Discover best practices for building effective Business Intelligence (BI) reports and dashboards to deliver meaningful insights.
Business Intelligence reporting has become increasingly crucial as we have become so deeply ingrained in technology. BI is crucial to understanding the health and operations of a business, and you might be using a BI visualization tool such as Power BI or Tableau. When building these reports/dashboards, here are a few guidelines to consider to ensure you are bringing the most value with your work.
Do – plan what the data story is.
What story are you trying to tell? When someone first looks at the report, what are the main takeaways, and are they easy to identify? Know the audience you are building the report for, what details and KPIs they would be interested in, that can better help decision making. For example, a C-suite executive will have different priorities than an accountant or a staff manager.
Know the end user and tell them the story that means the most to them.
Don’t – overcrowd the report with visuals.
Information overload can be very overwhelming. Pick and choose visuals that give the most valuable information, in a simple, easy to understand way. The reports should be user-friendly and easily navigable. Just because a visual is cool and new doesn’t necessarily mean it makes the most sense for that context. For example, while a tree map is different and uses fun colors, it can be hard to pin down two buckets that appear to be similar sizes but may have different values. Instead, using a bar chart is simpler and easy to understand.
Do – have a standard layout and theme.
Design the report with the user experience in mind. Don’t use contrasting colors that are hard to read; don’t use tiny fonts that may not translate correctly. If your company has a standard logo and color scheme, use them! This makes all reports look professional and easily identifiable as the company’s product.
A corporate client of mine is actively acquiring lots of subsidiary companies. To standardize the reporting across all subsidiaries, we set up a report template that standardizes the color palette, fonts formats, and visualization properties. This provided an easy set-up when developing a new report.
Don’t – put the ETL logic in the report.
A reporting/data visualization tool is NOT an ETL tool. Transformation and cleaning of the data should be as minimal as possible in the report. When reports directly connect to the backend like a live database or API, this has negative effects on the performance of the report and can slow down the source system, too. If possible, tap into a specifically curated Data Warehouse or Data Mart with views that are built specifically for the purposes of that report.
Once I was called in to help a manufacturing client who built a Power BI report that pulled from 3 different APIs directly into the report with layers and layers of data cleansing, curation, and joins and filters. This caused the report to have over an hour of refresh time, often the API calls timing out. Additionally, the report could not report on historical data, only current state. We helped them build a Data Mart that housed all the data in a database and used Azure Data Factory to pull from the APIs. The report refresh time decreased to seconds, APIs were no longer timing out, and the report could present historical data to better guide key business decisions.
Do – implement proper security standards.
There are different levels of security for every report. An individual contributor may not need visibility into all costs and expenses of the company, and an executive may not need to know every single transaction that happens. Implementing security groups and/or row-level security are good practices to ensure users have access to only the data they need.
A logistics client of ours has several customers that have access to the client reports. Each customer should not be able to view another customer’s data, which includes costs, orders, addresses, and other customer-specific data. We implemented RLS to allow a single report to be used for all customers, which reduces redundancy, while keeping each customer’s data secure.
Don’t – confuse BI for AI
Business Intelligence is NOT Artificial intelligence. Business intelligence provides information on the status of the business using historical data. Artificial intelligence analyzes past data but can suggest future trends. Both can be used to make business decisions; however, they should be used in different operational areas that best fit the needs of the business.
If you or your team is interested in more guidance to tips and tricks to generate the most value to your company via business intelligence reporting, contact the Keller Schroeder Data Strategy Group to learn more!
