1.
DATA QUALITY
MANAGEMENT
Presented by,
Chandana Maya S
2147014

2.
AGENDA
 Data quality management.
 Why do you need data quality management?
 Major causes of poor data quality.
 Essential factors for clean data.
 How to maintain clean data?
 Best data quality tools.

3.
Data Quality Management
 Data quality management consists of the processes and practices of constantly
maintaining a high quality of information.
 Data quality management includes the process of identifying poor-quality
data, cleaning it, and making it usable with your business intelligence
platforms.

4.
Why do you need data quality management?
 Data enters an organization in various ways, so not all the data is accurate and
perfect. It may be outdated, duplicated, or inconsistent.
If it is not accurate and consistent, you cannot use it to make important
decisions.
Making business decisions based on incorrect and unreliable data could cost
you a fortune.
 Data quality management helps you find the poor-quality
data and detect how it is coming into your database.
 Then you can clean that data and prevent more from entering
your database.

5.
Major causes of poor data quality
Manual entry
Acquisition and mergers
Real-time updates
Indiscriminate data collection
System upgrades

6.
Essential factors for clean data
Completeness

7.
Accuracy

8.
Consistency

9.
Timeliness

10.
Integrity