Data Architecture

Designing For Data Protection - Episode 106

The practice of data management is one that requires technical acumen, but there are also many policy and regulatory issues that inform and influence the design of our systems. With the introduction of legal frameworks such as the EU GDPR and California’s CCPA it is necessary to consider how to implement data protectino and data privacy principles in the technical and policy controls that govern our data platforms. In this episode Karen Heaton and Mark Sherwood-Edwards share their experience and expertise in helping organizations achieve compliance. Even if you aren’t subject to specific rules regarding data protection it is definitely worth listening to get an overview of what you should be thinking about while building and running data pipelines.

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Data Orchestration For Hybrid Cloud Analytics - Episode 103

The scale and complexity of the systems that we build to satisfy business requirements is increasing as the available tools become more sophisticated. In order to bridge the gap between legacy infrastructure and evolving use cases it is necessary to create a unifying set of components. In this episode Dipti Borkar explains how the emerging category of data orchestration tools fills this need, some of the existing projects that fit in this space, and some of the ways that they can work together to simplify projects such as cloud migration and hybrid cloud environments. It is always useful to get a broad view of new trends in the industry and this was a helpful perspective on the need to provide mechanisms to decouple physical storage from computing capacity.

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Straining Your Data Lake Through A Data Mesh - Episode 90

The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access. In this episode Zhamak Dehghani shares an alternative approach in the form of a data mesh. Rather than connecting all of your data flows to one destination, empower your individual business units to create data products that can be consumed by other teams. This was an interesting exploration of a different way to think about the relationship between how your data is produced, how it is used, and how to build a technical platform that supports the organizational needs of your business.

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