- The more I read about BIG data the more it astonishes me how fast things are evolving around us and how critical data collection and assimilation is becoming in our day to day lives.
If we look around businesses Big and Small technology oriented or Non-technology oriented are investing heavily on market researches, surveys, end user opinions etc. to maximize their information base and use this as a key to their business transformation and success.
“Data Management is now a Critical differentiator that can determine Market winners and Has Been.”
Obviously, to manage such volumes, diverse and dynamic data you need technology. BIG Data refers to these technologies and initiatives.
The 3 key ingredients for BIG DATA analysis are Volume, Variety and Velocity. In other words How Much, How Fast and What kind….
It’s fascinating when you read about how organizations are churning and using data:
- Facebook ingests about 500 terabytes of new data daily, Boeing 737 generates roughly 240 terabytes of data in one flight across US
- Clickstreams, Ad impressions capture user behavior at millions of events per second
- Data collection does not comprise of just the traditional numbers, strings and dates. It’s spanning across 3D data, Audio, Video, Geospatial data. Google Earth is a classic example
We have so many examples of organizations from different sectors like Insurance, Commodities, Automotive even Government offices using this technology to further their businesses or assist in daily operations
The Next Question that comes to mind…..
Are the traditional database geared up to handle this kind of data ??
The answer is Traditional databases were designed more to handle smaller volumes and structured data with fewer updates.
We are talking of unstructured, huge volumes and frequent updates of data. This is where now the paradigm shift to BIG DATA Databases is happening.
BIG DATA landscape is essentially dominated by two classes of technology:
Operational – Systems that provide operational capabilities for real-time, interactive workloads where data is primarily captured and stored
Analytical – Systems that provide analytical capabilities for retrospective, complex analysis that may touch most or all of the data.
Finally, like in every aspect of life you have favoring and opposing opinions. BIG DATA is no different.
I will close with an interesting cartoon I came across on BIG DATA….