What exactly is involved in Data Governance?

Data governance involves a holistic approach to managing data throughout its lifecycle, from creation to retirement and it encompasses a set of processes and practices aimed at ensuring the availability, quality, security, and proper management of an organization’s data. . It ensures data accuracy, security, and alignment with business goals. 

Key activities involved in data governance are:

1. Data Classification and Contextualization:

• Identify and classify data based on its sensitivity, criticality, and business context.
• Apply metadata tags to data to enhance visibility and understanding.

2. Data Profiling and Data Mapping:

• Profile data to understand its characteristics, patterns, and quality.
• Create data maps to visualize data flows and relationships across systems.

3. Data Lineage:

• Establish data lineage to track data movement from source to destination.
• Understand how data is transformed, aggregated, and used within the organization.

4. Metadata Management:

• Maintain metadata repositories that describe data attributes, definitions, and ownership.
• Ensure consistent metadata across systems.

5. Data Ownership and Stewardship:

• Assign data ownership to specific individuals or teams.
• Define roles and responsibilities for data stewardship.

6. Data Security and Privacy:

• Implement security measures to protect data from unauthorized access.
• Comply with privacy regulations (e.g., GDPR, CCPA) by managing access and consent.

7. Data Quality Control:

• Monitor data quality through data profiling, validation, and cleansing.
• Address data anomalies and inconsistencies.

8. Data Access and Authorization:

• Define access controls based on user roles and permissions.
• Ensure appropriate data access for authorized users.

9. Data Risk Management:

• Assess data risks (e.g., data breaches, data loss) and develop mitigation strategies.
• Monitor and respond to data security incidents.

10. Data Sharing and Dissemination:

• Establish guidelines for sharing data within and outside the organization.
• Facilitate secure data exchange with partners and stakeholders.

11. Compliance Monitoring and Auditing:

• Regularly audit data governance processes and policies.
• Ensure ongoing compliance with data regulations and internal standards.

12. Data Governance Council or Committee:

Form a cross-functional group responsible for setting data governance policies and making strategic decisions.

My Experience with DLP - Data Loss Prevention (Airbus)

 ForcePoint DLP

Forcepoint Data Loss Prevention (DLP) is a robust solution designed to safeguard sensitive data across various channels, including web, cloud, email, network, and endpoints. 

• The solution dynamically adjusts policy enforcement based on user behavior to prevent data breaches. (risk based policy enforcement)
• Real-time audit and intervention help stop data loss before it occurs. 
• Forcepoint DLP accurately classifies sensitive data using artificial intelligence.
• It protects against unauthorized actions (e.g., downloading, emailing) on files containing intellectual property or sensitive information.
• Unstructured data discovery
• Email data theft prevention (outbound and inbound emails).

My activities.

• DLP Network and Endpoint security project.
• Due diligence - 79 laptops identified and deployed DLP. Gathered stats and reporting.
• Eventually 600 laptops. Filton.

> Data prioritization was done by the business (what data to classify / protect, etc.)

> Categorize data -- apply appropriate classification tags

> Policy creation and configuration (Security devs in conjunction with security teams)

> Deployment options -- POC on 79 laptops, gather stats, report.

> Actualy deployment on 600+ laptops.

> Dashboard configuration, monitoring / reporting, define BAU processes. 

> Training and user education.

Metrics gathered

On time resolution rate

Resolution rate

Delivery time

Audit rate

Bug fixing change time

Change blocking incident

Change duration

Change incident

Change volume

On time change rate

On time urgent change rate 

Unplanned change communication

Planned change communication

Urgent change time

Introduction to Data Analytics - IBM

Python Programming

•  List vs Tuple

List is mutable whereas Tuple is unmutable. You can change values in a list once it is defined, however for a Tuple, once the values are defined, they cannot be changed / manipulated. 

• List

Mutable: Can be modified after creation (elements can be added, removed, or changed).
Ordered: Maintains the order of elements.
Indexable: Allows access to elements by their index.
Dynamic Size: Can grow or shrink as needed.
Syntax: Defined with square brackets, e.g., [1, 2, 3].
Methods: Extensive set of methods for modification and querying (e.g., append(), extend(), remove(), pop(), sort()).

my_list = [1, 2, 3]

my_list.append(4)  # [1, 2, 3, 4]

my_list[1] = 5     # [1, 5, 3, 4]

• Tuple

Immutable: Cannot be modified after creation. 

Ordered: Maintains the order of elements.

Indexable: Allows access to elements by their index.

Fixed Size: The size is fixed upon creation.

Syntax: Defined with parentheses, e.g., (1, 2, 3).

Methods: Limited set of methods mainly for querying (e.g., count(), index()). 

•  

Business Analysis Fundamentals

As a business analyst, 

1. You'll facilitate communication between different stakeholders, business users, IT teams and management, 
2. Organizing meetings, 
3. Gathering requirements, and ensuring everyone is aligned, 
4. Driving projects forward with clarity and efficiency. 
5. Gather and document business requirements for projects or initiatives, 
6. Conducting interviews, surveys, or workshops with stakeholders to understand their needs and priorities, 
7. Translating these requirements into actionable plans for development teams. 
8. Testing and validation, you'll assist with user acceptance testing or UAT, ensuring that new software meets end users needs before deployment. 
9. Support project managers in coordinating and tracking project activities, milestones and timelines, 
10. Updating project plans, monitoring progress, and communicating status updates to stakeholders. 
11. Participate in process improvement initiatives, identifying areas for optimization, and proposing solutions to streamline operations. From suggesting workflow improvements to enhancing inventory management processes, your insights will drive continuous improvement within your organization. 

Tasks of a BA

• Problem identification / business needs / root cause
• Stakeholder management
• Risk management
• Process analysis and process improvement
• Data analysis
• Gathering requirements and documenting them
• Solution evaluation and recommendations
• Testing and validation
• Implementation support
• Continuous improvement

End to End Process

Electricity supply company. 

Issue is customer churn. Nearly 50% of their customers do not renew their contracts with the electricity supplier.

BA is involved here at Project Initiation / Requirements gathering / define project scope / conduct feasibility studies.

Before conducting the stakeholder workshops on the requirements, BA goes thru:

> Churn statistics

> Customer complaints

> Surveys

> Trace customer journeys

> Review Google Analytics of customer journeys