Thoughts from ODTUG Kaleidoscope 2008

Kaleidoscope 2008 is getting into full swing, and I've already found some nuggets of wisdom from the speakers. Ron Moore, one of the first Essbase certified consultants in the world and founder of Marketing Technologies Group (http://www.mtgny.com/), is a speaker at Kaleidoscope this year. In conversation with him about blending analytic and relational data, he said that you:

"Just can't get by on a hammer or a saw - you need both."

From the perspective of corporate data, that just rings true. Companies can't simply rely upon cube data from their analytic applications in order to make the best business decisions, and they can't rely solely upon relational data – they need both. And to create a central data store requires cooperation between the business owners (of analytic data) and IT owners (of the relational data stores).

Many companies experience a disconnect between the Finance and IT groups, as their goals can appear to be at odds. While Finance teams often implement the business systems, it is IT who inherits the issues of compliance, maintainability, and governance for those systems. But in order to successfully integrate corporate data to provide a holistic information view, the project requires the cooperation of both groups.

In order to harness the value of the content in the cube data, we need to synthesize it within relational data sources. Ultimately, a standard rows and columns relational database is the only common ground to which every application available to the information technology industry can have ubiquitous access. Trying to achieve the bridge in the absence of relational technology creates the potential for a myriad of misinterpretation and eventually the value of the cube data would get lost in translation.

Once the cube data is exported into a relational structure, the infrastructure and data are in place to provide information access to stakeholder groups across the business. A potential next project step, incorporating data from other sources such as ERP or CRM systems or operational data stores, creates a centralized, single version of the truth for all stakeholders to work from, and provides a comprehensive, holistic view of the business that includes both operational and management data.

The benefits of this level of integration to a company are myriad. But as Ron Moore so succinctly put it, it takes both the hammer and the saw to make this kind of effort successful. Finding the tools and technologies that can help bridge the inherent gap between groups is imperative to success.

As Kaleidoscope continues through the week, I'm sure that I'll hear more about opportunities to create mutually beneficial projects between Finance and IT groups and the tools to support them. With technical and thought leaders from across the country here in New Orleans, I'm sure I'll find a few more nuggets of wisdom to share this week.

Ready for Operational Business Intelligence? A Good Read…

Operational reporting isn't new; I remember slogging through reams of mainframe-generated reports in my very first job out of college, many years ago. So why is operational Business Intelligence (BI) garnering so much headline real estate these days?

Expanding beyond traditional, strategic business intelligence, operational BI provides an unprecedented level of business insight to support the management of daily operations. And as we look at ways to extend our existing investments in analytic applications, this seems a natural evolution. But introducing operational BI into your organization comes at a cost. The impact on your data warehouse environment can be enormously disruptive if not approached with the understanding that this is a broad-scale project that will have significant impact (and benefits to be realized) across the organization.

Claudia Imhoff, recognized thought leader and expert on business intelligence, has published a new white paper on The Ever-Evolving Data Warehouse: Dealing with Changes and Pressures for BI Today that discusses the impacts of operational BI on the data warehouse environment. Some of her key takeaways regarding the impacts to data warehouse include:

• Scalability
• Performance
• Continuous availability
• Ability to combine different sources of data

While not exactly summertime holiday light reading, her white paper focuses on the impacts to the data warehouse and provides great food for thought for those of you who are considering or beginning an operational BI project. The paper digs into issues beyond the `headline-hype' of operational BI; in fact, the considerations that she discusses are applicable beyond operations and are equally appropriate for any project aimed at extending the foundation laid with your existing BI systems.