Take a look at these statistics:
- There will be 5,200 gigabytes of data for every human on the planet by 2020 – The Economist
- We are generating more than 2.5 billion gigabytes of data every day – Forbes
- Wal-mart has accumulated 30 petabytes (30,000,000 gigabytes) of shopping data (and growing) – PC Magazine
Is this much data necessary? Maybe but it is not the raw data that will generate the most value for enterprises. It is how you interpret the data and the ensuing conclusions that are the most valuable pieces of information.
A recent article in Forbes magazine highlighted the need for analytics to tackle the data that is out there. Called “How Big Data Analytics Creates Order Out Of Chaos”, the article cited three examples where when analytics was applied to collected data, companies were able to drive real value:
- A major manufacturer analyzed purchasing and cost-related data in all of its vendors’ databases, enabling it to consolidate vendors, reduce the cost of goods sold and achieve a 942% return on investment (ROI).
- A resort integrated shift scheduling processes (by analyzing) data from a national weather service that allowed managers to avoid unnecessary shift assignments and increase staff utilization for an ROI of 1,822%.
- When a metropolitan police department combined its criminal records database with a national crime database, it was able to use national trends, local crime-related data and predictive analytics to allocate its law enforcement assets more effectively and reduce crime rates. The end result was an 863% ROI.
The pattern in all three cases was that the companies integrated data from various sources, analyzed the data, identified patterns and derived meaningful, actionable changes that altered the way the companies worked.
So while “Big Data” is today’s hot topic, “Big Data Analytics” is what we should really be talking about when it comes to achieving measurable business results.