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Data Warehouse Visualization with Power BI

How to visualize your Data Warehouse using Power BI

If you have multiple data sources, unstructured data, you need historical data for reporting – Data Warehouse is a must for you. Quality reporting begins with a quality foundation, in this case, a quality data warehouse.

Power BI is a cloud-based analytics tool that enables you to visualize any data using the unified, scalable platform for self-service and enterprise business intelligence (BI) that’s easy to use and helps you gain deeper data insight.

Data warehouse and Power BI are complementary. Power BI allows you to directly connect to the data stored in your DWH and enable data-driven decisions throughout the organization.

 

Do you really need a Data Warehouse to use Power BI?

Technically, you can use any data source with Power BI, even a simple text file. However, in order to answer this question properly, you need to determine your end goal. For example, if you are trying to gain valuable insights from your rather large database, you will need a data warehouse to consolidate all of your data.

Power BI allows you to directly connect to the data stored in your PI DWH Banking model, offering simple and dynamic exploration.

 

What are the benefits of the analytics layer on top of the DWH?

Visualized reports – discover insights hidden in your data and enable everyone at every level of your organization to make confident decisions using up-to-the-minute analytics.

Fast insights – data warehouse will provide you with rapid data access resulting in instant insights valuable for decision making. Having lots of non-consolidated data will result in a tedious reporting process. If you store all the information in one file, you might end up with a large file with slow refresh times.

Historical data – if your case is to push live data into Power BI and no historical information, then a data warehouse is not required. However, to analyze different time periods and historical trends and make future predictions, the best way to do that is by implementing a data warehouse.

Aggregated data from multiple sources – merging information from various sources helps you to make a better-informed decision. DWH enables you to see the big picture and provides a holistic view of the organization, connecting all departments to help them work as a team.

 

Data analytics challenges in the Banking industry 

If you have multiple data sources, unstructured data, you need historical data for reporting – Data Warehouse is a must for you. Quality reporting begins with a quality foundation, in this case, a quality data warehouse.

The banking industry, in particular, has accumulated a large amount of customer data. Combining forces of multiple tools like  Banking Data Warehouse and Power BI this data provides a great insight into customer trends and historical data, improving retention and segmenting your customer base to acquire new customers effectively.

Imagine having an interactive report that shows your number of customers, the distinction of legal entities and individual customers, and additional numbers related to specific groups of customers like PEP clients.

Think about the possibility to track trends like the number of new clients or lost customers over time and current information -current credit risk rating of the customer, age segment, income segment, country, or geolocation of client’s resident address.

Track crucial KPI’s such as Current total bank exposure, Net Interest Income, EVA, Deposit and Loan Balance YoY.

 

Power BI report - Banking Data Warehouse

 

Check out the power of data visualization on top of the DWH Banking model and deep dive into all the possibilities for reporting in this Power BI reports!

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Learn how to visualize your Data Warehouse using Power BI!

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