Business intelligence systems are used to help business owners make data-educated decisions to help move their organizations in the correct direction. Depending on the size of the organization and its place in its growth, these systems can be made up of many moving pieces. These can be made up of data analysts, engineers, scientists, managers and much more.
When a business decides to apply data analytics to their organization, the center piece of these systems are often the BI software that is purchased. In the market today there are hundreds of options for BI software, with some of these options specializing in particular domains such as manufacturing, technology and energy.
Within these systems there are many parts to play, each different and vital. While the title of “Business Analyst” or “Data Analyst” may be the more familiar position for the layman, these two titles certainly do not encompass the entirety of the complex system. Understanding this principle is crucial, especially for a new or future analyst entering the world of business intelligence systems.
It’s significant to understand that the cogs within BI systems are separate and different but very much interconnected and contribute to the overall process. In a university setting, students that train to become data analysts are given small-scale excerpts of the different “cogs”. This can include learning how to write SQL queries, tidying data with specific software and even developing knowledge in statistical tests and models.
While this jack-of-all-trades approach is effective in giving prospective analysts a view of the big picture, it may also leave the wrong impression of what a day-to-day workflow looks like in a professional setting. Different roles mean different points of emphasis. Entering the job market without a complete mastery of databases, statistical programming or other necessary skills does not mean an analyst is unprepared or unqualified.
Leaving university as a finished product is an expectation that no reasonable employer should have of their newly graduated hires. Rather, a prospective analyst will be a work-in-progress with strengths and weaknesses that well-fit a specific role. Within this role or “cog” they may grow and have the opportunity to get small tastes of each part of the BI system.
Publishing a report
From my perspective as a recent university graduate entering the workforce, I’d like to share an insight I’ve gained from being a “cog” in the business intelligence machine. This has been developed through different internship experiences and past projects.
In university there are one-off assignments, quizzes and other tasks that often have specific deadlines. While there are certainly deadlines in the professional arena, creating dashboards and reports can be a fleshed out process that requires multiple iterations. A project can go through many hands and eyes before it is considered “completed”
As far as the “cog” that I’ve had to fill in the past, it primarily revolved around data munging, creating summaries, running occasional statistical tests and communicating the results. Sometimes these reports and dashboards would have long-term implications while othertimes they would be ad-hoc analyses.
As a business analyst from the bottom looking up, there typically has been no way for me to publish a report for my organization without appropriate approval and a business intelligence manager to help with the implementation. Perhaps this was a result of my role as an intern or data analyst but rarely have I been “left alone” to complete a project.
In any case, this wasn’t a hinderance but rather evidence of a business intelligence system in process. A single piece of the machine won’t get the job done. For projects both simple and complex, the many “cogs” in BI must work and communicate well with each other in order to be successful.
Play the role to its fullest
The world of data analytics and business intelligence is diverse. While having knowledge of all the different corners of analytics is significant, it’s unreasonable and impossible to master it all. As a result, there are different roles to fill as cogs to this machine.
From the bottom looking up, this may be disheartening and one may come to believe that their part is small and insignificant. Business intelligence systems are meant to help move organizations in the correct direction by using data to fuel their push. When the role is played to its fullest, whether the role is data analyst, statistician or data engineer, it will be obvious which “cogs” are essential and which ones aren’t.