Business Analytics Explained
Analytics – making the best of it
If you're reading this, the chances are you are strongly involved in doing something difficult with large quantities of information. Let's assume that the data is qualified from a good source, cleansed, transformed and loaded into a usable and robust data warehouse. What next?
You have probably sat through many presentations and read many articles telling you how much information is out there, and how much of that information will find its way into your organisation in the next year, five years, ten years. Whether you measure it in gigabytes, terabytes, petabytes or exabytes doesn't really matter. What does matter is whether you can use it all, and whether you can spot the trends and patterns within it.
Identifying Relationships
Not just patterns, either. Where SAS technology can really score is in tracking down the seemingly impossible-to-identify relationships that are forerunners of critical movements in trends.
- If inoculation rates fall, which drugs and treatments might be needed in twelve months time?
- What happens to revenues when populations migrate from one region to another?
- How do changes to legislation affect demand for our products and services, and do they affect demand positively or negatively?
- Why might existing customers be inclined to make further purchases?
Where such relationships are identified, analytics becomes a powerful tool in the hands of statisticians, marketeers and information analysts in all walks of industry. Now those relationships can be used to analyse what went before, deduce what is most likely to happen in future, and most crucially use that information to inform your business decisions.
SAS characterise such analysis as "what happened?", "what will happen?" and "what’s the best that can happen?" It is that last question that especially separates SAS from other business intelligence software.
OLAP
One of the key methods used by information analysts to help identify patterns and spot trends is the On-Line Analytical Processing (“OLAP”) Cube. Relevant information is extracted into separate marts or “cubes” of data, which can then be analysed far more quickly than trying to interrogate the entire data warehouse. There is a skill involved in extracting the right information into the OLAP cube, and then creating the business rules by which that cube is analysed. The objective is to identify those parameters with statistical correlations that make the most impact on any number of possible outcomes, and then, by manipulating those key parameters, create the best possible outcome.
Business Advantage
Delivering such a powerful tool to your organisation requires planning and co-ordination – remember that we started by assuming that data quality and data structures were already in place. But the rewards are potentially enormous; imagine the business advantage you could gain if the future became that bit more visible.
Need advice with Business Analytics? Call 01993 848010 and ask for the Business Development Director.
