3/10/2024 0 Comments Etl extracttransform load![]() ![]() Once the Rule is run, the data will be added to the Billing Summary module. To run the job, you would run it manually or create a job with a schedule. Here’s how the Rule looks in an editor like Notepad ++. INSERT INTO f_Trans_OT72 (TransactionID, Value1, Value2, Value3, TimePeriod, UDF001, UDF002) Since Rules use Transact SQL, anyone with that knowledge can learn to create a Rule.įor the code, you would reference the objects in Solver. In the example above, you would create a Rule that uses a SQL Insert Into statement. Solver is housed in a Microsoft Azure SQL environment. The heart of the Rule, though, is the stored procedure. There are a few things that you put in the XML portion, like parameters. Think of Rules as processes that are run.Ī Rule is, basically, a stored procedure wrapped in XML. Rules are created outside of Solver but are imported and run within Solver. With Solver, you would use a Rule to take data in one table and put it into another table. If you’re using SSIS, you would probably have a query that views the data in the Billing Detail table, summarizes it, and adds any data, like Territory. The generic connectors include Excel, SQL Server, OData, and Azure SQL. Solver supports multiple connectors, such as those for different accounting, enterprise resource planning (ERP), sales, and customer relationship management (CRM) platforms. For this process, an integration is created. Once the modules and dimensions are created, the next step is to populate the Billing Detail module with data. Similarly, here’s the complete configuration for the Billing Summary module. The items with arrows to the left are dimensions. The next image displays the complete configuration for the Billing Detail module. In the image, only two dimensions are shown. There are multiple dimensions configured for the two modules. When a dimension is added to a module, the system creates a column behind the scenes in the fact table to store the dimension value. ![]() The module schema is how Solver connects the dimensions to the modules. The column will be populated during the data feed. For this example, it was set up as a column. In this setup, you’ll see a column for Territory. A later image will show the relationship. The dimensions will be joined to the module. The reason is these columns will be stored in dimensions. You’ll notice in the following image there are no columns for customer and item. Steps in SolverĬreate modules in Solver for the billing detail and the summary data.īelow are examples of how these modules can be designed. There are many ways to do things, but let’s look at one way you might accomplish these items in Solver. In Microsoft SQL Server Integration Services (SSIS), you would create a package that might do these steps: The amount and profit columns are calculated. The territory data may come from logic or a customer master table that contains a territory column with a value for each customer. Using the above example, notice there are three columns not in the source data: Territory, Amount, and Profit. Using the example above, the FROM data might be your source billing system and the TO data could be a module in Solver called Billing Summary. With Solver, you work with modules and dimensions in a data warehouse. Moreover, the format of the destination data may change and you may need additional columns. For example, you may have detailed invoice information in an invoice system, and you need to create summary records in a reporting system. The reason for ETL is that the data in the source rarely matches how it should be stored in the destination. You can use the ETL process when you’re working with data from a source and putting it into a destination. The big acronym in data integrations is ETL (extract, transform, and load).
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