Logo

Resources

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 !

A

|

B

|

C

|

D

|

E

|

F

|

G

|

H

|

I

|

J

|

K

|

L

|

M

|

N

|

O

|

P

|

Q

|

R

|

S

|

T

|

U

|

V

|

W

|

X

|

Y

|

Z

D

Data Governance

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 :
- Strategy,
- Policy,
- Stewardship & Ownership,
- Culture Change,
- Principles & Ethics,
- Data Valuation,
- Data Maturity Assessment,
- Data Classification.

Sources : DAMA DMBok 2

Data Intelligence

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

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