Thanks to Business Intelligence (BI), company data can be transformed into valuable insights. This general definition highlights BI's central role in data analysis. However, to use BI successfully for decision-making, numerous steps and interdisciplinary collaboration are required:

1. Collection: Data must be collected from various sources.

2. Storage: Data is centrally consolidated or provided via a systematic query of data sources.

3. Processing: Through cleansing, structuring, and enrichment, the consistency and accuracy of the data are ensured.

4. Analysis: Statistical methods are applied to discover deeper insights and patterns in the data.

5. Visualization: Complex analyses must be transformed into understandable visualizations that decision-makers can easily interpret.

To implement these steps, the collaboration of data engineers, data scientists, and data analysts is necessary. Depending on the scenario, one of these roles may take on more responsibility. In addition, an extensive tool stack is required to support the process steps. BI therefore encompasses a broad field of responsibilities that requires interdisciplinary collaboration and is not universally applicable.

Self-Service BI: Independent Data Analysis for Businesses

To make BI more accessible, so-called Self-Service Business Intelligence (SSBI) tools have been on the market for many years. These are now crucial for companies that want to analyze and use their data efficiently. The choice of the right SSBI tool depends heavily on a company's specific requirements and existing technologies. Three of the leading SSBI tools, which are often compared with one another, are Power BI, Tableau, and Qlik.

The 3 Best-Known Self-Service BI Tools

• Power BI from Microsoft is known for its seamless integration with other Microsoft products and offers an intuitive user interface that is easy for beginners to use. Thus, Power BI is especially well suited for companies that already use Microsoft products and are looking for a cost-effective solution.

• Tableau also has a clear focus on ease of use and is ideal for companies that need sophisticated visualizations and are willing to accept higher costs for them.

• Qlik's data modeling platform, known as Qlik Sense, offers associative data modeling that enables users to easily recognize and analyze relationships in their data.

The choice of the right SSBI tool depends heavily on a company's specific requirements and often on its existing technologies. In the following, we will take a deeper look at Power BI and discuss its potential, as well as questions about architecture and data management.

Our Top Tool Power BI: Efficient Analyses Without Technical Prior Knowledge

With a strong focus on Self-Service BI, end users can use Microsoft's Power BI solution to independently perform data analyses and create reports without in-depth technical knowledge. This leads to a significant increase in efficiency in companies. Power Query in Power BI is a powerful tool for importing, transforming, and modeling data from various data sources. This is especially useful for users already familiar with Microsoft Excel. The creation, publication, and sharing of reports with stakeholders can also be handled via the Power BI Service. Furthermore, the Power BI Service offers continuous data refresh and integration with intelligent ETL pipelines to keep the data in reports up to date without manual intervention.

For report creation, the Power BI tool offers a wide selection of built-in and custom visualizations available through the Power BI Marketplace. Commonly used calculations such as "Running Total", "Cumulative Sum", "Previous/Next Value Comparison", "Percentage Changes", "YTD", etc. can be easily represented using different user-friendly options from visual calculations.

Advanced Analyses with DAX in Power BI

If the basic functions of Power BI are not sufficient for your analysis and reporting needs, using Data Analysis Expressions (DAX) offers an excellent way to perform complex calculations and create detailed data analyses that meet a company's specific requirements. DAX is a powerful formula language specifically designed for working with data models in Power BI, Power Pivot, and Analysis Services.

DAX significantly expands Power BI's capabilities and offers the flexibility to create calculated columns, measures, custom filters, and contexts. This enables companies to gain even deeper insights and derive important findings from their data in order to improve performance across the entire organization.

Self-Service BI at CarByte

We have already successfully integrated Power BI as a reporting tool for our customers, who benefit from connectivity to various data sources such as Jira and Microsoft Dynamics. For this, we were able to deliver a custom-developed database connector, which enables consolidation into a shared data model. This allows a wide variety of questions to be answered with great flexibility.