What is Source-to-Target Mapping?Consider this, you shift from one house to the other. Now, will you leave all the items you owned in the previous house, or will you move each one of these items to the new house exactly at the proper place? Surely you will opt for the second as you will need these items from time to time to run your house chores effectively. Similarly, a business operation requires data to run effectively. For this purpose, it needs to source data from the initial data mart to the final destination, which is commonly the data warehouse. A good example here will be of a restaurant that has a dine-in facility available with over 20 tables. It is listed on a travel website where the data is passed in real-time about the status of each table - whether it is vacant or occupied. Now, if the sourced data (from restaurant to the site’s booking system) is not matched to the right column in the destination system, that restaurant will start to get double bookings for the same table or lose bookings due to outdated data. This is just one instance. The same thing can occur for seats on a flight, for rooms in a hotel, or even critical issues such as the number of beds in a hospital. Botched data mapping can lead to data loss, which in turn hits the bottom line of any organization.
Why Use Source-to-Target Data Maps
- For creating pre-ETL data models
- When a new data point is added to the sourced system
- Before moving data to OLAP or Tabular system for report generation
- When a new repository is added to the data model
- For consolidating data of multiple sources into a single data warehouse or a data lake
- After applying new business transformations and conversion rules to sourced data