Job profile: Become a business intelligence analyst
Some of my favorite people in the world are business intelligence (BI) analysts. I have always held the believe, like most do, that knowledge is power, so the ability to harness that power is something I hold in high regard.
So what does a business Intelligence analyst, or BIA, actually do? Well, as businesses have become more dynamic and innovative in how work gets done, the roles of project managers and business intelligence analysts have become more prominent in corporations and organizations throughout the world.
The bigger picture
A BIA is a catalyst for change, but she (or he) does more than simply inspire others to do things differently. A BIA uses data-driven analysis to determine strategically where improvements and adjustments should be made, thereby bringing about changes that organizational leaders and stakeholders want to see.
According to the BABOK® Guide produced by the International Institute of Business Analysis (IIBA) “business analysis involves understanding how organizations function to accomplish their purposes and defining the capabilities an organization requires to provide products and services to external stakeholders.”
Even though this definition is for a pure business analyst, the same general concepts apply to the work done by business intelligence analysts. In short, they translate business needs into actionable items for technology professionals. If management want to understand what code the business needs, they should ask a developer. Explaining how that code solves a business issue or meets a business need? That’s for a BIA.
Business intelligence analysts seek first to understand the organization and its data as it is, then imagine how it could be in the future. They shape their understanding of the desired future state by listening to leaders, stakeholders, subject matter experts, and project team members. Business intelligence analysts then devise ways to get their company from where it is to where it wants (or needs) to be.
They provide a fresh perspective on many problems that a company has. They come into a situation without the preconceived notions held by people who routinely deal with projects and processes. Business analysts ask the obvious questions without looking stupid. They question fundamental assumptions everyone else takes for granted. For people who like to solve problems with actionable data, business intelligence analysis is a great field.
Business intelligence analysts primarily work on project teams. They usually work in cooperation with their project managers and database engineers on more than one project.
They spend a lot of time on documentation, writing procedures and workflows to solve problems. Brainstorming requirements for, and enumerating the details of, a business solution are always needing to be done by the BIA, which requires a good understanding of how technological solutions are implemented.
The business intelligence analyst is critical to a data project’s success because he (or she) has an understanding of both the business side and technical side of things. The project manager often has this knowledge, but not to the degree the business intelligence analyst does.
A BIA can translate technical jargon into something project team members can understand, and they can translate organization-specific lingo into terms computer programmers can incorporate into their mental framework.
Keeping pace with changes
When it comes to business intelligence analysis, the one place I can see some rapid growth is machine learning. But what is machine learning, and how can the BIA translate it to help grow the business?
Machine learning is a form of artificial intelligence in which a machine can perform tasks without being explicitly programmed to do so — it learns on its own. For example, machine learning can take a simple form wherein a machine “learns” by parsing through large data sets and recognizing patterns: this image is either a bird, or not a bird.
This is probably the easiest example and one that is cited quite regularly. You will need to train the machine or computer program, in essence, to “recognize birds.” Training a machine learning algorithm typically requires a lot of data that’s “cleaned,” or structured and organized deliberately. Birds have to be a really clean picture of a bird.
The data may be labeled to give the machine a sense for what it’s looking at, i.e. “bird” or “not a bird.” Such machine learning is referred to as “supervised” and is the kind of machine learning that businesses are most likely to encounter in this day and age. Business intelligence analysts are likely to put these sets together for the machine.
By analyzing data, the machine builds an algorithm based on the patterns it recognizes. If we stick with birds, it analyzes tons of pictures of birds and things that are not birds, and the machine learns how to classify the images. The algorithm is refined over time until it achieves a high degree of accuracy.
Ultimately, the business intelligence analyst no longer must curate the sets of data. The algorithm can then be applied to entirely different data sets. For example, data sets that aren’t labeled “bird” or “not a bird.” Machine learning has incredible implications for any business that wants to leverage data.
The bird/not a bird example is an incredibly simple illustration of a classification algorithm, but it provides a helpful baseline of understanding what machine learning is and how it can help.
A BIA can help because with good numbers in hand, it can be easy to miss the bigger picture. And frankly, your team likely doesn’t have the bandwidth to dive deep, especially when things look good on the surface.
Machine learning algorithms combined with a BIA can help identify underlying currents. Sales may be increasing, but your market share is stagnant, and the brand’s category is declining nationally. Meaning, sales are only a part of what they could be, and failure to adapt to a changing marketplace could result in decline over time.
To navigate the waters of a BIA job, a qualified individual must have a deep understanding of data and business requirements workflow that will allow them to navigate any project that comes up. An advanced academic degree is helpful, along a high level of understanding when it comes to data manipulation and BI reporting tools.
Experience with SQL is a must. Databases of all types, depending on your companies’ database choice, you are going to want to know Mongo or SQL. Certifications in SQL, PowerBI or any data specialization degree would be of the most use for this position and title.
Above all, as I have always stated, a strong degree of soft skills is also essential. You will never go wrong with knowing how to address the 16 personality types. You can learn any technology after you master the soft skills. If you choose to go into this field, I wish you the best of luck, and may your journey be prosperous.