Combined power of Big Data and Social Analytics

Benefits of Big Data and Social Analytics sound too good for any top executive team to not jump on this bandwagon. But there still remain quite a few challenges, says TO THE NEW's Narinder Kumar

e4m by Narinder Kumar
Updated: Sep 10, 2014 8:02 AM
Combined power of Big Data and Social Analytics

If we have to pick five most-talked-about terms in the world of technology in past three years, both Big Data and Social Media would likely make it to the list.

Big Data, as the name states, can be broadly defined as a combination of data-sets often large and complex enough to be analysed on a single large computer, thus requiring distributed storage and computation. With more and more digitisation, we are generating huge amounts and various type of data at an alarming speed. This is popularly referred to as 3 Vs of Big Data: Volume, Variety and Velocity.

Social Media refers to the applications and platforms enabling users to create and share content in online space. Because of fast increasing Internet penetration and very low entry barrier, social media platforms are among the largest and fastest growing technology platforms in terms of user base, traffic and hence generation of amount of data. Facebook, Twitter, LinkedIn, WhatsApp, Pinterest and Wikipedia are just a few popular examples.
Looking closely, Social Media has played a significant role in the growth of all 3 Vs of Big Data. By the end of 2013, Facebook had 1.2+ billion monthly active users, we were having 50+ million tweets per day, English version of Wikipedia alone is having 4.5 million articles and adding 800 articles every day. 100 hours of video is uploaded to YouTube every minute. That’s not just a lot of data, but of different types, which is being generated at a very fast speed.

So what does all this mean for businesses? These are not people merely uploading their vacation photographs or chatting among friends, but also potential / existing customers expressing their thoughts on different products / customer service or deciding their next big purchases. While organisations are investing time and resources individually in both Big Data and Social Media Analytics, they are ignoring what they stand to gain by harnessing the combined power of these two:

? Create new and/or improve existing products and services based on real consumer desire than guts and assumptions
? Targeted advertising and marketing campaigns at fractional cost compared to traditional channels
? Understand and rapidly react to consumer sentiment to protect and improve brand and corporate image
? Build customer and brand loyalty through innovative usage of social media
? Learn greater insights about your customers to personalise and further improve their experiences

All these benefits sound too good for any top executive team to not jump on this bandwagon. But there still remain quite a few challenges:

? Paradigm shift required in way organisations make decisions. Big Data and Social Analytics force organisations to become more data driven not just in few pockets but across the board
? Evolving technology may not be 100% ready to serve immediate business needs precisely
? Difficulty in merging corporate data with social media data for actionable insights

Current state- We are seeing some organisations taking limited initiatives in these areas, but there are still several gaping holes. Firstly, these actions are limited to technology pioneers while majority are still sitting on the fence. Secondly, works are mostly ad hoc and being done in different silos. Thirdly, there is a lack of coherent planning for combining Big Data and Social Media initiatives.

What’s in future for businesses? Both Big Data and Social Media will only grow bigger from here. They are relevant for both large conglomerates as well as SMEs. In fact they should be seen as an opportunity rather than a threat or mere distraction. We are also witnessing a deluge of products and technologies in this space. Hadoop ecosystem, NoSQL datastores (designed with scalability and unstructured data in mind), Predictive & real-time analytics are just a few examples. All this has made it possible and cost-effective than ever before to apply innovation and leapfrog the competition. We need to adapt fast, else we risk losing out in this fast evolving landscape.

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