MDM Academy lessons and materials are in Portuguese. You can take the program from any country, and an English version is on our roadmap, with no committed date. The certificate is issued in Brazil, in Portuguese, and is valid in Brazil. To earn it you need to follow the lessons in Portuguese.
Practical articles on quality, master data, LGPD, tools and career. No loose theory: what works in real data programs.
111 articles published · new every week
featured
Completeness, uniqueness, validity, consistency, accuracy and timeliness: how to measure each one without depending on an expensive tool.
Operational MDM vs analytical MDM: understand the differences, see practical examples from procurement and SAP, and find the right model for your master data.
Data governance analyst: what they do day to day, the tools they use, how to get certified, and how much they can earn.
Business glossary: what it is, how it differs from a data dictionary, and how to build one to align purchasing, sales and finance.
NCM in the material master: understand why the wrong tax classification leads to fines, import delays and lost tax credits.
Master data in mergers and acquisitions: how to diagnose, unify and cleanse customer, supplier and material masters after the deal closes.
ESG and master data: understand why the sustainability report fails without data governance and a reliable supplier master.
Customer master data: what it is, how to organize the customer master across CRM and ERP, MDM tools, and how to avoid errors in sales and collections.
MDM consultant: what they do day to day, which tools they use, how to become one, and how much you can earn in this growing market.
International data transfer: what Brazil's LGPD says, when it requires contractual clauses, and how to prepare master records to operate abroad.
ISO 8000 is the international master data quality standard: what it defines, how it works, and why it shapes material, supplier and customer masters.
LGPD fines: understand the amounts, how the ANPD calculates the penalty and why master data governance prevents the problem.
Supplier master data: what it is, how it works in the ERP and why it underpins procurement, vendor approval and compliance.
HR master data is the record that underpins payroll, eSocial and people management. Learn what it is and how it works.
Data governance operating model: understand the differences between centralized, federated and hybrid and how to choose the right one for your master data.
Financial master data: what the chart of accounts, cost center and profit center are, who looks after them and why they decide the accounting close.
A CDP (Customer Data Platform) centralizes customer behavior data for marketing. Learn what it is and how it differs from MDM.
Survivorship in MDM: understand the survivorship rules that decide which value wins when duplicates are merged into the master record.
Data ontology: what it is, how it differs from taxonomy and metadata, and why it underpins MDM, master data and AI projects in companies.
Master data interoperability: what it is, how it works across ERP, CRM and e-commerce, and why it decides whether your master records get duplicated.
Master data workflow: understand the approval flow for material, customer, and supplier records, from the request to publication in the ERP.
Asset master data: what it is, how to organize the equipment master record in SAP PM, and why it decides industrial maintenance.
Data processing agents: understand who the controller, processor, and DPO are under the LGPD and how this shows up in master record governance.
Cloud MDM: what it is, how it works, and why the SaaS master data platform lowers the infrastructure barrier to governance.
Transactional data is the day-to-day record, like orders and invoices. Learn how it differs from master data and why that stalls data and AI projects.
Data architect: what they do, how the role differs from a data engineer, tools, salary in Brazil, and how to become one.
LGPD
MDM Academy's LGPD and data compliance course: legal bases, data subject rights, inventory, and data governance in practice.
MDM Academy's SQL and Python for data course: queries, automation, and hands-on investigation of your own database.
Career
MDM Academy's data steward training: matching, deduplication, data quality, and a career path in practice.
Tools
MDM Academy's SAP course for material master: taxonomy, NCM, standardization and preparation for the S/4HANA migration.
Governance
MDM Academy's data governance certification: content aligned with the DAMA DMBOK to organize and validate your knowledge.
Quality
MDM Academy's data quality course: dimensions, data profiling, deduplication and a data cleansing plan in practice.
Governance
MDM Academy's data governance course: pillars, roles, RACI, indicators and how to apply it in practice at your company.
Master data
MDM Academy's MDM and master data course: domains, golden record, matching and integration with SAP, TOTVS and Oracle.
Data matching: what it is, how it works in MDM, the tools on the market and why it decides whether two records are the same entity.
Master data diagnosis: the signs that your customer, supplier and material base needs data cleansing.
RACI in data governance is the matrix that defines who decides, executes, is consulted and is informed about each master data item.
Data governance indicators: which KPIs show whether your MDM program works, and how to measure duplication, completeness and accuracy.
Data subject rights under the LGPD: what the law guarantees and how companies respond to access, correction and deletion requests.
Master data for AI: why autonomous agents fail with poor master records and how to prepare customers, suppliers and materials for AI.
Multi-domain MDM: what it is, how it works and why managing customers, suppliers and materials together changes data governance.
Data enrichment: what it is, how it works in practice and why incomplete supplier and customer master records stall decisions.
Data security: what it is, the difference from privacy and governance, and how to protect customer, supplier and material master data.
A data product is data treated as a product, with an owner, quality and standardized access. Understand the concept and how to apply it.
The RIPD is the LGPD's Personal Data Protection Impact Report. Learn what it is, when it is mandatory and how to prepare it.
Shadow AI: what it is, the risks to master data and the LGPD, and how to structure governance to reduce that risk.
LGPD legal bases: learn the 10 grounds in Article 7, when to use each one, and why consent is almost never the right basis for companies.
Data scientist: what they do, how much they earn in 2026, skills, tools, how to become one, and why data governance sets professionals apart.
Data mining: what it is, how it works, techniques, tools, and why it only creates value with data governance and quality behind it.
Business Intelligence (BI) turns data into decisions. Learn what it is, what it is for, the tools, and why it depends on data governance.
Data analyst: what they do, how much they earn in 2026, tools, how to become one, and why data governance sets professionals apart in the market.
Data engineer: what they do, how much they earn in 2026, and how to become one. The full guide to the most in-demand data career, and why governance matters.
Data governance tools: what they are, what they do, the main ones (Collibra, Purview, SAP MDG), and how to pick the right one without buying the vendor pitch.
Big Data: what it is, the 5 Vs (volume, velocity, variety, veracity, value), the market's tools, and why without data governance it is just a cost.
Data steward: what this data governance professional does, how much they earn, how to become one, and which MDM tools they use day to day.
Data governance policy: what it is, what it should include, and how to create one. A guide to roles, quality rules, tools, and LGPD.
Data classification: what it is, the levels (public, internal, restricted, and confidential), and how to classify company information and comply with the LGPD.
ETL is the process that extracts, transforms, and loads data between systems. Learn how it works, the difference from ELT, the tools, and the link to master data.
Data warehouse, data lake, and data lakehouse: what they are, the differences in practice, and why data architecture can't fix bad data without governance.
Data dictionary: what it is, what it is for, what it contains, and how to create one, with a practical example and the difference from the data catalog and metadata.
Data modeling: what it is, the conceptual, logical, and physical models, how it works in practice, the tools, and the link to governance and master data.
Data protection officer (DPO): what a DPO does under the LGPD, how much they earn, how to become one, and why data governance underpins protection.
Data contracts: what they are, how they work, who is responsible, and why they ensure data quality and trust for the business and for AI.
Data anonymization: what it is, how it works, the main techniques, and the difference from pseudonymization under the LGPD, with practical corporate examples.
Data fabric: what it is, how it works, and how it differs from data mesh. Understand the architecture that connects distributed data and where governance fits in.
Data observability means knowing the database broke before the wrong report lands. Learn what it is, the five pillars, tools, and who owns it.
Learn the four MDM implementation styles (registry, consolidation, coexistence, and centralized) and how to choose the right master data architecture.
CDMP certification: what DAMA's data management credential is, the Associate, Practitioner, and Master levels, what it costs, and how to get certified.
Data profiling is the analysis that reveals how your database really is. See what it is, what it's for, which tools to use, and how to apply it in practice.
Reference data: what it is, how it differs from master data, who owns it, RDM tools, and why governing it prevents integration errors.
PIM (Product Information Management) is product information management: what it is, how it works, tools, how it differs from MDM, and careers.
Data lineage is the map of where data is born, where it goes, and how it changes. Learn what it is, what it's for, and how to use it in governance.
What a Chief Data Officer (CDO) does, what they earn, and how to become one. The role, tools, DAMA certification, and the data career market.
Metadata is the data that describes other data. Learn what it is, the types, who owns it, and why it underpins data governance in your company.
Data mesh: what it is, how it works and why this domain-based data architecture does not replace master data governance.
Data culture: learn what it is, how to build it in practice, who is responsible and why AI only works when the company takes care of its data.
Data catalog: what it is, what it is for and how it organizes metadata and helps governance find the right, trusted data in the company.
Single customer view (Customer 360): how to unify duplicate customer records into one trusted record to make better decisions.
Data migration to SAP S/4HANA exposes the quality of master data. Learn why cleansing data before loading decides the project's success.
Learn what data governance is, the role of master data (MDM) and how to start in one of the most sought-after data fields in Brazil.
Understand what Master Data Management (MDM) is, how master data management works and why it is the foundation for procurement, AI and reliable decisions.
Data governance is the set of policy, roles, processes and technology that lets a company trust its own data. Learn the pillars and how to get started.
Master data is the core customer, supplier and material information reused across operations. Learn what it is and how it affects the business.
Data quality goes beyond being correct. Learn the dimensions (completeness, uniqueness, consistency, accuracy, timeliness) and how to measure trustworthy data.
Learn the pillars of data governance (people, processes, policies, technology and quality) and why none of them works alone.
Duplicates are almost never a typing error. They come from a missing key field, a missing approval flow and a missing domain owner.
A realistic step-by-step guide to implementing data governance: diagnosis, priority domain, roles, standards, process, technology and measurement.
DAMA-DMBOK is the world's leading data management framework. Learn its knowledge areas and how to apply them without becoming a hostage to theory.
A good material master reduces duplicates, improves purchasing and unblocks inventory. See how to standardize description, classification and technical attributes.
A step-by-step guide to mapping processing, legal basis and retention without stalling operations for weeks.
Material taxonomy organizes the material master into families and categories so purchasing, inventory and maintenance speak the same language. See how.
Data cleansing fixes duplicates, standardizes, and completes records. But without governance at entry, the base gets dirty again. See how to do it right.
Career
The shortest path for someone who already lives the problem from the inside: method, vocabulary, and proof of work.
Duplicate records inflate inventory, split purchasing power, and distort reports. Understand the causes of data duplication and how to prevent it for good.
Supplier qualification without clear criteria becomes a risk. See how well-managed supplier data supports qualification, compliance, and negotiation.
Five queries that cover 80% of a governance analyst's daily checks, explained line by line.
A golden record is the single, trusted record of each entity. Understand what it is, how it relates to the single source of truth, and why it matters.
Data owner and data steward are the roles that hold up data governance. Understand the difference, the responsibilities, and why nothing works without them.
Why most committees die by the third meeting, and the meeting format that survives a change of manager.
Enterprise AI doesn't fix bad data by magic; it speeds up wrong decisions. See why data governance is the foundation for AI to actually work.
LGPD requires knowing where personal data is, who accesses it, and why. See how data governance is the practical foundation for compliance.
Data governance maturity shows what stage your company is at and where to evolve. Learn the levels and how to advance without skipping steps.
The math that gets budget approved isn't technical. It's measured loss, expected gain, and a one-page defense.
SAP MDG is SAP's master data governance solution. Learn what it is, how it works, and why the tool only delivers value with governance behind it.
A wrong NCM in the material master creates tax risk and taxes paid incorrectly. See how data governance supports tax compliance.
Master data
How to build a description standard your operation can actually follow, with real examples from industry.
Data governance and MDM open doors in technology and business. See the skills, entry paths, and how to specialize in a growing field.
The criteria that separate a nice demo from a solution that can handle your volume and your rules.
Three questions that reveal whether there is a real data program or just a job with a nice title.
Roles, formal accountability, and the day-to-day difference between controller, processor, and data protection officer.
Deterministic rules, fuzzy matching, and the exact point where the decision goes back to the owning area.
WhatsApp group with daily technical content, governance and MDM job openings, webinars and masterclasses. Free entry, no sign-up.
An interactive guide to the Brazilian data management and governance market: fifteen roles, salary ranges with sources, a twelve-month roadmap and an assessment that points to your entry track.
free class
See the method from the inside: how a quality rule is born, measured and becomes routine in operations.
Get the free class→A few questions about your professional background and goal, and a recommendation of the track that makes sense for you.
Take the profile quiz→