Big data analytics

We are living in the century of information technology. There are a lot of electronic devices around us that generate lots of data. For example, you can surf the Internet, visit a couple of news portals, order new Nike Air Max shoes from a web store, write a couple of messages to your friends, and chat on Facebook. Every action produces data. And we can multiply the actions by the amount of people who have access to the Internet, or just use a mobile phone, and we get really big data. Of course, you have a question: how big is big data? It probably starts from terabytes or even petabytes now. The volume is not the only issue; we are also struggling with the variety of data. As a result, it is not enough to analyze just the data structure. We should explore unstructured data, such as machine data generated by various machines.

World-famous enterprises try to collect this extremely big data in order to monetize it and find business insights. Big data offers us new opportunities; for example, we can enrich customer data through social networks, using the APIs of Facebook or Twitter. We can build customer profiles and try to predict customer wishes in order to sell our product or improve the customer experience. It is easy to say, but difficult to do. However, organizations try to overcome these challenges and use big data stores, such as Hadoop.