Thanks to Business Intelligence (BI), corporate data can be converted into valuable insights. This general definition underscores the central role of BI in the field of data analysis. However, to successfully use BI 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 through systematic queries of data sources.

3. Processing: Through cleaning, structuring, and enriching, the consistency and accuracy of the data is ensured.

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

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

To implement these steps, collaboration among Data Engineers, Data Scientists, and Data Analysts is necessary. Depending on the scenario, one of these roles may take on more responsibility. In addition, a comprehensive tool landscape is required to support the process steps. Thus, BI encompasses a wide range of tasks that require interdisciplinary collaboration and is not universally applicable.

Self-Service BI: Independent Data Analysis for Companies

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

The 3 Most Known Self-Service BI Tools

• Power BI from Microsoft is known for its seamless integration with other Microsoft products and offers a user-friendly interface that is also easy for beginners to use. Thus, Power BI is particularly 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 incur higher costs for it.

• The data modeling platform from Qlik, known as Qlik Sense, offers an associative data modeling that allows users to easily recognize and analyze relationships in their data.

The choice of the right SSBI tool strongly depends on the specific requirements and often the existing technologies of a company. In the following, we will dive deeper into the Power BI tool and address its potential as well as questions about architecture and data management.

Our Top Tool Power BI: Efficient Analyses Without Technical Knowledge

With a strong focus on Self-Service BI, end users can independently and without in-depth technical knowledge conduct data analyses and create reports using the Microsoft Power BI solution. This leads to a significant increase in efficiency within companies. Power Query is regarded in Power BI as a powerful tool for importing, transforming, and modeling data from various data sources. This is particularly useful for users who are already familiar with Microsoft Excel. The creation, publication, and sharing of reports with stakeholders can also be done through the Power BI Service. Furthermore, the Power BI Service offers a continuous data refresh and integration with intelligent ETL processes to keep data in reports up to date without manual intervention.

For report generation, the Power BI tool offers a wide range of built-in and custom visualizations available through the Power BI Marketplace. Thus, commonly used calculations such as "Running Total", "Cumulative Total", "Comparison of Previous/Next Values", "Percentage Changes", "YTD", etc., can be easily represented with different user-friendly options from visual calculations.

Advanced Analyses with DAX in Power BI

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

DAX greatly enhances the capabilities of Power BI and offers the flexibility to create calculated columns, measures, custom filters, and contexts. This enables companies to gain deeper insights and derive important findings from their data to improve performance across the entire organization.

Self-Service BI at CarByte

We have already successfully integrated Power BI as a reporting tool with our customers, who benefit from the connection to various data sources such as Jira and Microsoft Dynamics. For this purpose, we were able to provide a custom-developed database connector, which enables the consolidation into a common data model. Thus, a wide range of questions can be answered flexibly.

We are always happy to advise you without obligation on your Self-Service BI use cases!