Data Governance Basics

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Data Governance Basics
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Introduction

Data is now everywhere – it is created by almost everything a company does. Management of your organization’s data is critical. The objective of the course is to present attendees the primary characteristics needed to implement a set of policies on good Data Governance at the corporate level. Students will learn how to manage the motivations, implications, architecture, and processes that intersect throughout the data life cycle.

Objectives

At the end of this course students will be able to:

  • Understand importance of having good data management
  • Identify business responsibilities regarding data
  • Follow a set of implementation steps for Data Governance
  • Understand how architecture influences Data Governance
  • Evolve a Data Architecture to a Data Model
  • Identify data storage requirements
  • Identify how to protect data assets through controls
  • Ensure data quality throughout the life cycle
  • Properly exploit data

Student Profile

This course is designed for:

  • Data analysts and managers
  • Auditors
  • CDO, CIO, CTO, CFO, CEO
  • Process managers
  • Any professional involved in the treatment and management of data

Prerequisites

We recommend that student how attend this course have exposure to data standardization, data security, various databases, and/or some knowledge of business process management.

Course Materials

Each student will receive a copy of the course documentation prepared by Netmind.

Methodology

Engaging and interactive course. Our instructors teach all course materials using the demonstrative method; the participants learn new concepts through exercises and real application practices.

Certification

There is no official certification issued for attending this class. However, students will earn 14 credit hours for their attendance.

Accreditation

A certificate of attendance will be issued to students who attend the course for at least 75% of the duration.

Course Outline

  1. Introduction
    1. Objectives: Define what data management really means and why is it important to the business
    2. Course objectives
    3. Data management
    4. Motivations and objectives of the business
    5. Basic concepts
    6. LADY
  2. Government of Data
    1. Objectives: Identify the responsibilities of the business regarding data
    2. Ethical principles of data
    3. What is data governance
    4. Data governance activities
  3. Implementation of the Data Governance
    1. Objectives: Considerations to take into account when implementing the Data Governance
    2. Implementation guide
    3. Metrics
    4. Assessing the Maturity of Data Management
    5. Organization of Data Management and Expectations of Roles
    6. Organizational Change Management and Data Management
  4. Data Architecture
    1. Objectives: Role of architecture in Data Governance
    2. Company Domains
    3. Enterprise Architecture Frames
    4. Enterprise Data Architecture
  5. Data Design and Modeling
    1. Objectives: Transition from a Data Architecture to a Data Model
    2. Introduction to Data Design and Modeling
  6. Storage and operations
    1. Objectives: Identify the needs when storing data
    2. Business drivers related to data storage
    3. Database management and its technology
    4. Tools and techniques
    5. Asset Management
  7. Data security
    1. Objectives: Identify how to protect our data assets through controls
    2. Policies, standards and requirements
    3. Tools
    4. Techniques
    5. Implementation guides
  8. Integration and interoperability
    1. Objectives: Identify how to extract, transform, and load data from different sources
    2. Data integration across platforms
    3. Monitoring
    4. Tools and techniques
    5. Implementation and governance
  9. Quality Management
    1. Objectives: Guarantee data quality throughout the life cycle
    2. What level of quality do we need?
    3. Objectives, development and deployment of validation operations
    4. Tools
    5. Techniques
  10. Big Data and Data Science
    1. Objectives: Properly exploit the data
    2. Big Data strategy and business needs
    3. Data modeling
    4. Tools
    5. Analytical techniques
    6. Phased implementation

Public Classes

Currently, we don't have any public sessions of this course scheduled. Please let us know if you are interested in adding a session.

See Public Class Schedule

Course Details

Reference

JST 135

Duration

2 days

Delivery Mode

Virtual, Face-to-Face
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