By Abhishek Yadav via Iris.xyz

Did you know that we generate around 2.5GBs of data daily? What is even more surprising is the fact that just the last couple of years are responsible for 90% of this data. As the world gets more interconnected due to the growing number people in possession of smart, electronic devices, this figure is only likely to soar higher in the years to come.

If you’re surprised as to how you generate so much data, let’s take a quick recap of what seems like a redundant daily routine. A good morning text on WhatsApp wakes you up, you put on some music on your favorite online music streaming platform, and get ready for work. Then, using your preferred provider, you book a cab. On your way, you browse through your inbox to see if you’ve left any emails unattended. You log on to Netflix and catch the last few minutes of that episode you left incomplete the previous night. You get back from work and realize it’s a Friday – the end of a tiring week. What do you do next? Browse through the internet for the latest movies and their showtimes nearest to your place. Then, you go ahead to book your seats and get an e-ticket in your mail.

All of these are chunks of data you have been generating for organizations round the clock. These organizations come back with the same data to provide you better and personalized treatment. If you’ve used Apple’s Siri or Google Maps, you know what we’re talking about. Both of these (and many other) applications get better with time and start coming up with much more sensible responses. Enter the era of Big Data powered Machine Learning.

Big and small organizations alike are opening up to the importance of leveraging this Big Data and are therefore investing in much more sophisticated tools, technologies, and algorithms to help them gather much more insightful analysis. Right from managing and optimizing the supply chain to retaining customers by enhancing customer experience, these organizations are turning to Data for all their analytics needs.

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