Wrapping Your Head Around Big Data
There’s an example I like to use when trying to illustrate the concept of Big Data: Everybody’s got a cell phone. And every 30 seconds, each of those cell phones sends out a message (a “ping”) to the network, saying “I’m here at this spot, still within network range.” Yes, when someone calls you, your phone rings – simple enough. But that’s just one bit of data. When you think about every one of the billions of cell phones (and tablets, and other networked devices) in the world sending out pings over and over again, all day long, day in and day out, you get an idea of the staggering amount of location-based machine data produced. And that’s just one example of the massive volume of information gathered every day.
Big data is a big bucket: Start with video, audio, text, machine, structured, and unstructured data. Combine massive volume with tremendous variety, and you get complexity. The tricky part: Within this complexity is a significant amount of value. The challenge is how best to corral and mine the information to create new opportunities.
But no one collects Big Data for bragging rights. Companies go to the trouble only if the information is (or will be) valuable or, in certain industries, if required by law. Just as important, the value of Big Data is time bound – to extract its value, employees must be able to access and analyze it in real time.
Does This Sound Familiar?
Customers come to us, each with a unique business model but all with an overwhelming amount of available data. They speak of a growing number of impatient end users demanding real-time information. Then there are the employees, who want data access from home, on the road, from the cloud – at any time on any device. And they don’t just want to see the data; they want to analyze it and then transact or act on it, right then and there. They want to approve POs from the sidelines of their kids’ soccer games or finalize and send a revised price list to a customer from Gate 16. How can you possibly deliver on these expectations?
Mapping SAP Solutions to Your Big Data Dilemma
The good news? SAP has aligned five core market areas (database, analytics, cloud, mobile, and applications) to create the perfect solution for Big Data challenges, so you can get the most Big Data value out to the most employees, in real time.
Of those core areas, the one I want to focus on here is analytics. Even as companies accrue many disparate types of data in staggering amounts, technology has made it easy to say “analyze it” – and get the results you need.
Remember, though, that behind the scenes that ease masks a tremendous amount of complexity – not just numbers, but sentiment, opinions, and trends. You can get answers to the most complex questions, immediately – wherever you are. When you think about the amount of technological expertise that goes into offering real-time analytics on every platform, you can see why SAP leads the market. We deliver across all five dimensions of Big Data:
- High speed
- Real time
And this is why we generate momentum and capture so much attention – because we provide real-time analytics on all types of data, on any platform. Today, SAP is revolutionizing business, and we’re going to see even more big changes in the next few years.
When it comes to Big Data, it’s time to do more than pick up your smartphone. It’s time to analyze, decide, and act – to execute business in real time, courtesy of SAP.