In these slides, I present a general idea about data management and its importance in the field of organization development and business

1. Data Management
Hassanein Alwan Malik
Iraq,MSc in AI, University of Technology

2. Data vs. Information
 Data
Data is raw, unorganized facts that need to be processed. Data can be something
simple and seemingly random and useless until it is organized.
 Information
When data is processed, organized, structured or presented in a given context so
as to make it useful, it is called information.

3. Example
 Data
Each student's test score is one piece of data.
 Information
The average score of a class or of the entire school is information that can be
derived from the given data.

4. Data Management
 Simply put, data management is all of the activities necessary to make
research data discoverable, accessible and understandable today, tomorrow,
and well into the future.

5. Importance of data management
 DM can be used to make more-informed business decisions, improve
marketing campaigns, optimize business operations and reduce costs, all with
the goal of increasing revenue and profits.

6. Life Cycle of DM
• Choosing file formats
• File organization & naming conventions
• Version control
• Document all project/file details
• Access control & security
• Backup & storage
• File format conversions
• Sharing and preservation

7. Manual Processes of DM
 Policies for what data to record
 Standardized forms for collection of data
 Controlled document, like SOPs
 Policy for organization, indexing and storage to facilitate retrieval
 Training

8. Automated Processes of DM
 Policies for what data to record
 SOPs for operation of software for:
 Data entry
 QA checks/verification
 Archival of primary results (e.g. agarose gel images, raw chromatogram data etc.)
 Report generation

9. Why develop a DMP
 DMPs help you to properly manage your data for your use, meet funder needs
& enable sharing
 i.e. they're useful whenever researchers are creating data
 They help researchers to:
 Make informed decisions
 Avoid duplication, data loss, and security breaches
 Develop procedures early on for consistency
 Ensure data are accurate, complete, reliable and secure
 Plan to share data and increase the impact