Data Governance

Data has value, normally measurable or otherwise estimable, as does the chain of data value. The risk of losing or corrupting this data is therefore real and can also be estimated. The management of these asset and so it is not only a technological phenomenon, but also Organisational and Standard. Data quality is of critical importance in all its aspects, including that of a single point of truth, meaning: if I have multiple versions of a piece of data, which one can I trust? The proliferation of applications within companies (including on different platforms and technologies) has led to the haphazard spread of databases that are more or less interconnected.
There is therefore a growing need to bring order, quality, and knowledge to the chaos of data, also in light of:

• New paradigms (Data Warehouse, Big Data, Open Data, Blockchain);
• Mergers o reorganisations business;
• Needs of Auditing and of Data certification (PCI, GDPR, 285, Solvency…);
• Data Architecture and Data Catalogue.

Data Governance is necessary to address these topics in order to track and coordinate the solutions proposed by various business specialists (Modeling, Quality, Security, Privacy etc.) within a business framework based on value and risk, but not bureaucracy. If Data Governance seems unsustainable, a Data Catalog project can be opted for, entirely bottom-up, starting from data discovery through to a reduced and agile governance process. The course examines these topics in light of international standards and defines the necessary stakeholders (from the CDO to Data Stewards etc.), architectures, and technological and organisational solutions for the formulation of the Programme of Data Governance.