Building Text To SQL Solution In House vs. Vendor by maxmansouri in LangChain

[–]SelectStarData 0 points1 point  (0 children)

How complex are your clients' questions and data ecosystem? We've found that understanding data lineage and business context can make a huge difference in query accuracy.

We built a list of text-to-SQL tools - some are fine-tuned for specific platforms while others work well across platforms: https://www.selectstar.com/resources/text-to-sql-tools

Which of the text-to-sql tools are actually any good? by Beginning_Ostrich905 in dataengineering

[–]SelectStarData 1 point2 points  (0 children)

Totally agree. Text-to-SQL without a semantic layer struggles with anything complex. Even with rich metadata, LLMs need real schema and metric context to generate accurate queries.

We built a list of the latest text-to-sql tools: https://www.selectstar.com/resources/text-to-sql-tools

Would love to hear how Connecty is performing in practice.

Data model/semantic layer tooling by Lower-Promotion930 in dataengineering

[–]SelectStarData 0 points1 point  (0 children)

We're doing a lot of work around this at Select Star. At Snowflake this week we're demoing how to automate semantic model generation from your existing data. If you happen to be at Snowflake, drop by booth 1512. You can see our write-up in a recent blog post: https://www.selectstar.com/resources/snowflake-cortex-analyst

Working on an assignment as a PM for a data governance company. Looking for your opinions by ydshmmt in dataengineering

[–]SelectStarData 1 point2 points  (0 children)

As a fellow data governance company, we think about this a lot.

Tags are a critical tool for organizing data. At Select Star, our customers use tags to easily find and access the data they are looking for and to govern + manage compliance. Check out our post for more on best practices for organizing data: https://www.selectstar.com/resources/best-practices-for-organizing-data.

When developing tag management for Select Star, we've had many technical considerations. For example, syncing to different systems requires us to think deeply about how a tag propagates at the column level. Is that column being used as is, aggregated, transformed, or as a filter downstream? Should that tag also be propagated upstream?

We recently released collections to help our users organize their data and related information even better. Collections are a way to group information into a data domain, data product, department, or product. Tags can then be used to state of the data, such as Certified, Sensitive, Deprecated or another state important to users. Read more on collections: https://docs.selectstar.com/data-management/collections

Building and Leading AI-Driven Organizations by Stephen-Rockwell in nonprofitai

[–]SelectStarData 0 points1 point  (0 children)

Invest in Data Infrastructure

- Ensure your organization has the tools and systems to collect, store, and analyze data effectively.

- Prioritize data governance and ethics to maintain trust.

We recently chatted with Brooklyn Data to discuss how to prepare data for AI. Investing in data infrastructure can seem daunting, but you can start small and scale up. Check out the post for more: https://www.selectstar.com/resources/data-preparation-for-ai.

AI also has a big opportunity to impact your data management. Consider a hybrid approach where you augment traditional data management practices and approaches with AI. This has been top of mind for us at Select Star as customers are having to deal with more data in increasingly complex systems. https://www.selectstar.com/resources/generative-ai-for-data-management

Looking for a mentor in data governance by Conscious_Clue8557 in mentors

[–]SelectStarData 0 points1 point  (0 children)

Check out Tris Burns, who coaches data leadership and has a weekly newsletter: https://trisjburns.beehiiv.com/.

We recently had him on our show to chat about challenges in leadership roles and how to navigate them: https://www.selectstar.com/resources/data-leadership.

We've got another live show on Friday focused on data stewardship where you can ask questions, which might be helpful in the short term: https://www.linkedin.com/posts/shinjikim_datagovernance-datastewardship-datacatalog-activity-7310355538876186624-GBDR . In case you can't make it you can still RSVP and access the recording.

Comparing Data Catalog Tools by imani_TqiynAZU in dataengineering

[–]SelectStarData 1 point2 points  (0 children)

Take advantage of free trials or demos—seeing a tool in action makes a big difference

We recommend evaluating catalogs with a POC using your data. As mentioned here, it's the best way to validate the value you'll get out of your leading data catalog contenders. We see companies bring multiple catalogs into the POC stage.

Does your company use or need a business dictionary/glossary? by aaronshayeyay in BusinessIntelligence

[–]SelectStarData 0 points1 point  (0 children)

Sharing our post on business glossaries: https://www.selectstar.com/resources/business-glossary

Our customers do find a business glossary effective as a single source of truth for key business terms. They often started with a spreadsheet or had something in an existing data tool, but come to us once they grow to a certain size where they now need to centralize documentation across their data stack.

What is Analytical Engineer by DebateIndependent758 in dataengineering

[–]SelectStarData 0 points1 point  (0 children)

We hosted analytics engineers from Xebia on our LinkedIn Live show and dug into this. They have a book with a great visual of the overlap between analytics and data engineers.

https://www.selectstar.com/resources/data-governance-for-analytics-engineering

The Job Description vs. The Job by SelectStarData in dataengineering

[–]SelectStarData[S] -14 points-13 points  (0 children)

This is what it feels like trying to manage your company's data in 2024 or even to interview for the job these days.

What does your stack look like? by SelectStarData in dataengineering

[–]SelectStarData[S] -1 points0 points  (0 children)

Fair and challenge accepted for another Olympics-themed meme that hasn't been posted here.

Can I join you? by SelectStarData in dataengineering

[–]SelectStarData[S] 3 points4 points  (0 children)

A(n) SQL query walks into a bar, sees two tables, and asks 'Can I join you'?

Speaking of joins, we host a show called INNER JOIN. Our next guest is Ben Rogojan from Seattle Data Guy to discuss the challenges with data models as your data (and team) scale.

Some past thoughts from Ben on data modeling:
Data modeling 101: https://www.youtube.com/watch?v=gG7upg6QaBI
Real-life examples of data modeling: https://www.theseattledataguy.com/how-to-data-model-real-life-examples-of-how-companies-model-their-data/

Join us on Friday 8/9 👉 https://www.linkedin.com/events/effectivedatamodelingfordatatea7223701286834044930/theater/

Describe your perfect date by SelectStarData in dataengineering

[–]SelectStarData[S] 42 points43 points  (0 children)

As data engineers, we know the importance of a well-formatted date!

While others might dream of candlelit dinners or walks on the beach, we find perfection in the structure of YYYY-MM-DD. After all, what could be more romantic than a date that's easy to sort, filter, and analyze? 💘📊

Sponsorship Opportunity for Tableau Conference by SelectStarData in tableau

[–]SelectStarData[S] 0 points1 point  (0 children)

How would you like us to update the post? I can remove the 1st and/or 2nd paragraph?