3. Importance of Data Capturing for
Monitoring and Review
Decision Making
Effective data capturing supports informed
decision-making based on real-time insights.
Performance Evaluation
It plays a crucial role in evaluating the
performance of systemsand processes.
Trend Analysis
Enables the identification of trends and
patterns for proactive adjustments and
improvements.
Risk Management
Helps in identifying potential risks and taking
preventive measuresfor mitigation.
4. Types of data that can be
captured
Quantitativedata:Numerical data such asrevenue,sales figures, or
website traffic.
Qualitativedata:Descriptive data like customer feedback, interviews,
or focus groups.
Behavioraldata:Dataon user actions and interactions, including
clicks,downloads,or social media engagement.
5. Tools and methods for data
capturing
1 Manual Data Entry
One of the simplest methods, involving inputting data manually into a
systemor database.
2 Automated Data Collection
Utilizing sensors,IoT devices,or software to collect and store data
automaticallyin real-time.
3 Optical Character Recognition (OCR)
Scanning and converting physical documents,PDFs, or images into editable
and searchable data.
6. Best practices for data capturing
Consistent Data
Format
Use standardized templates
and formats for data entryto
ensure consistencyand easy
analysis.
Data Integrity Checks
Implement regular data
integritychecks to identifyand
correct anyinaccuracies or
inconsistencies.
Comprehensive
Documentation
Thoroughlydocument the data
capturing process to facilitate
understanding and replication
of results.
7. Challenges and Limitations of Data
Capturing
Data Security
Protecting captured data fromunauthorized
access and breaches is crucial for
maintaining data integrity
.
Data Volume
Managing and storing large volumes of
captured data can strain resources and
infrastructure.
Data Ǫuality
Ensuring the accuracy
,completeness,and
consistencyof captured data can be a
significant challenge.
Data Privacy
Respecting privacyregulations and ethical
considerationswhen capturing sensitive
data is a complex task.
8. Data Capturing Process and
Workflow
1
Data Identification
Identifythe specific data to be captured for analysis.
2
Data Collection
Collect the identified data using appropriate tools and methods.
3
Data Storage
Store the captured data securelyand accessiblyfor analysis.
