Big Data Common Sense
January 30, 2013 Leave a comment
Back to Basics
Velocity, volume, and variety seem to be the 3 V’s that everyone talks about when it comes to Big Data. What happened to the most important V, Value?
So when it comes to Big Data, my advice is don’t get knocked off guard by the Big Data buzzwords. Go back to business and technology basics, and you’ll be fine.
Start by “Getting your business case in order.” Once the value to the business is understood, juggling higher data velocity, volume and/or variety becomes an engineering problem. Certainly, a new class of engineering problem, requiring new technologies or skills, but it is a fully solvable engineering problem nonetheless.
Making the Move to Big Data
For IT, Big Data is as much an organizational change challenge, as a technology challenge. Practical first steps that seem to work well include:
- Experimenting with a smaller, “SWOT” team on a selected set of projects is a great way to introduce something new.
- Going for some quick and easy wins, rather than boiling the ocean with large-scale initiatives, is a proven technique for gaining momentum.
- Implementing a solution with revenue impact, such a next-best offer analytic to improve upsell performance or a predictive churn analytic that helps reduce customer defection, can ease business funding challenges and improve executive visibility / sponsorship.
Big Data Means More Silos
Cloud sources, analytic appliances, Big Data stores, and more have resulted in a landscape of data processing silos. The good news is that each of these silos optimizes their specialized function. The bad news is that many other critical business functions – maximizing revenue, synchronizing a supply chain, accelerating new product development, managing risk or meeting compliance requirements – require data from across these proliferating silos.
This is where data virtualization offerings such as Composite Software’s have proven valuable at large enterprise customers such as Comcast, Pfizer and the New York Stock Exchange. Data virtualization is an agile data integration approach that easily leverages existing silos, without generating even more silos as organizations might have done with a data warehouse in the past.
Agility, Flexibility and Cost Savings
By simplifying information access in this way, the business dramatically improves their information and therefore business agility.
For IT is means greater flexibility to use whatever technology is optimal for each silo, but then provide the business with a common, “virtualized” place to get whatever data is required, whenever needed.
And for everyone, it means lower costs and greater business success.