Twitter is making big changes in the way big data is managed — and that’s not unusual. Twitter has been looking for solutions in that field for about a decade now.
Last Friday night, it took another step to build its Big Data business, signing a deal that will allow it to move all data analysis in-house.
The impact on other social networks is less clear-cut, however.
Back in 2001, Gartner analyst Doug Laney defined Big Data as “high-volume, –velocity and –variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”
In simple terms, Big Data helps organizations manage, organise and connect massive amounts of structured and unstructured data through a technology that processes data calculation, usually in a reasonable amount of time.
Through Big Data analysis, companies essentially build the know-how to operate efficiently all the way through the decision-making process. As of today, though, it’s unclear whether the economics and the benefits associated to Big Data are sustainable or not.
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Twitter, just like others, may — or may not — need to devote more resources internally to better understand and interpret the data.
My quick takeaway obviously goes down to the 3V Concept — Volume, Velocity & Variety.
- Due to constant storage improvement and decreasing costs, the storage of a large data Volume is not a major issue anymore. However, a secure, cost & time-efficient technology is key. As new products are rolled out, it’s vital clients understand the technology and properly assess the economics associated to it.
- Due to the Velocity of data changes and new inputs that could alter the data, clients must accordingly react via correlation models, for example.
- Different data formats (Variety) and unstructured data needs to be managed and controlled, in order not to lose any complementary data which could impact the later data analysis.
- Data quality control is a must at any step of the process.
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