Engineering at Meta
FEBRUARY 7, 2023
We’re Meta now, but our mission remains the same: Giving people the power to build community and bring the world closer together. In the fall of 2021, we launched a dark-mode variant to accompany our dark mode interface. We parsed OSM’s complicated building and building:part tags to refashion our building features from the ground up.
Monte Carlo
MAY 31, 2022
This article is sourced based on the interview between Lior Solomon, (now the former) VP of Engineering, Data, at Vimeo with the co-founders of Firebolt on their Data Engineering Show podcast which took place August 18, 2021. We have a couple of data warehouses with about a petabyte in Snowflake, 1.5
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Knowledge Hut
OCTOBER 4, 2023
Power BI has allowed me to contribute to various pragmatic projects across various domains, from data loading to visualization. I have read that the global data sphere will hold around 80zb of data in 2021. While the numbers are impressive (and a little intimidating), what would we do with the raw data without context?
Rockset
SEPTEMBER 20, 2022
This blog discusses some emerging use cases for real-time blockchain analytics and some key considerations for developers building dApps. Embedded content: [link] NFT and Crypto Price Analysis Although blockchain data is open for anyone to see, it can be difficult to make that on-chain data consumable for analysis.
Rockset
OCTOBER 6, 2022
Consequently, we needed a data backend with the following characteristics: Scale With ~50 commits per working day (and thus at least 50 pull request updates per day) and each commit running over one million tests, you can imagine the storage/computation required to upload and process all our data.
Towards Data Science
MARCH 9, 2023
Obviously, it runs on Apache Spark, which makes it the right choice when dealing with a big data context because of Spark’s properties of large-scale distributed computing. Databricks has a community edition hosted in AWS that is free and allows users to access one micro-cluster and build codes in Spark using Python or Scala.
Monte Carlo
MARCH 28, 2024
In a nutshell, DataOps engineers are responsible not only for designing and building data pipelines, but iterating on them via automation and collaboration as well. Former VP of Engineering at Vimeo, Lior Solomon, discussed one way by illustrating how the DataOps team works at Vimeo during the Data Engineering Show podcast.
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