An article in Intelligent Enterprise last year outlined the Nine BI Megatrends for 2009 that the author expected to reshape business intelligence and information management in the year(s) ahead. Since spend analysis is a major component of business intelligence in supply chain, one has to wonder what impact these megatrends will have. But first, let’s address the mega-trends presented in the article.
- Open Source
Low TCO, mature development stacks such as LAMP (Linux, Apache, MySQL and PHP, Perl, or Python) [or MAMP if you prefer the Mac which, being built on Unix, is fully compatible thanks to Xcode], and new open source offerings from players such as Pentaho are making open-source platforms and foundations attractive, and providing pressure on commercial vendors to bring down the TCO.
- BI is becoming less isolated
Many users are now employing reporting, access, and analysis tools that come with functional applications, forcing suites to break down silos to offer value.
- Users are demanding a richer experience
The days of simple, canned reporting are finally slipping into the past. BI portals are starting to become richer, more flexible, and more powerful. They’re using Rich Internet Application (RIA) technology to improve the user experience and incorporating mash-ups to allow users to better visualize the data.
- BI is starting to focus on relationships
BI used to focus on reports that did not provide any flexibility when it came to investigating data relationships, but new tools are giving users the ability to define their own relationships, cubes, and reports and dive into the data in new and innovative ways and find relationships that, classically, would take weeks of specialist data mining or statistical analysis to uncover.
- Business Modeling meets MDM
Master Data Management and emerging semantic models, which could serve business modeling in the same way that data models, schema, and metadata served extract, transform, and load (ETL) tools, are enabling some vendors to create tools that improve business modeling and its data modeling relationship using graphical interfaces that allow analysts to create their own data models without having to learn specialized languages or methodologies.
- MapReduce meets Large Scale Data Analysis
Although the most famous implementation belongs to Google, it’s also available in the open source Apache Hadoop framework, and allows organizations to build parallel, virtualized architectures based on server farms using commodity hardware which can analyze more data simultaneously than ever before, allowing for the discovery of new relationships that can prove very insightful to BPM.
- Column-oriented databases are attacking performance woes
Some of the leading column-oriented database technologies are employing advanced compression technology and large memory algorithms that is changing the game for BI and data warehouse architectures, allowing complex queries to be answered in realistic amounts of time.
- Event Processing is opening up new analytical possibilities
Emergent applications in healthcare, telecommunications, intelligence, IT management, gaming, and web analytics are capturing events and correlating them with analytics from BI tools to give organizations actionable insight.
- Too Big to Fail
As more and more queries are run against multi-billion row tables in data warehouses managing hundreds of terabytes of data (and growing daily), we’ll see more and more BI implemented to improve BI.
So what does this mean for spend analysis? With the exceptions of MapReduce and Column-oriented databases, not much. The reality is that It’s the Analysis, Stupid and anything that doesn’t simplify analysis while increasing the analytical power available to the user won’t stay on the radar very long. That’s why I’m pleased to inform you that Eric Strovink’s new series on Spend Analysis starts within a week. As I’m sure it will be as informative and forward looking as his last two (linked in Spend Rappin’), I’m certainly looking forward to it!