In the first two installments of this series we covered the origins of big data and laid out the framework for using big data analytics to further your business. In this article we are going one level deeper, looking into how technological companies are applying big data analytics.

While the technology industry is diverse, all the tech sectors, including FinTech, Internet of Things (IoT), HealthTech, and MarTech, have one thing in common. Companies in each sector are using big data analytics to increase top-line revenue or decrease bottom-line costs by doing one or more of the following:

  • Making better strategic decisions
  • Understanding customers
  • Improving control of operational processes

Here are a couple of detailed examples of big data analytics applications in leading tech sectors.

Big data usage in the Financial Technology sector

In FinTech, the focus is on making better investment decisions.

  • Peer-to-peer lending platforms, like Prosper and Lending Club, are using big data to evaluate the risk level of a loan and to determine the interest rate of each loan.
  • Other organizations in the Financial sector, such as hedge funds and investment banks, are using big data to predict movements in the market and act on them. According to The Financial Times, some financial companies are evaluating connections between a huge variety of data – including satellite images, app downloads, social media activity, legislation, invoices, scraped web content, and more – to guide investment decisions.

Big data applications in the Healthcare Technology sector:

In HealthTech, some of the most exciting projects are about understanding patients in order to improve their treatment.

  • MIT researchers are planning to use big data analytics to eliminate the need for invasive diagnostic procedures. For example, they’re hoping to replace the invasive procedure used to measure intracranial pressure with a non-invasive procedure that produces the same measurement by synthesizing data from two easily obtainable brain wave measurements.
  • Zebra Medical Vision is applying big data analytics to X-rays, MRIs, and other scans. It does this with an auto-diagnosing system that applies algorithms backed by big data to scans. The algorithms can detect things that the eye cannot, for example a patient’s bone density score can be determined from a regular non-intrusive CT scan.

Big data applications in the Internet of Things sector

In the realm of IoT, there’s a lot of activity involving the improvement of operational processes. The operational processes that are getting improved vary significantly based on the type of sensors supplying the underlying data.

  • Disney has invested in a wearable device loaded with sensors called the MagicBand, which acts as an online wallet, ticket to attractions, and room key for customers at Walt Disney World.
  • Rolls Royce puts sensors on all its aircraft, helicopter, and ship engines. This allows engineers to study data from the engines such as vibration, pressure, temperature, and speed. With this, engineers can pre-diagnose engine problems and schedule maintenance to minimize downtime.

Big data application in the Marketing Technology sector

In MarTech the focus is on customer analytics, with companies cracking the code to provide a 360 degree view of the customer.

  • Here at Jumpshot, we’re using big data analytics to help our clients understand what their customers do whenever and wherever they spend their time online, mapping out path-to-purchase activity across multiple sites, campaigns and ecosystems. For instance, we recently used our data to detect the leading stocks for public interest, analyze Americans’ Netflix viewership and binge-watching behavior and identify how exclusive album releases by streaming music providers don’t foster customer loyalty. But these are only a few insights out of a vast sea that you can reach with Jumpshot’s marketing analytics platform.
  • Data management platforms (DMPs) use big data analytics to consolidate and analyze data from a marketer’s own systems, as well as third-party vendors. By analyzing the consolidated data, marketers get new insights into their customers’ actions on their properties, that may have been invisible before. For example, U.S. Bank uses Adobe’s DMP to get contextual insight into who the bank’s customers are, what they seek, and when and where they sought it.

Bottom line: Every industry is already touched by big data analytics. We explored how big data is used in various sectors of the tech industry to showcase the benefits of implementing big data analytics. There are multiple ways to use big data to further your business, from better understanding your audience to cutting operational costs. Only the future will tell which companies explore big data analytics to its full potential and which types of big data endeavors bare the most fruit.