Realize business value from big data with Infosys data analytics solutions.

« What actually is Big Data? - The different definitions | Main | Big Data Enabled Enterprise »

Big Data: Custom Analytics Helps Gain Competitive Insight

Posted by Nikhilesh Murthy (View Profile | View All Posts) | February 19, 2013 9:36 AM

In my last blog, we briefly touched upon how critical it is for enterprises to identify the right data sources for their big data strategy. The next step is to break down the data to a greater level of granularity in order to glean relevant insights.

Custom analytics is the coming together of breadth of knowledge about how social data mining works and deep knowledge of the industries that the enterprises are focused on.

Consider for example, a scenario for the health care industry. Flu is a frequent health problem, and it spreads like wild fire. Pharmacists and hospitals would do well to stock up on the required medicines, and more importantly, the vaccines to prevent virulent attacks. How can data help here? 
Health care providers are probably gathering data from multiple web sites where people post symptoms and ask questions about various health problems. Around the time flu peaks, people probably start posting similar symptoms.

A smart combination of data gathering coupled with the right algorithms to capture these symptoms, match patterns, and provide reports that warn of a potential flu outbreak, will help pharmacists pre-order flu vaccines. It will also help hospitals gear up to handle the deluge of flu patients, and give them the required care.

Along a similar vein, the next step for enterprises, after identifying the right data sources, is to work with experts to help build custom analytics solutions for their data. How an enterprise wants to interpret its data is driven by the business context of the enterprise, and what is most relevant to their customer base.

Custom algorithms help enterprises establish the impact of who did what and when and take course-corrective action promptly.

Predictive analytics gains more power with more real-time data. With access to sources such as company web sites and logged in customer profiles, it becomes simpler to provide real-time recommendations to customers based on a trail of their previous actions.

This smart and real-time analytics lends itself to a custom analytics hub where enterprises can build use cases on the fly, process them in instantly, and create a transaction-based marketplace that helps customers make informed choices, and helps businesses make inroads into unchartered waters.

Post a comment

(If you haven't left a comment here before, you may need to be approved by the site owner before your comment will appear. Until then, it won't appear on the entry. Thanks for waiting.)

Please key in the two words you see in the box to validate your identity as an authentic user and reduce spam.