This is your reminder to check in and say hi to your friends, family, work family, and loved ones. Remember that time is the one thing we don't get back, never take the people around you for granted.
Regardless of how sophisticated your data architecture is it should handle the following elements of the data lifecycle:
1. Data generation
2. Data ingestion
3. Data storage
4. Data transformation
5. Data serving
If this is the end of Twitter, we want to sincerely thank everyone for 10+ years of letting us help you find your lost hat, bantering with us about delays and our favorite --- sharing your bus operator shoutouts.
With Metrics Observability, Sifflet enables business users to discover and trust existing and new business KPIs and drive decision-making using reliable metrics. Curious to know how it works? Join CEO
Execs like the idea of "data as a product" because they want more productive data teams, and data teams like it because they don't want to work like a service desk.
All sounds good, but it's really hard to pull off!
Let’s look into the future of streaming data together
Join #TernaryData’s @doctorhousley and Joe Reis, co-authors of “The Fundamentals of Data Engineering,” for a discussion on how #dataengineering is changing, at #Redpanda Open House!
Register now https://rpnda.co/3SBfzwJ
Arendt proposed that a stable material culture anchors human identity. If so, what happens when the world of stuff becomes increasingly disposable and virtualized?
I'm fascinated by the pattern wherein data practitioners unite on a common theme (e.g. data mesh, semantic layer, data contracts), which they (at least occasionally) spend more time debating than implementing. I don't observe this in other developer communities.
RT @redpandadata: Learn Connect Accelerateat the #Redpanda Open House with keynotes @KelseyHightower, and Joe Reis and @doctorhousley (authors of best-selling Fundamentals of Data Engineering) and our own @emaxerrno! on Nov 15 8am - 1pm PT!
Regis…
Episode 1 of our Domain Expert Series is next Thursday! Check out our blog that dives deeper into the NIST framework and the topics we'll cover surrounding #datasecurity. Don't forget to register for episode 1! https://bit.ly/3QJ6KzK#webinar#cybersecurity#cybercontent#mdr
[NEW RELEASE] Data Quality Fundamentals -- Learn how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. https://oreil.ly/U7aOj#OReillyExperts
tonight and chatting about helping engineers be more empathetic towards each other and our users. Thanks to the GCP folks and Overstock for putting it on.
Boom! 3 must read books & authors on #TheDataChief guaranteed to boost your #data#analytics impact. @TimHarford@zhamakd@analyticsherohttps://tinyurl.com/2p94ctum
Thinking of bringing on data lineage?
My experience working with 100s of companies is that data lineage is useless by default until tied to a use case . Let me explain (🧵1/N)