Essential Skill Sets for Careers in Business Intelligence

Last Updated April 30, 2019

Big Data has tremendous potential to lead the way toward business transformation. The sheer volume and variety of data being produced in today’s environment presents a valuable opportunity for managers to measure and understand more about their businesses. That, in turn, can mean better business decisions and better performance. The implications of Big Data are creating a huge demand for resources to help businesses utilize this information – to not just aggregate it, but understand how to leverage it to make informed decisions and build strategies.

Business intelligence is crucial because it has several facets that can help provide holistic insights into the business. One such facet is information management, which involves monitoring data quality and includes the processes by which data is created, captured and stored. Information management, according to Pringle, is the largest segment of the business intelligence services market. Other growing facets of business intelligence include performance management, which involves an analysis of financial operations, and analytics, which blends multiple skills in technology and analytic techniques with industry-specific information.

The need for business intelligence professionals is clear. As this industry continues to grow, succeeding in business intelligence may take a combination of technical skills and capabilities, along with a broader frame of reference for the work and how it’s carried out and measured.

For the technical skill sets, it may be helpful to have experience in:

• Relational databases – The limits of working with the table schema of the database developer make understanding relational databases important.
• SQL – While less frequently used, this specialized language for updating, deleting, and requesting information from databases can facilitate the solving of more complex problems.
• Basic programming skills – Due to the underlying scripting language in reporting software, a basic foundation in programming is needed.
• Reporting software familiarity – Business intelligence (BI) professionals should have a general understanding of the underlying theory and application of key reporting software on the market.
• Analysis skills – In business intelligence, analytics is a subset involving statistics, prediction and optimization – a means to business knowledge discovery. It can involve anything from data mining to predictive modeling to prescriptive analytics.

In addition to technical skills, business intelligence professionals should build their soft skill sets, or skills that allow them to lead not only the business but also people using the insights uncovered:

• Macro-perspective – Adopting a different perspective or mindset – broader and more team-oriented with an eye to impact on the enterprise – is also critical to success in the business intelligence space.

• Communication skills – In a 2012 report on Business Intelligence, Gartner, the world’s leading information technology research and advisory company, said that 70% of projects in this realm are considered failures, mainly due to lack of communication. The organization’s business intelligence teams should place the strongest communicators at the forefront of every project and leaders should consider special training for their teams to ensure the basics are grasped.

Today’s business intelligence professionals should cultivate their technical and soft skills and establish a respect for real-time data and the importance of portability. To that end, businesses may demand reports and dashboards that deliver information via compelling interfaces and expect to receive the information quickly. To address this demand, business intelligence teams should adopt a mobile mindset. They may win the support of stakeholders and team members by making their most critical and visible applications compatible with smartphones and tablets.

The freshness of business intelligence and BI projects can make success a difficult metric to effectively measure. The primary metric is a basic understanding that BI outputs should have a positive effect on the business. Delivering this effect typically requires fast user adoption – the higher the better – so teams can focus on BI outputs from the start, rather than gaining internal support. Several recent studies have reported only a 25% adoption rate at the start of most business intelligence project deployments. When teams should be delving into business intelligence, they are instead pushing for user adoption which creates bottlenecks and can result in project slip-ups or failures, like lack of performance or inaccurate data.

Staying on top of emerging trends and understanding their implications in business is one critical aspect for professionals leading the way in business intelligence. A firm understanding how to harness the power of Big Data and the insights that can transform a business is quickly becoming a cornerstone of strategy. Professionals driving business intelligence adoption need to see mobile and next generation IT services like the ‘cloud’ as necessary tools, not options, and plan how to adjust accordingly. Businesses  that continue to transform with technology and data-analytics advancements may be ahead of the curve.