Prerequisite: Basic BI and data analysis knowledge
Once upon a time, corporate data was stored in internally controlled solutions for ERP, HR, or CRM and operated with daily loads of an enterprise data warehouse. That’s ancient history. Now data lives and flows in the cloud. We want it available in real time—or at least with minimal delay. Now we’re all familiar with Doug Laney’s Three Vs of big data: volume, variety, and velocity. Sometimes, Laney’s three are supplemented by a fourth V for value, but the most overlooked V of all is veracity. Without veracity, big data is just a pile of ones and zeros and value cannot be achieved. To assure veracity, data must be governed, just like any other asset in an organization.
However, with the advent of big data, it is not uncommon for business users and analysts to manage vast amounts of data. This makes it even harder to govern data and to ensure availability, correctness, and completeness.
All of which is becoming more relevant every day due to stricter privacy rules and government regulations,such as the EU’s General Data Protection Regulation(set to go into effect on May 25, 2018), which requires the hiring of a data protection officer among other new regulations.
You Will Learn
- What data governance means in a big data world, and what value it brings
- How to design a multilayered, multipurpose architecture to support data governance and comply with new regulations
- How emerging platforms like Apache Atlas and Ranger can be utilized in a corporate data governance framework
- Which techniques are available to monitor and improve the quality of your data
- BI managers and analysts, information and business analysts