“Data will grow to several petabytes and zeta bytes in the next few years;” “Corporations will be overwhelmed by the sheer volume of data;” “By 2015 databases will grow so large that companies will have to rent space on the moon to store them.” These are just a few common quotes we hear from renowned industry analysts, experts and CIOs surrounding the topic of Big Data.
But for many observers, there’s still a lot of gray area surrounding when to apply Big Data solutions. How is Big Data different from traditional analysis tools? How does it impact an organization? Just because there are several terabytes of data, does that make it Big Data? Does it really matter?
We can make a generic bold statement here: Data is everywhere! When you pause to think, you’ll see it’s true. The cars we drive, stores we shop at, the phone we use, the websites we read, the social media we so closely embrace, the TV programs we watch, the election polls that we follow – everything generates data and it is all stored somewhere.
When it comes to Big Data, people commonly mention the 4 Vs, but this only scratches the surface. Traditionally, any large organization that implements ERP services has all these Vs associated with their everyday line of business. Admittedly, this is primarily “structured” data, and it can be handled by a traditional RDBMS or an MPP database. But in light of the other Vs, it technically has volume because everything is recorded in an ERP system; the incorrect and the correct entries alike form the millions and billions of rows. It undoubtedly has value; otherwise corporations would not bother to collect it. It clearly is volatile because data does not come at regular intervals. It also has variety; data comes in from multiple sources, such as CRM systems, HR systems and modules that are implemented within the organization.
Even if you add unstructured data, can you really derive strategic value for your business? What is this unstructured data comprised of? What kind of metrics can we extract from this unstructured data?
More often than not, Big Data buzz induces a cool factor akin to what was once associated with owning an iPhone/iPad or, back in the day, having a free Facebook account. Sometimes a personal agenda is associated with Big Data implementations. Several managers and CIOs have vested interests in showing off a ‘cutting edge’ Big Data implementation. We recommend organizations take a breather to make sure that the data problem they have qualifies as a Big Data problem.
…Stay tuned for a model CIOs can use to evaluate whether Big Data is the solution to their challenge…
Ajay Narayan is a presales solution architect for Bodhtree, a leader in data analytics and product engineering. Bodhtree partners with SAP and Informatica to assist companies in leveraging enterprise data to gain a competitive edge in the market. Bodhtree also offers the MIDAS product suite, which migrates, cleanses and integrates data between SalesForce, SAP and legacy platforms.
CMMI is a process improvement approach that enables organizations to establish effective processes that ultimately improve their performance.
As part of this appraisal, a total of seventeen critical Engineering and Organization level processes have been assessed across various parameters such as on-time delivery, customer satisfaction ratings, total quality management metrics, etc. Maturity Level 3 indicates that our organization has defined standards, procedures, policies, checklists, tools and methods to conduct business effectively, and has also established processes that are well characterized and understood.
Achieving CMMi Level 3 emphasizes our commitment towards quality and pushes our quality standards to new levels. From my perspective, this enables us to explicitly link our Management and Delivery practices to our customer’s business objectives and exceed their expectations at all times. It not only strengthens our ability to deliver world class solutions, but also allows us to better manage risk and enhance organizational processes.
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