Data News - May

Hey there,

It's with a blend of nostalgia and excitement that I announce to you that this is the last incarnation of our beloved newsletter in its present form.

From June onwards, Castor will have a brand new identity. I wish I could tell you more. But my lips have to be sealed until June. The only clue I can give:?June 6th will be a big day for Castor . Keeps your eyes open! Until then, let’s enjoy business as usual.

In this edition you’ll find:

• One?data?tool?that we believe is worth digging into as a?data?person. We will also provide where it fits in the?data?ecosystem.
• A selection of the?most delightful articles?we read this month along with a quick teaser.
• Show and Tell:?Three great pieces of news from the Castor team.
• The?data?person?you should follow right now if you don't already because he/she writes interesting content.
• A?data meme?to make you smile.

Data?Tool

This month, we decided to put the spotlight on?Hex . Hex is a data collaboration platform allowing data teams to analyze data, create visualizations and share insights with their team. It’s interesting to talk about Hex, because this company started as a SQL notebook, and has evolved into a data collaboration platform, a sort of “data workspace”.

Does Hex represent the future of SQL notebooks? When I originally wrote a piece about?SQL notebooks ?2 years ago, I noted that third-generation notebooks were collaborative by design, with a built-in visualization layer. In my opinion, Hex has taken the whole category a step further, which is why I changed its place on the landscape. But if you think Hex has simply left the “SQL notebook” category, I wouldn’t dispute that either.

Another thing I like about Hex is that they were pioneers in integrating AI in their product by providing a built-in AI assistant that helps you generate, debug, and explain your code. For all these reasons; I think Hex is a great tool worth checking out. If you’re interested in a full landscape of SQL notebooks, read?this.

Data?News

• The Next Big Crisis for Data Teams .?You have probably read this article already, because it made a lot of noise in the data ecosystem. In this piece, Barr Moses says a lot of relevant stuff. Data teams have received a lot of investment in the past, without having/ being able to justify ROI. Given the macro-economic context, data teams now have to pay the bill. Prove their value. Justify the investment. The only way out is for them to get closer to the business. The idea is not revolutionary, but Barr gives some good tips for putting this in practice. It’s also the vision we have at Castor, and we’ll keep building a product that allows data to flow to business units.

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• Crafting Your Data Team . Do not look for years of experience when hiring a data team leader and data team members. The more experience they have, the more detrimental it could be for your organization. Why? Because things become obsolete very quickly in the data world, and hiring people who use old techniques can cost you a lot. This an original idea from?Marc Stone ’s piece on building data teams. You will find lots of other great tips on how to hire a good data leader and the rest of your data team.

• Learning: The Meta-Skill for Accelerating Impact .?Do you know how to learn? it’s probably the most important thing in the workplace, and in life in general. This piece by?Caitlin Moorman ?focuses on the skills that enable data practitioners to have high impact: knowing what you don’t know, asking effective questions, growing technical skills, and teaching others. It’s a very practical piece that will help you understand what these skills look like when they are underdeveloped, how to develop them, and what success looks like. This article targets data practitioners, but in my opinion it is useful for any role.

Show?and?Tell?

• In my most recent piece, I discussed?data domains ?- a potentially confusing concept. Simply put, they're a grouping mechanism for data, that help teams locate, own, and understand it. However, they're not necessary until your organization reaches a certain level complexity. Instead, organizing data by?teams?and?sources?effectively does most of the job. At a certain complexity threshold, data domains might be beneficial - but you’ll have to read the full article to find out when.

• Sync back across your stack . This is our star feature of the month! We’ve announced that Sync Back now supports early access for Snowflake, Bigquery, Tableau, and Looker in addition to dbt. What does that mean for you? If you're working in Looker, Castor will push back the documentation right in there, so you don't have to switch tools to check a definition. This feature is part of our effort to let documentation flow across the whole stack.?Get in touch ?if you want to check it out.

• In terms of events, we also have something in store for you! Snowflake summit is just a month away, and we are organizing a dinner with our friends at Census, Airbyte and LaunchDarkly. If you are coming to the summit, you should sign up for sure.?Here ?is where you can do it.

Data?Person

Our favorite data person this month is?Marie Lefevre . Marie writes on?medium , sharing tips and lessons she learns along her Data Science Journey. It’s always a pleasure to read her work.?

Data?Meme

Are you still documenting data using a wiki page? If so, it might be time to upgrade from this and try Castor.?

Until next time,

?? Louise from Castor ??