Everywhere small to medium business decision makers turn, they see messages telling them that they'll do just about everything better if they use "Big Data" technology and analytics. They're told that they'll be able to save money, make more money and serve their customers better.
A recent example of this is a nice video that is a recording of a "kitchen table" coffee chat between an IBM executive and a number of IBM partners. They are speaking about how Big Data analytics has been put to use helping their SMB customers. It's worth a few moments to view this video. It is called “Evolving with Analytics” Coffee + Conversation and can be found here: http://www.youtube.com/watch?v=JfAhD2RBr_U&feature=youtu.be
While I thought the dicussion would be useful, it really didn't address the three fundimental questions that come to mind during the discussion. They are: 1) What is Big Data? 2) How do Big Data Analytics differ from the reporting my information systems already are providing? and 3) Why should I care about this at all?
What is Big Data?
What is Big Data is a question that I've addressed in a number of places. Here is a quick summary.
“Big Data” is a catch phrase that has been bubbling up from the high
performance computing niche of the IT market. Increasingly suppliers of
processing virtualization and storage virtualization software have begun
to flog “Big Data” in their presentations.
If one sits through the presentations from ten suppliers of technology, fifteen or so different definitions are likely to come forward. Each definition, of course, tends to support the need for that supplier’s products and services. Imagine that. IBM's video is no different in that it points to successes of both IBM and its partners. My key take away was that IBM and its partners are actually helping their customers put this appraoch to work.
In simplest terms, the phrase refers to the tools, processes and procedures allowing an organization to create, manipulate, and manage very large data sets and storage facilities. Does this mean terabytes, petabytes or even larger collections of data? The answer offered by these suppliers is “yes.” It is a way to sift through huge amounts of operational data to discover the answers to previously unasked questions.
How do Big Data Analytics differ from the reporting my information systems already are providing?
The key differences between Big Data Analystics and current operational systems are the following:
- Operational systems
- Operational systems were designed to collect specific, well-defined, structured pieces of data.
- These systems were designed to manipulate this structured data and turn it into specific types of information.
- The reports have been designed to answer specific, already known questions and are likely not to be able to cross reference data held in other operational system databases
- Often other questions that might provide equally useful answers may not be asked. The data may be changed to rapidly for reporting systems to keep up. The data is being held in non-structured files, such as in documents, spreadsheets, presentation decks, SMS messages and the like, it may be difficult to impossible to process using traditional systems
- Big Data Analytics
- Data, both structured and non-structured, from many operational workloads, system logs, and device reports can be drawn together and examined for useful relationships.
- Rapidly changing, very large quantities of data may be reviewed to ferret out useful tidbits.
- New questions may be asked and new learnings be developed
Why should I care about this at all?
SMB decision makers, like those of larger companies, are having to examine and re-examine their business to reduce costs, increase revenues or quickly react to new market opportunities. Often market "winners" are those who discovered a new opportunity and can exploit it before their competitors find out about it. Opportunities may come and go in a matter of a few weeks.
Those who are looking for these opportunities are far more likely to
find them than those who are not looking or are looking at the same old
things in the same old way
Big Data Analytics offers many opportunities. Learning about them and exploiting them requires the use of new tools and looking and new sources of data. While it is possible that the staff of a SMB company could do this on their own, why not take advantage of what others have already learned?
Rather than feeling like it has to go on this journey alone, it
would be wise for SMB IT decision makers to speak with trusted advisers
from partners, such as IBM, in order to develop reasonable plans for
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I've been compensated to contribute to this program, but the opinions expressed in this post are my own and don't necessarily represent IBM's positions, strategies or opinions.