TDWI The Data Warehousing Institute

Strategies for Creating a High-Performance BI Team

A key element in the success of any business intelligence (BI) program lies in the team you create to deliver solutions and the clout it has within the organization to secure resources and get things done. Although there is no right or wrong way to organize a BI team, there are some key principles that are worth knowing. The following the seven guidelines can help you create a high-performance BI team that delivers outstanding value to your organization.

1. Recruit the best people. Jim Collins in his best-selling book “Good to Great” says great companies first get the right people “on the bus” (and the wrong people off it) and then figure out where to drive it. Collins says that the right people will help an organization figure out and execute a strategy, which is a much more effective approach than recruiting people based on their skills and experience to support a strategy which might become obsolete in short order.

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Three Tiers of Analytic Sandboxes: New Techniques to Empower Business Analysts

Analytic sandboxes are proving to be a key tactic in liberating business analysts to explore data while preventing the proliferation of spreadmarts and renegade data marts. Many BI teams already provide sandboxes of some sort, but few recognize that there are three tiers of sandboxes that can be deployed individually or in concert to meet the unique needs of every organization

Analytic sandboxes adhere to the maxim, “If you can’t beat them, join them.” They provide a “safe haven” for business analysts to explore enterprise data, combine it with local and external data, and then massage and package the resulting data sets without jeopardizing an organization’s proverbial “single version of truth” or adversely affecting performance for general DW users.

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Evolving Your BI Team from a Data Provider to a Solutions Provider

In her presentation on “BI Roadmaps” at TDWI’s BI Executive Summit last month, Jill Dyche explained that BI teams can either serve as “data providers” or “solutions providers.” Data providers focus on delivering data in the form of data warehouses, data marts, cubes, and semantic layers that can be used by BI developers in the business units to create reports and analytic applications. Solutions providers, on the other hand, go one step further, by working hand-in-hand with the divisions to develop BI solutions.

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SAS Kicks It Up A Notch

With “analytics” a hot buzzword and the newest competitive differentiator in Corporate America, SAS is sitting in the catbird’s seat. With $3.1 billion in sales last year, SAS is by far the leader in analytics software and is prepared to leverage its position to compete head on with the big boys.

It was a clear after spending a day with SAS executives in Steamboat Springs, Colorado that SAS is thinking as big as the towering Rocky Mountains that surrounded our resort hotel. Specifically, SAS is focused on competing with IBM. That’s partly because IBM just acquired its nearest analytics competitor, SPSS, and is now heavily marketing its “Smart Analytics System” initiative, which enables customers to purchase a single integrated analytical solution consisting of hardware, software, tools, consulting services, and support via a single SKU and have it delivered in two weeks. (See “IBM Rediscovers Itself” August, 2009.)

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Reflections from TDWI's BI Executive Summit

More than 150 BI Directors and BI Sponsors from small, medium, and large companies plus a dozen or so sponsors attended TDWI’s BI Executive Summit last week, a record turnout.

Here are a few of the things I learned:

- Veteran BI directors are worried about the pace of change at the departmental level. More specifically, they are worried about how to support the business’ desire for new tools and data stores without undermining the data warehousing architecture and single version of truth they have worked so hard to deliver.(See "Zen BI: The  Wisdom of Letting  Go.")

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Zen BI: The Wisdom of Letting Go

One of my takeaways from last week’s BI Executive Summit in Las Vegas is that veteran BI directors are worried about the pace of change at the departmental level. More specifically, they are worried about how to support the business’ desire for new tools and data stores without undermining the data warehousing architecture and single version of truth they have worked so hard to deliver.

At the same time, many have recognized that the corporate BI team they manage has become a bottleneck. They know that if they don’t deliver solutions faster and reduce their project backlog, departments will circumvent them and develop renegade BI solutions that undermine the architectural integrity of the data warehousing  environment.

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Launching an Analytics Practice: Ten Steps to Success

Everyone wants to move beyond reporting to deliver value-added insights through analytics. The problem is that few organizations know where to begin. Here is a ten-step guide for launching a vibrant analytics practice.

Launching the Practice

Step 1: Find an Analyst. You can’t do analytics without an analyst! Most companies have one or more analysts burrowed inside a department. Look for someone who is bright, curious, and understands key business processes inside and out. The analyst should like to work with numbers, have strong Excel, SQL, OLAP, and database skills, and ideally understand some statistics and data mining tools.

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Mashboards: New Tools for Self-Service BI

There is an emerging type of dashboard product that enables power users to craft ad hoc dashboards for themselves and peers by piecing together elements from existing reports and external Web pages. I’m calling these “Mashboards” because they “mash” together existing charts and tables within a dashboard framework. Other potential terms are “Report Portal,” “Metrics Portal,” and “Dashmart.”

I see Mashboards as the dashboard equivalent of the ad hoc report, which has spearheaded the self-service BI movement in recent years. Vendors began delivering ad hoc reporting tools to ease the report backlog that afflicts most BI deployments and dampens sales of BI tools. Ad hoc reports rely on a semantic layer that enables power users to drag and drop predefined business objects onto a WYSIWYG reporting canvas to create a simple report.

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Sleep Well at Night: Abstract Your Source Systems

It’s odd that our industry has established a best practice for creating a layer of abstraction between business users and the data warehouse (i.e., a semantic layer or business objects), but we have not done the same thing on the back end.

Today, when a database administrator adds, changes, or deletes fields in a source system, it breaks the feeds to the data warehouse. Usually, source systems owners don’t notify the data warehousing team of the changes, forcing us to scramble to track down the source of the errors, rerun ETL routines, and patch any residual problems before business users awake in the  morning and demand to see their error-free reports.

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IBM and Informatica Acquire MDM Capabilities

Special Note: This analysis was written by Philip Russom, Wayne's colleague in TDWI's research department who covers MDM and data integration.

I don’t know about you, but when I read two, similar announcements from competing software vendors, delivered at pretty much the same time, I can’t help but compare them. So that’s what I’m thinking about today (February 3, 2010), after hearing that IBM intends to acquire Initiate Systems. This bears strong resemblance to Informatica’s announcement a few days ago (on January 28, 2010) about their completion of the acquisition of Siperian.

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