data warehousing data mining and olap alex berson pdf

Many categories of sensitive data require protection and regulatory compliance that include personally identifiable information (PII) and payment card information (PCI). Sensitive data of some types requires stronger protections than can be ensured by requiring independent data domains to adhere to enterprise data governance policies. Not all data is well-suited to domain data management. In this article, I’ll discuss four practices for thoughtful application of Data Mesh principles. Those principles, if thoughtfully applied, can ease the pain of data management without regressing to disorderly data silos. Two fundamental principles lie at the core of data mesh architecture-domain -managed data and sharing through data products. Jay Piscioneri emphasizes the risk when he says “ A half-hearted attempt at data mesh will produce a train wreck.”Ī few good architecture practices can help to realize the benefits while managing the risks. The reality lies somewhere between-a big shift in architecture thinking with a level of risk if poorly applied. Detractors view it as a dangerous trend and a backward slide to the chaos of data silos.

Proponents see it as revolutionary-the first new data architecture thinking in many years.

Good architecture practices help to reap the benefits with minimum risk.ĭata mesh gets a lot of discussion.

A Thoughtful Approach To Data Mesh - Audio BlogĪBSTRACT: Data Mesh raises hard questions-game-changing or high risk? Reality lies somewhere in between.

Data warehousing data mining and olap alex berson pdf