Data Quality Issues Part-03 Issues Caused by System Design Failure to Enforce Uniqueness Constraints Multiple copies of data instances within a table or file expected to contain unique instances. If …
Data Quality – Causes of Data Quality Issues – Part-02
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 – Causes of Data Quality Issues – Part-01
Common Data Quality Issues – Part 1: Causes and Consequences Common Data Quality issues can emerge at any point in the data lifecycle, from creation to disposal. When investigating root …
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 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 …
DII – Data Interaction Models – P2P, Canonical and Publish/Subscribe
Data Interaction Models in DII Canonical Model (Hub-and-Spoke) A Canonical Data Model is a common model used by an organization or data exchange group that standardizes the format in which …
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 …