Big Data and Analytics trends of 2015

The best way to begin speaking about how interesting the past year was for Big Data is to say that – there will be more.


By more we mean that there will be more data, thus, there will be more data scientists, data analysts, more cloud analytics, more mobile analytics and data discovery. So, it is evident that Big Data will only get Bigger this New Year on 2016 with more data to visualize.

But if you are new in the world of Big Data Hadoop courses and are only beginning to acquaint yourself with Big Data, here are a few special trends of 2015 that you must keep a close eye on, this year.

You can make magic:

The technologies we use today are nothing short of sheer magic that, we could only imagine in our wildest dreams even a few years ago. But in the field of Big Data Hadoop and other data analytics tools, nothing such amazing has been noticed yet. We only know of tools and features that get the job done with some difficulty, but nothing that gives us data magic on our very fingertips. Thus, the world of data science still requires shepherds who would oversee and micromanage each and every step of data analysis. We still need people to manage aspects like – where to find data, how it should be stored, how it should be stored and most important how to analyze it and what conclusions to draw from the analysis.

Experts suggest that all this would soon change with advanced technologies being incorporated into the world of analysis to further automate the process. Things like machine learning with other advanced analytics tools are being applied to data science to further upgrade the process.

Insiders now want advanced tools that help them take care of the trivialities fast and get to analysis sooner with facilities like – simply pointing them at the data and allowing the algorithms to figure out things like how to join the data, propose complementary data, and cleanse it and to optimize it to determine it should be stored. Thus, 2016 will see more developments in this aspect of advanced automation.

Make way for multi-polar analytics:

Nowadays the layer cake approach of model analytics is slowly becoming obsolete and a practice that was thought of as the best – with external data feeding data marts and warehousing data with Bi features, as the final touch is fast being replaced with a multilayered or multi-polar approach. So, this New Year we will gain a better idea of how we can get better results from realistic yet complex data analysis centres.

Data privacy laws:

Currently there is a huge room for development in the world of data science contrary to the rate of development in the technologies. Already there have been reports of serious abuses with important data and we expect that 2k16 will see some strict actions in encryption practices in data.

In conclusion, 2016 will be a wonderful year for data analytics with increased adaptability.

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