Self-service BI tools are designed to empower users to access, analyze, and visualize data without relying on IT or data experts. However, using these tools effectively requires some skills and best practices. In this article, you will learn how to use self-service BI tools more effectively by following six tips.
Before you start using a self-service BI tool, you need to understand where your data comes from, how it is structured, and what it means. You should also verify the quality, accuracy, and relevance of your data sources. This will help you avoid errors, inconsistencies, and confusion when you use the tool to create reports, dashboards, or insights.
Before building your dashboard or report, do data profiling to ensure quality and accuracy. First, check your data quality. Verify that columns have the right format (numeric, date, text, etc.). Check for blank or missing values, and fix any errors from data load. Next, check your numeric data. Calculate and compare totals with the source system. For example, for financial data, ask: What is my revenue? What are the costs? Are they correct and consistent? Then, profile your data. Explore and analyze it to understand its features and patterns. Look at trends over time, and slice and dice data across dimensions to gain insights into your data structure and business drivers.
Present your data sets. Describe your data, provide definition and context for using it, provide examples and, very important, mention a goto person to have additional information on this data set. Everything to enjoy using your data :)
The next step is to define your business questions clearly and precisely. What are you trying to achieve, measure, or improve with your data analysis? What are the key metrics, indicators, or outcomes that you care about? How will you use the results to make decisions or take actions? By defining your business questions, you will have a clear direction and purpose for using the self-service BI tool.
Writing down a Specification document, describing business questions, criteria, definitions(details descriptions for measures and attributes used), and the contact information to reach out will help you succeed in a self-service model, also, many tools, for ex:Tableau has something called "As Data" powered by NLP where business user can ask and question that can be translated into report and get answers that would defiantly compliment your self-service tool
Maximizing the value of data and analytics investments | Qlik Partner Ambassador 2023
Before you build a dashboard or report you need to understand that the quality of those reports / apps is determined by the quality of questions that would be asked to the data rather than by the beautifulness of charts. Here is the list of the self-check questions: 1. Can I give an example of a successful, correct decision based on this report? How did I define it? 2. What obstacles/problems have occurred (or which good outcomes have not) because of not having the report/dashboard? How am I planning to detect them? 3. Why should I care about those particular key metrics? 4. Who is the target audience of the report? Who will decide based on the signals from the report/app?
There are many self-service BI tools available in the market, each with different features, capabilities, and limitations. You should choose the tool that best suits your needs, preferences, and budget. You should also familiarize yourself with the features and functions of the tool, such as data connectors, data models, data transformations, data visualizations, filters, calculations, and interactivity. You should use the features that help you answer your business questions and communicate your findings effectively.
Maximizing the value of data and analytics investments | Qlik Partner Ambassador 2023
The best tool is the tool that helps you to get the correct information at the right time without any doubts about data quality. I like the K.I.S.S. (KEEP IT SIMPLE, STUPID) principle from the programming world, which states that designs and/or systems should be as simple as possible. Wherever possible, complexity should be avoided in a system—as simplicity guarantees the most significant levels of user acceptance and interaction. For instance, the same regarding the data visualizations - don't use complicated visualizations that must be explained before using them or visualizations that distract the end-user from the decision-making process (example: 3D pie-charts).
One of the main benefits of self-service BI tools is that they allow you to create and customize data visualizations that can reveal patterns, trends, and insights from your data. However, not all data visualizations are created equal. You should follow some data visualization best practices, such as choosing the right chart type, using appropriate colors and labels, avoiding clutter and distortion, and telling a story with your data.
Maximizing the value of data and analytics investments | Qlik Partner Ambassador 2023
You can start designing a dashboard and working with data with a clear understanding of your task. This determines the choice of charts and the final composition of the dashboard. A key rule that works not only on any type of dashboard, but on any visual experience product in general, is the points of attraction for human attention. We instinctively pay the most attention to the information in the upper left corner - simply because we are used to doing so: we start reading from left to right and top to bottom, which is a very basic pattern of our behavior. The top left corner is the area of greatest focus and primary attention. The further down and to the right the information on the dashboard, the less attention is paid to it.
Another benefit of self-service BI tools is that they enable you to collaborate and share your insights with others. You can use the tool to create and publish reports, dashboards, or stories that can be accessed by your team members, managers, or stakeholders. You can also use the tool to comment, annotate, or chat with your colleagues about your data analysis. By collaborating and sharing your insights, you can improve your data literacy, get feedback, and generate more value from your data.
Finally, you should keep learning and improving your skills and knowledge of using self-service BI tools. You can use online resources, such as tutorials, blogs, videos, or courses, to learn new tips and tricks, explore new features, or solve common problems. You can also join online communities, such as forums, groups, or networks, to exchange ideas, experiences, or questions with other self-service BI users. By keeping learning and improving, you can use self-service BI tools more effectively and confidently.
Self-service means different things for different users. An everyday business user wants to get answers and for them, self-service might be access to dashboards with the ability to filter and drill down. On the other hand, analysts want the flexibility of discovering, connecting to any data sources, cleaning and preparing the data for analysis, doing their analysis, and presenting the insights discovered in a self-serve manner. So, it really depends on the persona. However, the common theme is that they should be able to get the job done themselves without reaching out to someone who is more technically skilled or someone who holds the key to the kingdom.