With data breaches in the news and legislation such as the GDPR, it’s a tough time to be looking at data governance. In particular, for business intelligence and analytics, the regulatory and social environment feels very restrictive. However, you can still do great work with analytics if you keep up with new technologies, build sound practices to support your teams, and don’t overreact to legislation.
To enable these best practices, in this course we will address these big challenges for business and IT:
- What is the GDPR and how does it affect your governance processes, even for non-European companies? Well look at the legislation with practical, non-scary advice.
- How are other regulations emerging around the world—including in the U.S., India, China, Australia, and Africa? We’ll explore the underlying trends in usage, legislation, and technologies that are currently emerging.
- What is the role of master data management, the data warehouse, the data lake, or the data catalog? You’ll learn the advantages and disadvantages of each of these platforms, along with helpful guidance on how to architect governance solutions around them.
- Are there new technologies available to help with these requirements? Yes, there are new technologies, tools, and platforms specifically designed for governance. We’ll review the main players.
- What about blockchain? Yes, it’s a hot topic, and we’ll demystify its role in data architectures, services, and governance.
- Can we still analyze customer data? If so, how do we protect privacy? We’ll review analytics practices from traditional BI to data science and AI with a focus on governance. In addition to privacy-protection techniques, we’ll look at methods for explaining algorithms and addressing bias in data and algorithms.
- Data architects and IT managers charged with supporting analytics with good governance.
- Business, analytics, and data management leaders who need a firm grounding in modern governance issues.