Category: ETL / ELT

Martin Schoombee brings back metadata tables:

The metadata that drives the execution within a framework is probably the most critical part. Going back to our analogy of building a house, the metadata would be the foundation. It is here where you are going to make some architectural decisions outside of which the framework cannot operate.

One such decision is how configurable or flexible you’d like the framework to be. In other words, how many attributes would you like to be dynamic and/or have the option to change during execution. It seems like an easy choice, and most engineers would lean towards “everything” or “as much as possible” as an answer. In reality however, the trade-off is complexity and the more dynamic you make the framework the more complicated it becomes. And you pay for the complexity later when you need to maintain or add new functionality to it.

Read on to see how it all fits together.

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Martin Schoombee begins a new series:

In the context of what we’re talking about throughout this series – facilitating the execution of an ETL process in a platform like Azure Data Factory – orchestration means that we’re using the ETL tool primarily for the “E” (Extract) part of the process. In addition to that, most people I know would also use the ETL tool to facilitate the workflow, in other words the order of execution and any constraints that go along with that.

In what I’d like to call the “traditional” approach for lack of a better term, all parts of the ETL process are performed natively by the tool (image below), using whatever built-in tasks are available and of course accounting for any nuances. With this approach, transformations are typically performed in transit and in memory.

Read on to see how the Orchestration approach differs from the traditional ETL approach.

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