3 Industries You Didn’t Know Are Using Big Data

Big Data is transforming the lives of people and the daily operations of companies. Though Big Data analytics has created billion dollar companies like Amazon and Google, for most traditional companies Big Data analytics is a hurdle that has yet to be overcome. While McKinsey Global Institute estimated that major retailers can grow their operating margins by over 60 percent by utilizing big data analytics, three quarters of big data experts from major corporations say that Big Data analytics has helped them increase revenue or decrease cost of doing business by less than one percent. This said, there are many examples of traditional companies leveraging big data and getting outstanding results. Some of the industries where companies have achieved great results through big data analytics are retail, healthcare, and finance.

Big Data in Retail

Retail has been revolutionized by Big Data. An especially big change occurred in the last few years when the multi-screen experience became the norm. This change has been caused by the increase in mobile usage which has redefined consumer purchasing patterns. These new purchasing patterns require retail companies to take advantage of new means of data gathering and analysis.

Before Big Data, the customer experience was always the same. Big Data has allowed a greater degree of personalization; retailers have started using big data analytics tools in order to understand purchasing trends and customer identities. Another form of personalization came in the form of product information specifically tailored to customer’s purchase history.

Big Data gave rise to product information management which is a set of methods for managing product information in a manner most suitable for product marketing and selling. Product information management, on the other hand, gave new meaning to omni-channel experience. Retail stores have started using all forms of marketing, including social media and mobile apps, in order to get the maximum number of sales possible. This omni-channel experience pushed retailers to adopt an interactive set of information systems which exchange sales data in real time.

Big Data in Healthcare

Healthcare was not one of the first industries to embrace the digital age. However, it was fast enough to digitize vast amounts of information. Today, over 80 percent of hospitals are using electronic medical records. Many of them are utilizing Big Data analytics tools in order to reduce costs and improve patient experience. Doctors and insurance companies are also using big data analytics in order to improve their daily operations.

Vendor neutral archive is one of the tools available to doctors and other medical professionals that allows them to store and sort out all of the collected data. This medical imaging tool allows medical professionals to access documents and images in a standard format from any information system in a vendor-neutral manner. Medicare is one of the healthcare systems that is using this technology.

Big Data is currently used by the medical community in order to discover relationships and trends that have been hidden till now, such as medication efficacy rates and precursors of diseases, not to mention health risks associated with certain genes.

Big Data has changed the industry of healthcare by expanding the use of data from clinical trials to every area of medical profession. Hypothesis is no longer needed in order to justify the use of data analytics. Though big data collected from patients is not considered as important as data collected from clinical trials, it can be useful in establishing the value of new drugs.

Big Data in Finance

Big Data has transformed the world of finance in more than one way. Big data analytics tools have been adopted to make smarter investment choices. Big data has also helped increase the popularity of algorithmic trading. This type of trading takes advantage of advanced mathematical tools. Along with sophisticated mathematical models and historical data, big data has become the main building block of modern algorithmic trading.

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Written by:
Dennis Hung is an entrepreneur and product analyst specializing in mobile technology and IoT. He’s spent most of his career consulting for businesses in North America.
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