Learn how to build a solid technology architecture to ensure the optimum performance of Power BI.
To optimize its Power BI system, a global insurance company recognized the need for comprehensive training. The training focused on configuring and setting up a robust Power BI architecture, enabling the company to analyze and visualize data more effectively. Through the training, the company aimed to improve the accuracy of insights generated from its data while reducing refresh and load times for data views.
Given the global reach of this company, with operations spanning over 80 countries and a workforce of over 50,000 employees, managing and analyzing the vast amounts of data generated can pose a significant challenge. To ensure that the organization's data processing needs are met, a robust Power BI architecture is essential. Therefore, the company has implemented a Snowflake instance to store their data and run their queries. However, the company encountered excessive load times when accessing data from the Snowflake server. This was attributed to the large and disorganized nature of the data stored within the server. Consequently, there was a need to create a well-architected Power BI architecture that could seamlessly integrate with the Snowflake instance.
Typically, organizations that independently implement Power BI create connections to data using the Power BI desktop, which is then published to the cloud. However, this approach presents challenges, especially with large amounts of data. Specifically, creating hundreds or thousands of individual dataset connections to the data source (in this case, Snowflake) overloads the system and reduces operational efficiency. As a result, a more streamlined approach was required to reduce the number of individual connections and improve system performance.
Power BI for Meaningful Data Reports
To address the data processing challenges faced by this organization, JourneyTEAM developers provided extensive training to the technical team. The training focused on Data Analysis Expressions (DAX) and data modeling, as well as creating meaningful reports in Power BI. This comprehensive training laid a solid foundation for the company's Power BI system, enabling it to manage and analyze data more efficiently. Consequently, the Snowflake server was no longer overloaded, and data could be pulled from the server more quickly.
The efficient data reporting process created in Power BI resulted in cost savings for the organization. This was achieved by reducing the excessive costs associated with frequently loading and pulling data from the Snowflake server. Furthermore, the streamlined data management process in Power BI improved overall operational efficiency.
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