trends in big data agence tesla singapore bangalore analysis insights case studies

Among the topics of Bangalore’s top tech event, Nasscom PC trends in Big Data had a full half a day of panels, pitches and keynotes to better grasp what it’s all about.

In 2008, the number of devices connected to the internet was more than the world’s population. The forecast for the next decades is without appeal: we’re living in a world where machine to machine (M2M) is bringing a huge technological and cultural shift.

 

Understanding trends in Big Data: going from causality to probability

The main paradigm set up by the use of massive, big data is certainly the cognitive shift it operates on our own understanding of the world.

In a universe where information was so far scarce, we had as human beings to devise theories, hypothesis, and in most cases to analyse samples of data or population to verify them.

It was a decent way to proceed, although the hunt for causality was highly biased, and always on small clusters of data.

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Today, even if the data is too huge in its volumes, too messy in its different formats, there’s an incredible amount of value stemming from the correlations we can detect.

All experts agree on point, as stressed in Big Data, an easy to read vulgate by Viktor Mayer-Schönberger and Kenneth Cukier, messy data is always better than handpicked and precise data.

The cultural, psychological shift we need to operate is also quite impressive. Some, like Chris Anderson have been trumpeting the “death of theory”, and popular movies such as Minority Report show well how correlation, and probability, is a form of power we are unprepared to.

Trends in Big Data for business: 5 Insights to make it actionable

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Back in Bangalore, the afternoon dedicated to trends  in Big Data was introduced by Atul Batra from  Manthan, a world leader in Advanced Analytics,  Business Intelligence, Optimization and Analytics-  driven Execution solutions for Retailers.

In his speech, Atul offers 5 insights to better use Big  Data for businesses, in particular in the retail world:

Insight #1: Focus on one vertical only and get intelligence out of that, see what are the pain points, the change in processes, what is still done manually, what are the gaps, then you have a good product proposition. For instance, there are about 50 different parameters you can check on as a retailer. Try to focus on one move before going wild on all the other data.

Insight #2: Close the loop between analysis and decision. Execute on the data, don’t let the loop open, and do numerous tests (still keeping insight #1 in mind: it’s easier to execute on one small field first). Say you have a big analytics platform: how are you going to link it up with marketing execution? And then engage on a personal tone with customers?

Insight #3: Predict and Prescript Business Outcomes. How to mark on 10% of a certain category of products? How does it impact the other categories? Again, you need to test and see how changes in a few variables will impact your global business. If you change prices every week, how do you inform mobile sales forces?

Insight #4: Drive real-time personalisation

How do you link up different segments of customers with different set of promotions, in real time?

Insight #5: Leverage platforms

Don’t reinvent the wheel, a lot of solutions exist today.

Case studies in trends in Big Data

The different speakers then chose to shed the light on a few case studies to understand how Big Data impacts their businesses.

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Vijay Raghavendra, VP Engineering at Walmart Labs, showed how Big Data is being applied to the biggest retailer in the world in a startup mode.

In his case study, Vijay showed how the title of each product on Walmart.com was tailored in a unique way for each separate set of keywords typed in in Google.

Take a basic tote bag with a humorous message. Depending on what query lead to the product, Walmart can guess part of the intent (buying a funny bag, buying a simple bag, buying a bag in organic cotton), and offer a product name based on this intent.

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In another case, one of India’s top TV shows, Satyamev Jayate, used Big Data to change, on a very short notice, the upcoming episodes.

The show itself is more like a documentary, where sensitive societal are discussed, generating a huge conversation online and on social media. After just 13 episodes, writes GigaOm, the stats are huge:

“400 million viewers on Indian television and across the world on YouTube.

More than 1.2 billion people have connected with Satyamev Jayate across its website, Facebook, Twitter, YouTube and mobile devices.

More than 8 million people have contributed a total of more than 14 million responses to the show’s content via Facebook, web comments, text-message votes and a telephone hotline. More than 100,000 new people respond each week.”

Thanks to an Indian consultancy (Persistent Systems), the show was able to organise a follow-up on radio with the best messages, as well as influence the government. In one of the episodes, talking about female feticide, the Big Data team showed how 99.8% of the conversation agreed to set up a fast track court to prosecute doctors performing such operations. The Rajasthan high court approved the idea just after the show.

These stories and case studies must convince you that a huge cultural shift is happening right now, with a transformative impact for all businesses.

Find out more about big data and its trends here:

Big data in Africa: How an insurance company provides an optimized cover for farmers in Kenya

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