Data Culpa

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Data Culpa

Data Culpa

@DataCulpa

We make data observability fast and easy for any data pipeline, warehouse, or lake or file system. #dataobservability #dataengineering #dataquality

Boston Katılım Haziran 2019
309 Takip Edilen92 Takipçiler
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Data Culpa
Data Culpa@DataCulpa·
To monitor #dataquality effectively, you need to see how data is changing over time. That's usually more important than whether or not rigid unit tests are raising errors. Here's why: dataculpa.com/blog/effective…
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Jamin Ball
Jamin Ball@jaminball·
Seems to be 2 main headwinds in software currently: 1) new bookings slowing due to macro 2) Optimizations (everything from lowering AWS / Azure / GCP, Snow, DataDog, etc bills, to cutting / consolidating vendors) 1 will last until macro turns around. But how about 2?
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
Here are a few trends I am observing, from talking to a few people: - Optimize cloud spending bill: understand where things can be cut down, identify waste - Optimize logging provider spend. Basically: stop logging stuff that doesn't matter - Review pricing of eg pager systems
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Rugg
Rugg@rd_rugg·
Bad quality data is worse than no data: ML models will do wrong predictions. Dashboards will show wrong metrics. Still data quality, monitoring and observability are not treated as priorities in many companies. #DataScience
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Jordan Ellenberg
Jordan Ellenberg@JSEllenberg·
Explained in class today that delta means a small positive number you choose and epsilon means a small positive number your enemy chooses.
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SeattleDataGuy
SeattleDataGuy@SeattleDataGuy·
THEY'RE CALLED DATA CONTRACTS THEY'RE API-LIKE AGREEMENTS BETWEEN THE SOFTWARE ENGINEERS WHO OWN THE SERVICES AND THE DATA CONSUMERS THAT RELY ON THEM. IT'LL ALLOW THE SWES TO WORRY LESS ABOUT BREAKING PRODUCTION DATA PIPELINES AND HELP THE DATA TEAM MOVE AWAY FROM FIXING IN SQL
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