4x1 Data Management/Governance/Security/Ethics Masterclass

You'll learn about data literacy, Data Quality operations, Data Governance policies and Data Security/Privacy controls.

4.50 (404 reviews)
Data Science
4x1 Data Management/Governance/Security/Ethics Masterclass
15.5 hours
May 2023
last update
regular price

What you will learn

You'll learn about the frequent data disciplines (Data Management, Data Governance, Data Stewardship, Data Science), their differences and nuances.

You'll learn about the most frequent types of Data Quality (DQ) operations, including profiling, parsing, cleansing, standardisation, record merging, and others

You'll learn about the levels of data sophistication in an organisation, and the usual DM/DG progression from projects to programs to centralised processes.

You'll learn about the 4 major types of data (master data, reference data, transactional data and metadata), as well as what each means, and how they intersect.



There are many activities related to data in organisations.

Data Management (DM), Data Governance (DG), Data Stewardship, Data Science, and many others.

All of these are crucial activities for organisations, especially those trying to protect their data from cyberattacks, complying with regulation, or just trying to improve the quality of their analytics and reports.

Frequently, you can find information on one of these activities, but not all.

And on top of that, many courses use different definitions, so you may become confused.

In short, most courses on data don't fit the minimum requirements.

And this has consequences not just for your career, but yourself personally as well.

What happens when you don't have enough information (or in the adequate format)?

  • You'll become confused by the myriad data activities, the tools used, which roles and responsibilities each person has, and how they intersect;

  • You won't be able to properly identify what belongs to Data Management or what belongs to Data Governance - and what should not be done at all;

  • You'll become frustrated and irritated that you don't know why an operation works, or why it doesn't;

  • You won't be able to identify what a specific data tool should be used for, and when your current tools don't fit the job;

  • You won't know how to optimize your DM and DG operations in an organisation, resulting people not taking data seriously, or making obvious mistakes;

  • You won't be able to know what security controls to apply to what specific data classes, or how to protect data subjects;

So if you want to know everything about Data Management, Data Governance, Data Security and a lot more, what is my proposed solution?

This new course masterclass, of course!


Unlike other data management or data governance courses you'll find out there, this course is comprehensive and updated.

In other words, not only did I make sure that you'll find more topics (and more in-depth) than other courses you may find, but I also made sure to keep the information relevant to the types of data quality issues you'll find nowadays.

Data operations may seem complex by nature, but they rely on simple principles.

In this course, you'll learn about the essentials of how data are managed with activities such as profiling and remediation, as well as how data are governed with processes and policies.

Not only that, we'll dive deep into the activities, stakeholders, projects and resources that each discipline entails.

In this 15-hour+ masterclass, you'll find the following modules:

  • You'll learn about the essential Data Literacy and Considerations (what are the key principles, what are the different data disciplines, usual processes of each, the information lifecycle, and sophistication levels in an organisation);

  • You'll get to know about Data and Data Quality in specific (including the types of data that exist, the types of data quality issues and their financial impact, the Data Management activity process flow, as well as the data dimensions and tools used);

  • You'll learn about Data Governance (including how to define principles and policies, what are the specific activities such as data classification, data lineage tracking and more, as well as how to implement DG from scratch in an organisation);

  • You'll learn about Data Security, Privacy and Ethics (including what security and privacy controls to use to protect data both in physical and logical formats, how to ensure that data subjects are treated fairly by algorithms and across geographies, how to implement and measure data ethics, and more);

By the end of this course, you will know exactly how data are managed and how they are governed in an organisation, to a deep level, including the necessary tools, people, and activities.

The best of this masterclass? Inside you'll find all of these 4 modules - plus countless bonuses.

In short, even if you only fit one of the three profiles (only Data Management, only Data Governance, only Data Security/Ethics, or only "general" Data Quality knowledge), you will still have a course dedicated to it!

And naturally, if you are interested in multiple of these topics... this is the ultimate package for you.


This course is targeted at different types of people.

Naturally, if you're a current or future data professional, you will find this course useful, as well as if you are any other professional or executive involved in a data project in your organisation.

But even if you're any other type of professional that aims to know more about how data work, you'll find the course useful.

More specifically, you're the ideal student for this course if:

  • You're someone who wants to know more about data management itself (how to profile datasets, how to parse/cleanse/standardise them, how to link and merge records, or how to enhance data);

  • You're someone who is interested in data governance (how to define rules and controls for data, how to institute policies, how to define required metadata, how to fill said metadata for different data sources, and many other activities);

  • You're some who is interested in data security and privacy, or in data ethics (that is, how to ensure that data subjects are protected in terms of data safety, but also in terms of actually being treated fairly by processes and algorithms);

  • You're someone who wants to know more about data quality in general (what are the usual types of problems, how do they create financial impact in organisations, what are the usual activities to improve DQ, and so on);


Some people - including me - love to know what they're getting in a package.

And by this, I mean, EVERYTHING that is in the package.

So, here is a list of everything that this masterclass covers:

  • Data Literacy and Fundamentals

    • You'll learn about the 4 key principles for any successful data initiative - considering data at assets, monetising them, seeing DG as business and not IT, and gauging your organisation's sophistication level;

    • You'll learn about the key data disciplines - that is, what is Data Management (DM), what is Data Governance (DG), what is Data Stewardship, and other activities such as Data Science, and terms such as Data Quality (DQ), as well as the specific roles and operations related to each of these in specific;

    • You'll learn about the main activities in DM and DG. In the case of DM, activities such as profiling data, remediating them, and setting future data validity requirements, and in the case of DG, uncovering business rules, setting policies and expectations for data, and controls to measure DQ, among others;

    • You'll get to know the different stages of the information lifecycle. Data being created, accessed, changed, deleted, and possibly other intermediate steps, as well as the usual preoccupations and controls at each stage;

    • You'll learn about the usual progression from projects to processes - how both DM and DG usually start as specific projects with local scope, and usually grow within an organisation, culminating in replicable and centralised processes to manage and govern data;

    • You'll get to know the possible sophistication levels of an organisation in terms of managing data. Being reactive, with no allocated tools or people, versus having centralised and standardised roles, tools and processes for data operations, and gauging your organisation;

  • Data and Data Quality Management:

    • You'll get to know the 4 main types of data. Master data, reference data, transactional data and metadata, as well as the nuances of each and how they intersect;

    • You'll learn about the types of DQ issues and their financial impact, usually in one of 3 main ways: direct costs, operational inefficiencies, and/or compliance or regulatory sanctions;

    • You'll learn about the usual DQ improvement process, starting with profiling, usually followed by triage, remediation of the data, and possible setup of automated controls to prevent future errors;

    • You'll learn about the three main types of DQ actions. Remediating data on the spot, analyzing the root cause of data problems, and/or instituting rules with automated controls to measure/prevent future data problems;

    • You'll get to know the different data dimensions used when analyzing DQ problems. Completeness, accuracy, timeliness, lineage, and other relevant ones;

    • You'll know more about the effect of Big Data and/or AI in data management, specifically the consequences both have in terms of the remediation possibilities and the data pipelines;

    • You'll know more about the tools used for DQ management, including profiling, parsing and standardisation, linking and merging, and data enhancement tools;

    • You'll get to know data profiling tools and their specific uses, including validating values in datasets, detecting outliers, validating data formats and rules, and/or uncovering implicit business rules;

    • You'll learn more about parsing and standardisation tools, which usually take data in different formats, parse them into a unified format, and then standardise data in that format, including the possible removal/editing of wrong values ("cleansing");

    • You'll get to know linking and merging tools, used to prevent duplicates, which usually use a comparison algorithm to establish a match between records, as being the same, which can then be merged;

    • You'll learn about data enhancement and annotation tools, which allow you to add more data to the current data, when these can't be edited - or don't need to be edited;

    • You'll learn more about building a business case for DM/DG, including the usual operations and steps, the usual costs and savings mentioned, and how to present it;

  • Data Governance:

    • You'll learn about the common functions and capabilities enabled by DG, from privacy and security controls to lineage tracking, metadata management, data classification, monitoring and more;

    • You'll learn about the usual roles and responsibilities in DG, from data owners to data stewards, Accountable Executives, who is the Data Council, the differences between the CDO (Chief Data Officer) and CIO (Chief Information Officer), and others;

    • You'll learn about data classification, including the 3 major systems used (by priority and criticality, by sensitivity and privacy requirements, and by processing stage), as well as the consequences of each;

    • You'll learn about what is data stewardship, and how it bridges Data Governance and reality, including multiple tasks related to metadata, master data, reference data, tracking DQ issues, and other activities, as well as the differences between business, technical and operational data stewards;

    • You'll learn about a day in the life in Data Governance, including the tasks that each role performs, how they coordinate, and how decisions are made;

    • You'll learn about assessing your organisation in preparation to implement DG, including data management maturity assessments and change capacity assessments, and how to define the scope of a DG program selecting processes, people and tools;

    • You'll learn about how to engage and obtain buy-in from different stakeholders, how to deal with resistance, how to prioritise the available projects, and how to ensure commitment to DG;

    • You'll learn about how to architect and define the initial DG program, including the tools used, the data lifecycle stages, the roles and responsibilities involved, and how to bring it all together in a single operating model;

    • You'll learn about how to deploy DG initially, with a roadmap, milestones, an operating model, and metrics to track;

    • You'll learn about the possible initiatives complementary to DG, including data-centric projects such as MDM (Master Data Management) or EIM (Enterprise Information Management), analytics and AI projects, and big ERP implementations, as well as how to let DG "piggyback" on these;

    • You'll learn about how to maintain a DG program, including maintaining key processes such as training and communication, while enforcing behavioral change through change management and controls;

    • You'll learn about how to scale a DG program, including dealing with resistance by new stakeholders from new projects and defining the federation of DG as it grows within the organisation;

    • You'll learn about how culture affects DG, including how aspects such as data literacy, commitment and others define the resources and the people accountable for DG;

  • Data Security, Privacy and Ethics

    • You'll learn about cryptographic protection (how to protect data with encryption), and measures to take into account;

    • You'll learn about data retention and disposal - that is, how to minimise retention time for data which may be leaked, as well as dispose of them securely;

    • You'll learn about locked rooms, locked devices and/or locked ports, placing physical barriers in front of attackers trying to steal data;

    • You'll learn about physical media protection, that is, how to protect media such as HDDs, USB drives, or paper while at rest, in transit and during their destruction;

    • You'll learn how service provider assessment and monitoring is done, to prevent third parties from introducing vulnerabilities in your organisation;

    • You'll learn about how geographical regulation affects data privacy - that is, how different countries may have different demands in terms of data subject privacy;

    • You'll learn about data governance structures, and how they can ensure that data ethics are taken care of in a centralised, standardised manner;

    • You'll learn about defining security controls by data classification, which allows us to protect more sensitive data with stricter controls and vice-versa;

    • You'll learn about media downgrading and/or redacting, which removes sensitive information from a medium to allow it to be shared more freely;

    • You'll learn about data de-identification and anonymisation, consisting of removing the personal elements of data to be able to use them without exposing PII (personally identifiable information);

    • You'll learn about the "compliance approach" to data ethics, consisting of treating ethics like a type of compliance the organisation must ensure, and how it enforces ethics;

    • You'll learn about actually implementing ethics in an organisation, with principles, governance structures and feedback loops, allowing transparency and iteration;

    • You'll learn about ethical data dimensions, which are just like the "vanilla" dimensions in DM, but specifically to measure ethics, such as Transparency, Fairness, Utility and others;

    • You'll learn about data processing purposes and authority, which consists of defining specific purposes for which data may be used (or not);


Remember that you always have a 30-day money-back guarantee, so there is no risk for you.

Also, I suggest you make use of the free preview videos to make sure the course really is a fit. I don't want you to waste your money.

If you think this course is a fit and can take your data quality knowledge to the next level... it would be a pleasure to have you as a student.

See you on the other side!


Data Literacy and Considerations

Module Intro
4 Key Principles
4 Key Principles Quiz
Data Disciplines
Data Disciplines Quiz
DG/DM Key Activities
DG/DM Key Activities Quiz
The Information Lifecycle
The Information Lifecycle Quiz
Projects to Processes
Projects to Processes Quiz
Sophistication Levels
Sophistication Levels Quiz
Module Outro

Data and Data Quality (DQ)

Module Intro
The 4 Types of Data
DQ Problems and Impact
DQ Management: Introduction
DQ Management: DQ Improvement
DQ Management: DQ Actions
DQ Management: Data Dimensions
DQ Management: Big Data and AI
DQ Tools/Techniques: Introduction
DQ Tools/Techniques: DQ Tool Overview
DQ Tools/Techniques: Data Profiling
DQ Tools/Techniques: Cleansing and Standardisation
DQ Tools/Techniques: Merging and Linking
DQ Tools/Techniques: Data Enhancement
Business Case Building
Module Outro


4x1 Data Management/Governance/Security/Ethics Masterclass - Screenshot_014x1 Data Management/Governance/Security/Ethics Masterclass - Screenshot_024x1 Data Management/Governance/Security/Ethics Masterclass - Screenshot_034x1 Data Management/Governance/Security/Ethics Masterclass - Screenshot_04


March 5, 2023
Hi Vasco, absolutely great course. One of the best, if not best udemy course so far. Clear, concise, well detailed. All the best. Dave
February 21, 2023
Not sure yet. I wish there was more hands on examples (possibly not the nature of courses like this).
February 6, 2023
This part gave me new look on Data Governance. It will help me to make people aware of it importance.
January 31, 2023
The modules are very repetitive and they ended up being boring. And some slides should be reviewed: the numbering is wrong and the lesson's titles are wrong, in some cases.
January 17, 2023
The course covers the great width of topics very well, however can be improved from a practical stand point of view. An end to end example of how someone executed data governance or management in a real world (case study) would have been extremely helpful. That too me is the biggest miss in what is otherwise a well researched effort. Also some of the modules towards the end seemed less relevant to a data generalist. The
January 15, 2023
Yes, indeed. Need to understand the key data principles for successful data projects. Implementation, sustaining and growing DG are important goals for success.
January 2, 2023
I like a lot how the course is organised (very well structured) and the quiz. I also like the fact that the teacher uses many practical examples.
December 5, 2022
Yes, thank you. Fluid instructor, speaks well, and the slides are profesional and pleasant to look at. There is some repetition here and there, but excelent course in general. very glad to do it!
November 15, 2022
Excellent match. Comprehensive course. Would recommend to all who need a thorough introduction to data
August 18, 2022
This is a truly fantastic course. It has given me an insight in various key aspects that are critical for not just initiating a DG program but also sustaining and expanding it's reach. The topics are very nicely sequenced and information provided is "to the point" without a lot of "overburdening" of information. I would strongly recommend this course for those keen to understand, learn and have the necessary wholistic information to drive a DG program towards success.
August 8, 2022
This was very helpful, highly granular and exhaustive, and very user friendly. Enjoyed it thoroughly.
August 2, 2022
I was recently tasked with driving a DG program for the organisation, so far this course has helped me define the scope and set up the foundation for the program.
July 12, 2022
It is absolutely 5 star course ! The content is very rich and and covers all aspects i need to know in Data. The instructor is very knowledgeable, he puts a lot of thought into how he presents the material. Very recommended course for people who are new in the Data world !
July 10, 2022
Assim como o curso Fundamentos do PCI DSS, seu treinamento merece 5 estrelas, Vasco! O treinamento é claro, didático e rico em informações e exemplos práticos, além de fornecer amplo material para posterior revisão e estudos. Com certeza vou procurar outros cursos disponibilizados por você, pois cada minuto, ou slide, vale o tempo investido! E para os alunos daqui do Brasil que tem dúvidas sobre a dificuldade de acompanhar os treinamentos por serem em inglês, podem ficar tranquilos porque a pronúncia é clara e fácil de acompanhar, mesmo sem o uso de legendas.
June 16, 2022
This course is worth WAY more than what Udemy is charging. The materials are really excellent and comprehensive. If you are looking to start or improve a data management program in your organization, this course will provide a solid foundation.


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