Educating the Next Generation of Business Intelligence Professionals

Originally published June 14, 2011

Business intelligence jobs held constant in the declining economy, but expectations were high for skill sets, time to deliver and breadth of knowledge. More importantly, business intelligence professionals are being asked to know more about the business, too!

It seems that everywhere you turn you see industry articles about the continual adoption of analytics across many industries, but the one thing that is not being addressed is where the employees are going to come from to fill those analytical jobs. The business world is changing; and as data becomes a prime business asset, there is a growing need for the next generation workforce to have greater understanding of analytics and the practices that go along with it, i.e., business intelligence (BI) and data warehousing (DW). The current educational model for computer science or management information systems is to provide a broad background in all aspects of the many skills that make up IT as a profession, but there is a gap between traditional IT jobs and business intelligence, data warehousing and analytics.

The Gaps

Students entering today’s business intelligence or data warehousing workforce have gaps in their education because of the special set of skills needed in the field. Students have little to no exposure to business analytics; star schema design; visualization best practices; extract, transform, and load (ETL) concepts; or online analytical processing (OLAP) cube development. These skills are needed to develop, implement and maintain the data warehousing lifecycle and the eventual process of turning data into actionable intelligence. We need today’s students to be better prepared for the environments that they will face in the “real world.” Every industry now seems to do something with analytical data, whether it is an Internet-based company, a nearly 100-year old law firm, or a small manufacturing operation. If students today are not prepared to enter an analytically based workplace, they are going to find themselves at a severe disadvantage or, worse yet, unemployed.

We constantly read about the aging of the baby boomer generation. This holds true in the analytical world as well. Based on a recent survey1 conducted by The Data Warehouse Institute, 76% of the respondents were 36 years of age or older, with only 1% being 25 or younger. If this trend continues, there will be a huge gap in the data and knowledge management fields as those older workers move toward retirement. Institutions need to start now to mold the next generation of the analytical workforce.

Comparing Skill Sets and Curriculum Today

Degrees in computer science, computer information systems or similar disciplines give the student an extremely broad base for entering the workplace, and while this is good for the more mainstream disciplines, it does not serve those who are in need of specialized skills. If your interests are in network administration or web programming, you will more than likely be exposed to those skills; but if you want to develop OLAP solutions or develop ETL code or design dashboards, your educational resources may be limited. Some students may not even know these avenues are available in the job market because they have not gained exposure during their college and university years.

In reviewing some of the curriculum offered for these degrees, there is very little that can be identified as being “in the neighborhood” of data warehousing or business intelligence. With that said, they are still teaching assembly language and Visual Basic, which hasn’t been routinely used in business over the last decade or more. On the other side, degrees in business fare no better as they do not offer any classes in analytics, so business professionals have no way to use and analyze the data that is presented to them. The curriculum for these programs needs a thorough overall overhaul to bring these programs in line with today’s work environment and the demands of the global workplace. More classes for specialized study should be made available to today’s students.

Why Should Institutions Teach DW/BI Curriculum?

Why should colleges and universities offer specialized courses focused on data warehousing and business intelligence? The data doesn’t lie. As professions, data warehousing and business intelligence are seeing strong salary and job market growth and also projected growth potential in corporate data. Based on information provided from The Data Warehouse Institute in their 2011 Salary Survey,2 there is steady progression in the maturity of business intelligence implementations. In 2010, 18% of the implementations were in the “beginner” phase of the project where individuals were just getting started in business intelligence. Forty-nine percent were in the “intermediate” phase where they were adding value to what had been developed. What many educators and curriculum leaders do not understand is that business intelligence and data warehousing cross all industries. These industries run the gamut from finance (at 12%) to transportation logistics (at 3%). There were also 12% of the survey’s respondents who selected “Other” as their industry.  It can be safely said that any business or industry that collects data about their business has a need for business intelligence.

Additionally, business intelligence and data warehousing jobs pay very well. With a mere 3 to 5 years of experience, there is the potential to be making $90,000 a year on average, depending on the region where the job is located. Starting salaries for these jobs are also higher than most jobs, ranging from $40,000 to $50,000 a year. People in these jobs also report a higher than average pay increases.

These jobs are not going to diminish anytime soon, so there is significant job security within the industry. Projections for the amount of business data in existence by the year 2020 is approximately 35 zettabytes3 (1 zettabyte = 1 trillion gigabytes) or 44 times the amount of data that existed in 2009. Someone is going to need help managing and analyzing that data; and if we don’t start preparing the workforce now, we will be overwhelmed with data.

The “Dream Curriculum”

There are really three paths to an educational curriculum. These are examining analytics, business intelligence and data warehousing.

For the analytics path, there needs to be a focus on examining data and thinking critically about trends, anomalies and what the data “tell us.” An understanding of how to read and understand charts and graphs, the ability to do a “what-if” analysis, and the skills to be able to formulate a follow-up question based on the data are essential to compete in the world of analytics.

For the business intelligence track, there needs to be some of the analytical education and the addition of the methods in which to put these data sets and visualization together, the ability to understand the analytical questions being asked, and how to turn those questions around and provide the answers and insight thought data presentation.

On the technical side, the data warehousing track needs to focus on the fundamentals of data warehousing methodologies, databases, SQL, data modeling and the development of data cubes that will have the ability to answer the business questions.

The following mind map lays out, at a high level, the areas of study (perhaps multiple classes in some cases) for a hypothetical bachelor’s degree in business analytics, business intelligence and data warehousing. To truly map out a curriculum that would be effective, there would need to be a summit between the colleges – and/or university – and the area businesses as well as the leaders in the industry to ensure an effective course of study. These areas of study coupled with a partnership between local businesses to provide internship and co-op opportunities would better prepare today’s students and would aid in transforming them into tomorrow’s business intelligence professionals.

Somewhere in the curriculum, we need to infuse classes that teach:

  • Application of mathematics to measure success and failure

  • Ability to tolerate ambiguity

  • How to be curious and to explore that curiosity

  • Visualization and how to communicate mathematics in visuals

  • Attention to detail as well as attention to summary

  • Inductive as well as deductive logic

  • Conceptualizing a situation from multiple viewpoints

  • Analytical writing skills

  • Data concepts such as congruency, data domains and data outliers

  • Multiple desktop tool proficiencies

  • Information delivery via alternate methods such as iPads, Playbooks and smart phones


These concepts may not appear in a traditional undergraduate program.  The meaning of “comprehensive” in business intelligence education may look more like this:

Figure 1: Example of comprehensive business intelligence education

References

  1. TDWI Annual Salary Survey 2011
  2. TDWI Annual Salary Survey 2011
  3. TDWI.org – 11 Big-Data Analytics Predictions for 2011


SOURCE: Educating the Next Generation of Business Intelligence Professionals

  • Mark Bradbourne, CBIPMark Bradbourne, CBIP
    Mark Bradbourne has been working in the data warehousing and business intelligence arena since 1997. He has been afforded the opportunity to work on the complete life cycle but enjoys the "user-facing" roles most including requirements gathering, visualization, reporting and  user training. He has worked for many companies across different industries including financial, manufacturing, Internet and legal. Mark is a graduate of the University of Akron with a degree in computer programming as well as business and organizational communication. He received his Certified Business Intelligence Professional (CBIP) certification from TDWI in February of 2011 in Business Analytics and is active in the ASUG Influence Council program as well as in the local ASUG Chapter. Mark may be contacted at mark@markbradbourne.com or you can follow him on Twitter as @MarkBradbourne.
  • Christina Rouse, Ph.D.Christina Rouse, Ph.D.

    Christina is the Chief Architect at  Incisive Analytics, LLC. An improvement catalyst, Chris applies business intelligence strategy for performance improvement. Leveraging two decades of data experience on a broad range of technical platforms, she developed a technology-agnostic approach to business intelligence consulting. Clients rave about Chris' unique blend of business acumen, technical architect and trainer skills. She may be contacted at  Christina.Rouse@IncisiveAnalytics.com.

Recent articles by Mark Bradbourne, CBIP, Christina Rouse, Ph.D.



 

Comments

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Posted June 14, 2011 by

Mark and Christina,

I enjoyed reading your article. You made some good points about the skills needed by BI professionals of the future.

Your article sparked a thought. Many roles could fall under the umbrella of “BI professional.” We often see people taking roles like “data wrangler,” “power analyst,” “collaborative user,” and “netizen user.” (I described these roles in this blog post: http://qlik.to/l3WYtv.) A skill that is increasingly important people in data wrangler and power analyst roles is translation, or interpretation. In essence: communication. They need to understand core business principles and the specifics of their own business; help collaborative users and netizen users formulate the right KPIs; and create Business Discovery apps that enable collaborative users and netizen users to ask and answer business questions and pursue their own path to insight. Does this ring true to you?

Erica Driver, QlikTech

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