, on-demand data visualizations is putting the power of big data understanding in the hands of everyday managers to make better decisions, improve efficiency and generate better outcomes.

  • The healthcare industry has made effective use of big data to increase efficiency and improve patient outcomes. Modern healthcare management emphasizes data analytics to improve patient treatment, reduce costs in healthcare delivery, improve patient care operations, spot potential health trends before they become severe, and identify patterns that can foretell problems such as emerging pandemics and drug interactions.
  • The insurance industry has also made heavy use of big data for significant benefit, in particular managing and quantifying risk. By getting access to much larger volumes of data at greater speeds across different data types, insurance companies such as Allstate and Nationwide have been able to expedite claims processing, better handle insurance needs even in major disaster scenarios, and provide highly competitive pricing for policies given the visibility they have into their customer's behavior patterns. Big data has also helped them manage insurance costs and enabled the use of advanced recognition systems and conversational apps that allow for 24/7 customer interaction.

5. Improved personalization and recommendation

One of the most popular uses of big data is to improve product recommendations and personalization of websites and services. The challenge with online offerings is that there are sometimes an overwhelming number of choices. With all those choices, making the wrong decision can result in dissatisfied users and customers. Big data has powered some of the most significant innovations in recommendation and personalization systems, giving people hyper-personalized recommendations that best match their needs.

  • In addition to retail, the media and content industries have squeezed significant value from personalization powered by big data. Streaming service leaders such as Netflix, Amazon, YouTube, Hulu and Disney+ use their massive customer behavior databases to optimize searches, ratings and suggestions. They use all manner of information -- views, reviews, clicks, searches, time and date preferences, and other aspects -- to develop algorithms that can best predict customer interests.
  • Online advertising is also heavily powered by big data analytics. Ads are developed, promoted, shared and displayed according to very specific user behavioral metrics to optimize clicks, downloads and conversions.
  • Other industries making use of recommendation systems include finance, insurance, healthcare and even consumer packaged goods companies. They depend on behavioral data to inform decisions about what services and products to offer.

6. Content analysis of 'dark data,' aided by AI

Companies are now processing zettabytes of data overall. Much of that data is unstructured information such as blobs of text, videos, images, audio and other forms that can't be easily searched or processed. Yet, it is a treasure trove that companies can tap to do the following:

  • understand customer sentiment;
  • find recurring patterns in disparate data sources;
  • moderate user-submitted content for nonallowable items;
  • match content to advertising; and
  • provide transcripts of audio and video, and much more.

AI has enabled natural language processing of big data that wasn't possible in years past. Companies that figure out how to use NLP tools can tap into over 90% of the information in their enterprise that currently sits in storage doing nothing.

  • Large internet companies such as Google, Facebook, Twitter, Amazon, Baidu and others clearly understand the value of tapping into the massive volumes of unstructured data. These companies have mastered the art of content-based advertising and promotion designed to add value to transactions.

7. Preventive maintenance and support

Organizations have realized the benefit of using big data to help ensure their organizations and systems stay functional. For many industries, downtime is simply not acceptable and can lead to significant loss of business -- or even loss of life. Systems produce a lot of data in the form of log, sensor and IoT data, and other information that can give an early indication of the potential for failure. Organizations that know how to use this information can see greatly reduced impact from unscheduled outages, downtime, natural disasters or other disruptive incidents.

  • No industry sectors are more susceptible to outages than the energy and transportation industries. These industries have invested heavily in big data-powered predictive maintenance systems. While it is not possible to eliminate every single cause of outages or downtime, the ability for these industries to respond quickly, provide alternate routing or fallback, improve overall system performance and give visibility into system operation is more possible today than ever before.

8. Identifying and mitigating potential risks

The world is a complicated place with risks emerging at every conceivable turn. Anticipating, planning and responding to these changes and risks are critical to the longevity of any operation. Big data has proved to be helpful across the risk management spectrum, providing early visibility to potential risks, helping to quantify the exposure to risks and potential losses, and helping to expedite the response to major changes.

Risk models based on big data have proved their benefit across a range of industry applications, from customer and market risks to challenges emerging from government shutdowns to natural disasters. Companies can digest information from a wide range of disparate data sources and synthesize that information to provide greater situational awareness and understanding of how to allocate resources to deal with emerging threats.

  • Supply chain management and logistics firms have been particularly adept at using big data to help identify and mitigate potential risks. From closures that can result in supply shortages to unexpected demands due to natural disasters or pandemic-induced changes in buying behavior, supply chain and logistics firms have used big data to understand how best to apply limited resources to mitigate these evolving risks. In addition, security companies, both physical and cybersecurity firms, are making increased use of big data to inform their threat and risk assessments and thus mitigate new and evolving risks.

The power of big data is yours to tap

The above outlines just some of the ways in which big data is changing how companies across a broad range of industries operate.

We're well into several decades of experience dealing with big data, and the power is at your fingertips to make good use of it. In the coming decades, companies will no doubt depend on big data to respond to evolving needs, manage customer expectations, keep risks that threaten operations at bay, and provide increasing levels of customer and employee satisfaction. Companies that fail to make use of big data are at a significant strategic disadvantage against competitors that do.

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