While the phrase “Safe to Bet On” is an oxymoron of sorts, it is that time of the year where we first look at the past, derive some insights and look forward to what the future has in store for us. I have no doubts that 2009 will be doubly interesting for BI practitioners as compared to 2008.
Having said that, I decided to do a bit of introspection to figure out what skills (can also be read as competencies) should I be looking at to stay relevant in the Business Intelligence world far into the future, say at 2020. Hopefully that resonates with some of you.
Having said that, I decided to do a bit of introspection to figure out what skills (can also be read as competencies) should I be looking at to stay relevant in the Business Intelligence world far into the future, say at 2020. Hopefully that resonates with some of you.
Let me first try and get down to defining the skills required for Business Intelligence and Analytics. The trick here is to stay “high-level” as any BI person will acknowledge the fact that one we get down to look at the trees (rather than the forest), the sheer number of skills required for enterprise level BI can get daunting
Taking inspiration from the fact that any business can be condensed into 2 basic functions, viz. Making & Selling, I propose that there are 3 key skills that make for successful BI
Skill 1 – Business Process Understanding: If you are a core industry expert and can still talk about multi-dimensional expressions, that’s great! But most BI practitioners have their formative years rooted on the technology side and have implemented solutions across industries. The ability to understand the value-chain of any industry, map out business processes, identify optimization areas, translating IT benefits to business benefits are the key sub-skills in this area.
Skill 2 – Architecting BI Solutions: This skill is all about answering the question of “What is the blue-print” for building the Business Intelligence Landscape in the organization. Traditionally, we have built data warehouses & data marts either top-down or bottom-up, integrated data from multiple sources into physical repositories, modeled them dimensionally, provided ad-hoc query capability and we are done! – NOT ANYMORE. With ever increasing data volumes, real-time requirements imposed by Operational BI, increased sophistication for end-user analytics, the clamor for leveraging unstructured data on one hand and the advent of On-Demand Analytics, Data Mashups, Data Warehouse appliances, etc., there is no single best way to build a BI infrastructure. So the answer to “What is the blue-print?” is “It depends”. It depends on many factors (some of which are known today and many which aren’t) and the person / organization who appreciates these factors and finds the best fit to a particular situation is bound to succeed.
Skill 3 – BI Tools Expertise: Once a blue-print is defined and optimization areas identified, we need the tools that can turn those ideas into reality. BI practitioners have many tools at their disposal straddling the entire spectrum with excel spreadsheets at one end to high-end data mining tools at the other extreme. If you bring in the ETL & data modeling tools, the number of industry-strength tools gets into the 50s and beyond. With convergence of web technologies, XML, etc. into mainstream BI, it probably makes sense to simplify and say “Anything you imagine can be done with appropriate BI tools”. “Appropriate” is the key word here and it takes good amount of experience (and some luck) to get it right.
In essence, my prescription for BI practitioners to stay relevant in 2020 is to be aware of developments on these 3 major areas, develop specific techniques / sub-skills for each one of them and more importantly respect & collaborate with the BI practitioner in the next cubicle (which translates to anywhere across the globe in this flat world) for he/she would bring in complementary strengths.
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