In this technological era, human beings are dependent on the machines for their day to day activities. Most of us are using E-commerce applications to buy/sell products or services. Social Media applications are much popular now-a-days for every age group. Statistics show that 500+ terabytes of new data like photos, comments; video get ingested into the databases of social media sites like- Facebook every day.
So Big data is a term which is used to describe the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important; it’s what organizations do with the data- matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
The important task for the organizations is how to get value from Big Data; so that there is a need to add contextual information and place analytical capability.
Big Data needs to be “humanized”-that is taken from the world of bits and bytes and converted into information for the persons who require this information to analyze. So Big Data needs to be brought down to earth where people can use it to help drive decisions and unlock its value.
· Making something inaccessible easy to use;
· Making the difficult easy,
· Making the complex problem simple,
· Making the abstract concrete.
The biggest goal of the humanization of big data is to focus on the critical factor which is most important to business and industry. That factor is the customer or the potential customer of the business. The process of bringing context to information to tell the stories of who and what is generating that information. Humanizing Big Data can give us a way to get concrete plans of action or to take the meaning that becomes actionable from the data that we have been given.
Humanizing Big Data is dependent upon two critical elements:
1. Making Big Data easy to access for the business analysts to drive strategic decision making across the organization.
2. Helping Big Data tell its story.
Design Principles for Humanizing Big Data
• Collection & integration of data from anywhere & everywhere: current records, from social media or from the data warehouse.
• Pattern Matching: Seek Patterns from the collected data to predict the future outcomes.
• Make insight available at the point of decision: Insights are best when widely available. With powerful analytical tools that were formerly centralized, one can make effective and informed decisions.
The Big Data that we are being given can help us to arrive at new answers and new ways of making life better for people. It may be one of the biggest business disruptors, but only if we interpret it using a human touch.
The goal of the humanized Big Data approach is to get these capabilities into the hands of analysts in business units, allowing them to create analytic reusable workflows.