Our Data glossary Management
This glossary aims to contribute to the clarification of key notions and concepts commonly used in Data Management. It is based on common and documented sources designed to harmonize Data Management knowledge and practices. You are convinced of the standardization need in the field and would like to contribute ? Please, send us a note !
Chief Data Officer
The Chief Data Officer an executive or senior manager in charge of Data. As this is a relatively new position, the job description may vary depending on the context and the hierarchical position of the Chief Data Officer. Four scenarios seem to be the most common:
- direct report to the CEO;
- reporting to a business executive such as CMO;
- reporting to a cross-functional department executive such as Chief Innovation Officer or Chief Transformation Officer;
- reporting to the CIO.
In enterprises that have choosen to centralize all data related matters under the direction of the Chief Data Officer, the CDO's responsibility includes :
- Data governance (including strategy),
- Data valuation with Analytics and AI,
- Data monetization with the creation of revenue-generating data products,
- Data architecture and application management,
- Data protection and security,
- Regulatory compliance and Ethics.
Since the appointment of the first Chief Data Officer in 2002 in the United States, more and more companies are recognizing the need to create the position of CDO in their organizations. According to a recent study, 57% of Fortune 1000 companies now have a CDO on their team.
Sources: CIO.com; Harvard Business Review; DAMA DMBOK 2.
Data Governance is defined as the exercice of authority and control (planing, monitoring and enforcement) over the management of data assets.
The Data Governance function guides all other data management functions with the following key focus areas on Data :
- Stewardship & Ownership,
- Culture Change,
- Principles & Ethics,
- Data Valuation,
- Data Maturity Assessment,
- Data Classification.
Sources : DAMA DMBok 2
IDC defines Data intelligence as intelligence about Data (not - like Analytics - from Data).
Data intelligence leverages business, technical, relational and operational metadata to provide transparency of data profiles, classification, quality, location, lineage and context; Enabling people, processes and technology with trustworthy and reliable data.
Sources : IDC.
Data Management is the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles.
Data management activities are wide-ranging. They include everything from the ability to make consistent decisions about how to get strategic value from data to the technical deployment and performance of databases.
The different disciplines of Data Management can be grouped as follows :
- Data Governance,
- Foundational activities :
¤ Data Protection (Privacy, Security, Risk Management),
¤ Metadata Management,
¤ Data Quality Management;
- Lifecycle management activities,
¤ Plan & Design : Architecture, Modeling, Design,
¤ Enable & Maintain : Big Data Storage, Data Warehousing, Master Data Management, Data Storage & Operations, Reference Data Management, Data Integration & Interoperability;
¤ Use & Enhance : Data Science, Data Visualization, Data Monetization, Predictive Analytics, Master Data Usage, Business Intelligence, Document & Content Management
Sources : DAMA DMBok 2