Data Ecosystems and Governance in Organizations


The entire business is composed of a set of internal and external variables important for the elaboration of corporate strategies. The better the
understanding of the characteristics that make up a company's activities, the greater the impact that this knowledge has on the decisions to be
made. Information never is too much. The more data the better to make decisions, set goals, define strategies or any other action that involves an
organization, whether public or private. There is no way to obtain accurate data without research and if we can gather all the important
information in the same location, even better!
In this course we will understand the huge variety of data that we have access to in our daily lives, the computer systems that manipulate and
store them and how we can extract useful information for the business and to support decision making. Topics such as access to data, by whom
and how, are extremely important for reasons of security and privacy, and a policy of access to data is essential. The last objective of this course
is the General Data Protection Regulation, its impact on organizations and the approach to a protection and data compliance program.

General characterization





Responsible teacher

José Carlos Teixeira


Weekly - Available soon

Total - Available soon

Teaching language





DAMA, The Data Management Association. Guide to the Data Management Body of Knowledge , 2014.
KIMBALL, Ralph, Foreword by W. H. Inmon. The Data Warehouse Toolkit . Practical Techniques for Building
Dimensional Data Warehouses. Wiley 2013.
MARR, Bernard. Biga Data in Practice . How 45 successful companies used Big Data Analysis to deliver
extraordinary results. Wiley 2016.
RAMESH, Sharda, DELEN, Dursun, TURBAN, Delen. Business Intelligence, Analytics, and Data Science . A
Managerial Perspective. Pearson Education Limited, 2018.
SARSFIELD, Steve. The Data Governance Imperative . A business strategy for corporate data. IT Governance
Publishing 2011.
SOARES, Sunil. The IBM Data Governance Unified Process . Driving Business Value with IBM software and
Best Practices. MC Press Online, 2011.
VOIGT, Paul, BUSSCHE, Axel Von. The EU General Data Protection Regulation (GDPR). A Practical Guide.
Springer, 2017.
The Bibliography for this course is optional.
We can privide e-Books for a major part of it, at the request of the student.

Teaching method

Lectures will cover the fundamental topics of the course, including some time for questions, discussion on case studies presented and guest
The first 3 weeks will be focused on Data Ecosystem, the third week on Data Governance, and the last 2 weeks in GDPR.

Evaluation method

Assessment Methods:
Mid term Exam (40%).
Final Exam (60%).

Subject matter

The course is organized in 3 modules, covering the topics below.
1. Data Ecosystem : Is a collection of infrastructure, analytics and applications used to capture and analyze data. Key concepts will be: Sources
and types of data; Structured and unstructured data; Cloud computing; Big Data; Business Intelligence; Data Warehouse and Data Mart; Data
Mining and Machine Learning; Data Management; Data Management and Data Usage; Indicators and KPIs.
2. Data Governance : Is a transversal program to the organization that consists of a set of rules and procedures that guarantee the integrity,
privacy and security of data: Why Data Governance; Benefits of Data Governance; Approach to a Data Governance Program; Data Governance
Office; Data Governance Principles and Policies.
3. GDPR : General Data Protection Regulation and its impact in organizations: Scope and Definitions; Stakeholders; Principles (Data
Minimization, Lawfulness of Treatments, Conditions for Consent, Controller and Processor); Registration of Treatment Activities; Data
Protection Impact Assessments (DPIA); Breach Notifications, Fines and Penalties; Electronic Marketing (PECR); Approach to a GDPR
Implementation; Main challenges for organizations.


Programs where the course is taught: