Much is said about the definition of Big Data, but for the sake of this blog let me reiterate:
Big Data = ∑ (Volume + Velocity + Variety + Veracity + Complexity)
This means that you don’t have to have all of the 4V + 1C characteristics in order to call it Big Data. Any combination of 4V + 1C results in Big Data. For example, you may have as little as one gigabyte of data, while the complexity and veracity of the data is high—this still qualifies as Big Data.
The interesting part of Big …
In my last two blogs, we discussed two of the three key activities to drive value through analytics—gaining control of your data and delivering the right information to the right people. Now it’s time to explore the third activity—enabling real-time analysis.
Business issues are on-going. Companies must continuously monitor business performance against established targets to identify areas for appropriate action and further analysis. In addition, business users are bombarded on a daily basis with questions that require quick investigation. And many of these questions require in-depth, ad-hoc analysis that goes beyond the scope of a standard report or dashboard.
Over the next several days, I’ll be writing a series of posts aimed at helping you better leverage analytics to create value for your enterprise.
Create Value from Big Data
There’s no doubt that companies today face an information explosion and a variety of devices to consume that information. But does this data profusion represent an invaluable resource to your business, or is it simply information overload?
Effective business insights can help you spot trends early and separate your company from the competition. But in order to realize the full value of information, companies must be able to:
Mobile phones allow us to always stay connected and deal with just about everything on the fly — we text friends to find them and meet up, for example, and use mobile phone apps on the way out the door to check traffic and transit schedules, make restaurant reservations, and buy movie tickets. However, many interactions still aren’t as “real-time” or as “smart” as most consumers want them to be.
Real-Time Room for Improvement in Old School Service
Recently, I was downtown on a weekend trying to find an available parking spot. Various mobile apps are available to show me …
What if you knew exactly who your customers were, what products they wanted, and when they were most likely to purchase them? It would have a huge impact on your marketing and sales strategy and execution!
We now have an unbelievable amount of data on every customer. Each of these data sets opens up a new window on a customer and reveals insights before, during, and after the purchase cycle. But most companies lack the right data, unified platform, or mathematical expertise to accurately predict customer behavior from all this data.
Fundamental new tools and techniques have recently emerged that …
Originally published August 15, 2012, on SAP Business Trends.
My response to people who talk about real-time information as if it’s the newest innovation on the planet is always the same: where have you been since 1998? That’s the year I discovered the joys of how real-time data can solve tough business challenges. I remember it well, the day I met the clients I’ve come to view as among the most challenging in my entire career so far. As communications manager at a high-technology public relations firm, I managed four or five teams, totaling about twenty people …
Everyone, it seems, is talking about big data (we’re even doing so on The Decision Factor). Why not, there’s a lot of untapped business value in big data. However, a lot of the hype focuses on how to access that data. Again, understandable—it’s a massive beast. But many companies seem to be stuck in analysis paralysis, focusing on an academic discussion of technical approaches for accessing big data rather than concentrating on where they can derive business value from big data today.
So, I thought I’d focus this blog on three simple business opportunities you can use to …
There is a saying in India: Never let your feet run faster than your shoes, which my grandfather was fond of cautioning me with whenever my youthful plans got too ambitious to execute.
I’m reminded of that saying lately as I think about the demand for data acceleration.
Organizations must deal with ever-increasing volumes of transactions and information – often thousands of transactions a second, 24 hours a day.
Any time you have such a high volume, there is an inherent risk, especially in a more strictly regulated, post-Sarbanes-Oxley world. How can you have absolute confidence …