Each time you measure sales numbers, track inventory levels or collect demographic details about current and potential customers, you’re producing data — data that thousands of other businesses are also generating and storing. And while the resources required for a company to be able to store all of that data have become far more accessible, much of that data remains unstructured and unorganized.
In fact, organizations today are generating such large quantities of data that old attitudes toward and techniques for dealing with data have become obsolete. In order to effectively utilize accumulated information, businesses now require state-of-the-art software tools and expert analysts to catalog, prioritize and interpret data. But even with these resources, many companies simply have too much data to sift through to fully maximize the data points being collected.
That’s where advanced analytics software tools come in.
What Is Advanced Analytics Software?
When your systems produce important data sets about business performance, revenue, spending patterns and more, that information is typically archived without being utilized fully, if at all. Sure, some data points will be pulled into a BI program or performance management system, but often much of the data accumulates in a company’s storage infrastructure (whether virtual, physical or both).
Advanced analytics tools are built to help alleviate this point of weakness, employing algorithms to mine and structure gathered information into valuable insights relevant to business infrastructure, efficiency and planning. In other words, an advanced analytics solution will help sculpt data into intelligence that can simulate and predict a variety of business decisions.
The Core Elements
Accessibility
Data Mining
Data Processing
Simulation and Optimization
Forecasting
Advanced Analytics vs Business Intelligence Tools
If you’re wondering what happened to business intelligence software, you’re probably not alone. BI is still a product of great value to the corporate environment, and many would argue that advanced analytics is merely a newly developed sub-category within the BI bubble. Yet business intelligence products have encountered more than their share of limitations as innovative technologies are continually introduced within the software realm.
The application of advancements like cutting-edge algorithms and more precise (yet also more global) data extraction marks a key difference between BI and its younger counterpart. Whereas business intelligence software can be used to collect and sort data sources, advanced analytic tools take the data a few steps further, using historical data to predict future outcomes and even simulating business behaviors to determine the best and most profitable course of action.
Here’s a breakdown of some of the key disparities between how the two programs are used:
- Data correlation (BI) versus data modeling and simulation (Advanced Analytics)
- Trend and pattern identification (BI), as opposed to algorithmic analysis (Advanced Analytics)
- More general data management (BI) versus complex data assessment (Advanced Analytics)
- Oriented for general business optimization (BI), in contrast to forecasting for specific actions, projects and investments (Advanced Analytics)
The Future of Advanced Analytics
The rise of advanced analytics platforms suggests a larger shift in the scale of business analytics and how software is used to help a company better optimize its performance. On exactly what scale calculated forecasting methods can be adopted remains to be seen, but the advantages of algorithm-based analytics appear promising.
As Gartner’s latest magic quadrant for advanced analytics software reveals, there are a handful of early standouts in the industry who have already made great strides in reinterpreting data analysis. You can find out more about these leaders by checking out our exclusive Top 5 Advanced Analytics Vendors comparison report.
[Photo courtesy of Flickr user r2hox.]