Periodic check-ups will help you avoid letting business intelligence and data warehousing problems spin out of control.
You need to establish a "care and feeding" program for the DW/BI sponsors. Business sponsors are highly experienced and respected businesspeople, however, they may not be highly experienced in the organizational culture change often required for an analytic initiative. They may need some coaching on their new roles and responsibilities. Take a look at our column, "Habits of Highly Effective Sponsors" (Sept. 1, 2003) for more details.
Never take your sponsors for granted. It's certainly not safe to rest on your laurels. You need to constantly communicate, feeding constructive, realistic, and solution-oriented feedback to the sponsors, while listening to stay abreast of sponsors' hot buttons. Communication is also critical to continually build bridges with other business leaders in the organization. Lastly, you should actively convey what the DW/BI world has done for them lately. You can't afford to wait until someone's scrutinizing expenditures to inform them of your successes. As uncomfortable as it may seem, you need to market the DW/BI environment. Enthusiastic business users typically deliver the most effective commercials.
Accessing good data is one of the two pillars of the data warehouse. (The other is addressing the right business problems). The most serious and common data disorders are poor quality data, incomplete data, and late data.
Symptoms. One of the key indicators of a data disorder is the degree of data reconciliation happening across the organization because the data's inconsistent or not trusted. Data disorders are often blurred with business acceptance shortfalls when the real underlying issue is the data is irrelevant or overly complex.
Treatment plans. The initial treatment for data disorders requires drafting an enterprise data warehouse bus matrix. This technique is thoroughly discussed in the Sept. 17th column referenced earlier. The matrix establishes a blueprint for enterprise integration by identifying the core business processes and common, conformed dimensions. After the matrix is developed, it should be communicated and "sold" up, down, and across the organization to establish enterprise buy-in. If you already have a slew of disconnected analytic data repositories, you can embellish the bus matrix by cataloging the "as-is" environment prior to developing action plans for your longer-term data strategy.
While the bus matrix identifies the links between core subject areas in the data warehouse, it also highlights "opportunities" for extract-transform-load (ETL) processing. Like the overall technical architecture, the back room ETL architecture is often created implicitly rather than explicitly, evolving as data profiling, quality, and integration needs grow. You may need to rethink the staging and ETL architecture to ensure consistency and throughput at acceptable costs.
You should preface the DW/BI project with a comprehensive data profiling task to confirm that the data is what it's advertised to be. During the production phase, you must continuously monitor the data for quality glitches and omissions. Finally, you should carefully examine whether you need to go to a streaming real-time architecture to deliver the data to decision makers within their "sweet spot" time window for affecting the business.
Data disorders often result when data is irrelevant, noncomprehensible, or otherwise difficult to use. Review your existing data schemas for potential improvements. We identified guidelines for reviewing presentation dimensional models in "Fistful of Flaws" (Oct. 10, 2003).
Finally, if you've invested a lot of time and resources to develop an atomic, normalized data warehouse but the business users complain about ease-of-use issues, you can leverage that existing investment by creating complementary dimensional models to address ease of use and query performance, while also boosting your chances of business acceptance.
Business Acceptance Disorder
Here's another critical disorder affecting data warehouse mortality rates. If the business community doesn't accept the DW/BI environment to support decision-making processes, then you've failed. Sorry to be so blunt, but it's a harsh reality. The business must be engaged if you're to stand any chance of DW/BI acceptance. Unfortunately, business engagement is often outside our comfort zones; we may be unsure about techniques for ensuring their engagement, plus there are typically no incentives in place for mastering this domain.
Symptoms. There are some strong indications of business acceptance disorder. Are the business users simply not using the data warehouse like you think they should? Do the number of BI tool licenses greatly exceed the number of active users? Do the number of trained users greatly exceed the number of active users? Are the prime targeted beneficiaries of the DW/BI environment turning their attention to a different analytic platform, independent of the DW? Do the business users make requests like "just give me a report with these three numbers on it" because they're loading the report into Excel where they're building their own personal data warehouse? Does the business community perceive a legacy of disappointment when it comes to IT's ability to address their requirements? Did the DW/BI project team focus on data and technology, presuming they understand the business's requirements better than the business does?
Treatment plans. Your mission is to engage, or reengage, the business. Talking to users about their requirements is an obvious place to start. The DW/BI environment is supposed to support and turbo-charge their decision-making. Given this mission, distributing surveys or reviewing entity/relationship diagrams are ineffective tools for gathering business requirements. Put yourself in their shoes to understand how they currently make decisions and how they hope to make decisions in the future. Obviously, you need to have the right attitude, listen intently, and strive to capture their domain expertise.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.
Top IT Trends to Watch in Financial ServicesIT pros at banks, investment houses, insurance companies, and other financial services organizations are focused on a range of issues, from peer-to-peer lending to cybersecurity to performance, agility, and compliance. It all matters.
Join us for a roundup of the top stories on InformationWeek.com for the week of September 18, 2016. We'll be talking with the InformationWeek.com editors and correspondents who brought you the top stories of the week to get the "story behind the story."