Data management

Question 1

What are the types of organizational data?

Answer 1

structured, semi structured and unstructured data

Question 2

What is data management according to (SAP, IBM and Tablaeu

Answer 2

The practice of collecting, organizing, managing, and accessing data to
support productivity, efficiency, and decision-making (SAP)
▪ Data management is the practice of collecting, processing and using data
securely and efficiently for better business outcomes (IBM)
▪ The practice of collecting, organizing, protecting, and storing an
organization’s data so it can be analyzed for business decisions (Tableau)

Question 3

Benefits of data management?

Answer 3

Visibility: Increases the visibility of organizational data assets, making it
easier for stakeholders to find the right data for their needs
▪ Enhanced customer experience: Enables personalization of customer
journey/targeted marketing
▪ Reliability: Minimizes errors by establishing processes & policies for usage… builds trust
in the data being used to make decisions across the organization
▪ Security: Protects the organization and its employees from data loss, thefts, and
breaches with authentication and encryption tools
▪ Scalability: Greater flexibility to scale up/down depending on needs (e.g. cloud
platforms)
▪ Regulatory compliance: Enables businesses to be compliant with data privacy
regulations (e.g., GDPR, POPIA)

Question 4

Types of data management?

Answer 4

Data pipelines: Information pathway that supports data transfer from
one system to another
▪ Extract, transform, load (ETLs): A type of data pipeline that extracts
data from one system, transforms the data through formatting, and
loads the data into another storage location (e.g. a data warehouse)
▪ Data catalogs: Supports metadata management to create a complete
picture of the data. Provides a summary of changes, locations, &
makes it easy to find data
▪ Data architecture: Provides a formal process to manage data flow,
including storage, usage & compliance
Data security: Protects data from breaches, theft and unauthorized
access
▪ Data modelling: Visual representation of the flow of data through a
system or between different systems
▪ Data governance: The rules, standards & policies that govern how
data will be maintained to ensure data quality, integrity & compliance

Question 5

Data management challenges?

Answer 5

Lack of data insight: The increasing amount of data can make it difficult
for organizations to sift through data, identify trends and gain
actionable insights from the voluminous data
* Compliance with changing data requirements: The ever-changing
regulatory requirements make it hard for businesses to commit to a
data management strategy…even more so for businesses with
international presence
* Integrating disparate databases: Data management platforms typically
draw data from different sources. Some systems or databases may be
difficult to integrate, leading to inaccurate, incomplete or incorrect data
formatting