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Interesting startup idea: benchmarking cloud platform pricing

The Pragmatic Engineer

Benchmarking: for new server types identified – or ones that need an updated benchmark executed to avoid data becoming stale – those instances have a benchmark started on them. Results are stored in git and their database, together with benchmarking metadata. Then we wait for the actual data and/or final metadata (e.g.

Cloud 332
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How to get started with dbt

Christophe Blefari

In the ELT, the load is done before the transform part without any alteration of the data leaving the raw data ready to be transformed in the data warehouse. In a simple words dbt sits on top of your raw data to organise all your SQL queries that are defining your data assets.

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Data logs: The latest evolution in Meta’s access tools

Engineering at Meta

For each data logs table, we initiate a new worker task that fetches the relevant metadata describing how to correctly query the data. Once we know what to query for a specific table, we create a task for each partition that executes a job in Dataswarm (our data pipeline system).

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Strobelight: A profiling service built on open source technology

Engineering at Meta

Not only is this data looked at by individual engineers to understand what the hottest functions and call paths are, but this data is also fed into monitoring and testing tools to identify regressions; ideally before they hit production. Did someone say Metadata? To add to that enchilada (hungry yet?),

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5 Helpful Extract & Load Practices for High-Quality Raw Data

Meltano

Setting the Stage: We need E&L practices, because “copying raw data” is more complex than it sounds. For instance, how would you know which orders got “canceled”, an operation that usually takes place in the same data record and just “modifies” it in place. But not at the ingestion level.

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Databricks, Snowflake and the future

Christophe Blefari

Below a diagram describing what I think schematises data platforms: Data storage — you need to store data in an efficient manner, interoperable, from the fresh to the old one, with the metadata. It adds metadata, read, write and transactions that allow you to treat a Parquet file as a table.

Metadata 147
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Metadata: What Is It and Why it Matters

Ascend.io

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like.