+44 (0)1892 512348

Blog

The 3 Most Practical Big Data Use Cases Of 2016

  |   INDUSTRY   |   1 Comment

Big Data is sexy. Data scientists are the unicorns of the job market right now. Some days, it feels as though we are living right on the edge of some science fiction utopian future. But unicorns and sci-fi aside, for businesses, implementing something like a big data strategy has to be more than sexy: it has to be practical.

Below are three examples of how effective use of Big Data is transforming various industries.

How big data is being used to drive supermarket performance

US-based family company Walmart, globally, is the largest company by revenue and employee count, with over 2.2m employees. With operations on this scale, it’s no surprise that they have invested heavily in data analytics over an already extended period of time.

In 2004, when Hurricane Sandy was imminently expected to hit the continental-US, attempts were being made to forecast demand for emergency supplies. As well as flashlights and emergency equipment, expected bad weather had led to an upsurge in sales of strawberry Pop Tarts in several other locations. Extra supplies of these were dispatched to stores in Hurricane Frances’s path in 2012, and sold extremely well when the time came.

How big data is driving success in manufacturing

UK-based Rolls-Royce produces enormous aero-engines used by over 500 airlines, and is a car manufacturer for over 150 armed forces globally. These engines generate huge amounts of power, which required dealing with huge amounts of numbers.

In high-stakes manufacturing, failures and mistakes can cost billions – and human lives. It’s therefore crucial that the company is able to monitor the health of their products to spot potential problems before they occur. As a result, Rolls-Royce put big data processes to use in three key areas of their operations: design, manufacture and after-sales support.

How big data is transforming healthcare

California-based computing firm Apixio was founded with a mission of uncovering and making accessible clinical knowledge from digitised medical records, in order to improve healthcare decision making. A staggering 80% of medical and clinical information about patients is formed of unstructured data, such as written physician notes.As Apixio CEO Darren Schulte explains, “If we want to learn how to better care for individuals and understand more about the health of the population as a whole, we need to be able to mine unstructured data for insights.” Thus, the problem in healthcare is not lack of data, but the unstructured nature of its data: the many, many different formats and templates that healthcare providers use, and the numerous different systems that house this information. To tackle this problem, Apixio devised a way to access and make sense of that clinical information.

As Apixio CEO Darren Schulte explains, “If we want to learn how to better care for individuals and understand more about the health of the population as a whole, we need to be able to mine unstructured data for insights.” Thus, the problem in healthcare is not lack of data, but the unstructured nature of its data: the many, many different formats and templates that healthcare providers use, and the numerous different systems that house this information. To tackle this problem, Apixio devised a way to access and make sense of that clinical information.

Apixio works with the data using a variety of different methodologies and algorithms that are machine learning based and have natural language-processing capabilities. The data can be analysed at an individual level to create a patient data model, and it can also be aggregated across the population in order to derive larger insights around the disease prevalence, treatment patterns, etc.

Read the full article here.

1Comment
  • Burchard | Oct 22, 2016 at 5:30 am

    That’s really thinnikg of the highest order