Data Management Focus Groups
The North Texas chapter of Data Management Association (DAMA) gladly partners with organizations to help pass on knowledge and best practices related to data management / data governance. The motivation of the Board is to setup various DAMA focus groups to help local businesses solve actual data management problems. If you have any ideas or topics of interest, please let contact Kevin Ladwig at 972.979.3465 or email@example.com.
Past members have expressed interest in the following knowledge areas:
- Data Governance – planning, oversight, and control over management of data and the use of data and data-related resources. While we understand that governance covers ‘processes’, not ‘things’, the common term for Data Management Governance is Data Governance, and so we will use this term.
- Data Architecture – the overall structure of data and data-related resources as an integral part of the enterprise architecture
- Data Modeling & Design – analysis, design, building, testing, and maintenance (was Data Development in the DAMA-DMBOK 1st edition)
- Data Storage & Operations – structured physical data assets storage deployment and management (was Data Operations in the DAMA-DMBOK 1st edition)
- Data Security – ensuring privacy, confidentiality and appropriate access
- Data Integration & Interoperability –acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization and operational support (a Knowledge Area new in DMBOK2)
- Documents & Content – storing, protecting, indexing, and enabling access to data found in unstructured sources (electronic files and physical records), and making this data available for integration and interoperability with structured (database) data.
- Reference & Master Data – Managing shared data to reduce redundancy and ensure better data quality through standardized definition and use of data values.
- Data Warehousing & Business Intelligence – managing analytical data processing and enabling access to decision support data for reporting and analysis
- Metadata – collecting, categorizing, maintaining, integrating, controlling, managing, and delivering metadata
Data Quality – defining, monitoring, maintaining data integrity, and improving data quality