The difficulty of unsupported data types when importing data from older systems into Power BI can be addressed with the following approaches:
Mapping And Transforming Data Types: Each data source may define its data types differently, which may create challenges when importing into Power BI. Start by analyzing the specific data types available in the legacy system and determine the closest Power BI equivalent. For example, Text may become string, numeric may become decimal, date, and so on. Using the Power Query Editor to load data into the appropriate formats, masking these data types to suit Power BI import formats. This might mean doing some custom transformation or using some other in-built methods like Text. From, Number.From, or DateTime.To ensure conformity with Power BI.
Pre-Transformation at Source: Where practical, it is recommended to resolve the issues related to data types in the source system before any importing to Power BI takes place. Most systems have built-in ways through queries or stored procedures that allow the user to define the transformation of the types of data returned from the queried table. This reduces the need for additional transformation in the Power BI and speeds up the data import process by ensuring that the data comes in already transformed into the required shapes.
Keeping In Mind Null Values And Data Arising From Place Of Inconsistency: Legacy systems may accept or hold values in a way that may not be consistent or use values that do not relate to the expected data types in Power BI (e.g., null or 0). In the case of Power Query, such values can be dealt with by Use Value or by ways of controlling import logic using the if function, which allows putting conditions. Such a step can eliminate issues brought about by avoiding data types or laterally unwelcome data, causing hitches in data infallibility and better organization of datasets in Power BI.
Here’s how you address the issues arising from unsupported data types coming from existing systems and also enhance the trustworthiness of your reports in Power BI.
