2014 Recap & Looking Ahead to 2015 – Tungsten Big Data and PetaData Labs


Every year – just around these days, we wonder at the year gone by and ponder over the year to come. Trust you had a great Diwali, Christmas and Hanukkah with family and friends. I would like to wish you and the family a very Happy and Prosperous 2015!

I hope 2015 will be even more wonderful, fully lived, full of purpose, and a year that you can look back at, with meaning, pride and a smile of joy. Hope and anticipation for success, contentment and wealth etc. fill our cups. Let me wish and hope for you that your cup brimmeth over.

We, at Tungsten, have now progressed from being an acorn with the dream to become an oak tree. We have now grown into a small plant in 2014. Starting in London from a solo single-office unit in July 2009 during the height of the global financial recession; to growing to a presence in 5 countries has been a significant leap towards our long term goals. It’s been a wild ride for us and as we have grown in size, so has our stature and the portfolio of products and services we have on offer.

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Tungsten’s Solution Accelerators (TSA) driving adaptive shopping campaigns

“Data! Data! Data!” he cried impatiently. “I can’t make bricks without clay!”

– Sherlock Holmes,The Adventure in the Copper Beaches

In Q3 2014, the R&D team at Tungsten developed a Tungsten Solution Accelerator (TSA) for offering a simpler and more flexible way for retailers to manage their Product Listing Ads (PLAs). Marketers have already seen success with their shopping campaigns using this TSA.

As Mr. Subhash Trivedi, CEO & Founder at Jobpedia says: “It’s been incredibly helpful having Tungsten develop such a customized solution for maintaining and managing our shopping campaigns. We were able to transition to hopping campaigns more quickly and determine the best prices and practices that work for our brands; giving us the competitive edge, long before the majority of retailers hit the market.”

Since then, we have been focused on building solutions, offering bespoke customization, plug and play features, scale and speed time to market, to capture maximum retail opportunities. This has been possible due to Tungsten’s capabilities in the Advanced Analytics space.
Predictive Analytics Solutions developed by Tungsten are the outcome of powerful matching algorithms that enable predictive models to utilize enterprise data in combination with very powerful technology stack. These predictive analytics solutions allow businesses to act on a single piece of information, without having to worry about data science equations and complex associations of data.

Check www.tungstenbigdata.com/analytics.php for more details.
Given below, are the details of the what, the why, and how customers use our TSA.

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Setting Big Data Analytics Infrastructureis all about the right tools to achieve right goals

Optimal big data infrastructure setup can be done by proper due diligence , asking right set of questions, and developing a suite of analytics reports that carry back business insights on both historical and real time levels.

An approach to determining what to ask and what to report on from big data is to start fresh. You can hire or retain temporary expertise in statistical analysis, heuristics, and big data analytics know-how for the business vertical you are in. But if you opt for an entirely “start new” approach, you are running the risk of not thinking broadly enough about your entire business reporting assets and the value they deliver to the enterprise-whether or not they involve big data.

Organizations have been defining what their IT investments in big data and big data equipment are going to be. In most of the cases, they are making longer term decisions to consolidate any big data processing now being carried out in individual company departments into a central data center where IT can take charge of scheduling big data jobs and ensuring that clusters of big data servers are being optimized to best advantage.

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Getting Ready for Big Data Analytics for Enterprise-Wide Appliances

Big Data is fully loaded with challenges: Lack of robust, emerging and yet-to-be- proven technologies, difficulty in finding right people and partners, and blurred and chaotic expectations around what Big Data Analytics can actually accomplish. In addition to all these, one of the major hindrances with Big Data is readying your Enterprise Applications to actually supply the data needed for analysis. Before heading on full force for a Big Data Analytics initiative or going big bang on new hardware and software purchases, consider the readiness of your Enterprise Applications.

A stitch in time saves nine

Common root causes of failures of Big Data efforts is not getting a handle on the location, structure, and quality of your existing data. At its core, Big Data is an analytical process designed to produce actionable information. Just as knowing the process of building airplanes will never result in a comfortable flight without knowing the process of flying airplanes, Big Data will never result in anything actionable without appropriate data and know-how of using that data.

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