Resolving Data Quality Issues Part 02 Issues Caused by Data Entry Processes Data Entry Interface Issues Poorly designed data entry interfaces can contribute to data quality issues. If a data …
Data Quality – Business Rules
Business Rules in Data Quality Business Rules are commonly implemented in software or by using Document Templates for Data Entry. Some common simple Business Rule types are: Type of Business …
Data Quality Programs – Guidance and Principles
Why Data Criticality Matters for a Successful Data Quality Program Criticality: Data Quality programs should focus on the data most critical to the enterprise and its customers. Priorities for improvement …
OLAP – ROLAP, MOLAP and HOLAP
How OLAP, ROLAP, MOLAP, and HOLAP Work OLAP – Online Analytical Processing It is a technology used to organize large business databases and supports performing complex and multidimensional analysis, at …
Data Warehouse, Data Lake & Data Vault
Understanding Data Lake vs Data Warehouse Data Lake and Data Warehouse both act as repositories, but they are designed for very different purposes. Data Warehouses work best for specific projects …
Data Warehouse Implementation – Guidelines and Principles
Aligning Data Warehouse Projects with Business Goals Importance of Defining End Goals for Data Warehousing Global Data Warehouse Implementation Design with Localized Execution Optimizing Data Summarization Strategies in Data Warehousing …
Data Management – DII (A Momentary Look)
Integrated Data Systems and Interoperability Overview Planning and Analysis Phase in Data Management – DII Designing Data Integration Architecture Interaction Models and Data Services Modeling Hubs and Exchange Patterns in …
Data Management – Manage Versioning and Control
ANSI Standards 859 – Levels of Data Control in Data Management ANSI Standard 859 has three levels of control of data, based on the criticality of the data and the …
DII – Need and Dependency
Data Integration and Interoperability (DII) – Need and Dependency Why DII is Critical for Data Management Functions Data Integration and Interoperability is critical to Data Warehousing and Business Intelligence, as …