When building a data warehouse, you often need to flatten the data when you move it from the Raw tables to the Stage tables. Flattening data can be a difficult concept for new warehouse designers to grasp, so here are two detailed examples.
If you're inexperienced with using SSIS, creating a data warehouse might seem like an impossible task—but it's not if you use some different strategies. For example, you can use a wizard to initially create an SSIS package that will move data from the source system into the data warehouse.
Data quality is really important. Why? Because it helps you save money while increasing profits because of accurate contact data. It’s important to understand what data quality is and why it is important....More
Are you dealing with national and international records? The more expansive your records are in territory, the more problems you will face when it comes to verifying addresses. Not only are you dealing with language differences, but you are also dealing with different address formatting for different countries....More
Your contact data is valuable, but is it up to its full potential? Without the proper maintenance, the quality of your data quickly decreases--so quickly that 50% of databases deteriorate after only two years. It is an absolute necessity to maintain your data in order to decrease costs and increase profits....More