data.world is a leading enterprise data catalog and governance platform that aims to democratize data access and champion inclusive, agile processes for data work. The company is a Public Benefit Corporation and a Certified B Corporation, prioritizing social and environmental performance alongside shareholder value. It is home to the world's largest collaborative open data community and offers a Data Catalog Platform built on a Knowledge Graph Architecture.

data.world

Catalog & Cocktails

data.world is the data catalog platform. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful knowledge graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has sixty-two patents and has been named one of Austin’s Best Places to Work seven years in a row.

Vopak

Alumni Ventures

OurCrowd

David Reuter

Richard Braddock

Stephen Pagliuca

Workday Ventures

Tech Pioneers Fund

Shasta Ventures

Prologis Ventures

Cotter Cunningham

Goldman Sachs Asset Management

Sandbox Insurtech Ventures

Dave Liu

Paul Albright

Scott Stephenson

Zachary Karabell

We're excited to announce an integration with Snowflake that brings new data quality metrics and measurement capabilities to enterprises. Say hello 👋 to data quality on-demand with the data.world Snowflake Collector.

When data trust is increasingly crucial to nearly every business - data quality becomes a vital component of the workflow.

Jeff Hollan, Director, Product Management at Snowflake, says: “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.”

Learn more:  https://lnkd.in/ejdJEd3n

On January 31, join our own Juan Sequeda, Principal Scientist & Head of data.world's AI Lab, along with Benn Stancil of ThoughtSpot and Joel Labes of dbt Labs for a live, in-depth discussion on data.world's groundbreaking benchmark study on the effectiveness of semantic layers on analytical accuracy of LLMs. Look forward to:

- The key findings of data.world's revolutionary research
- A behind-the-scenes look into additional tests conducted by Joel and the dbt Labs team
- A guide to the essential tools for constructing and managing your semantic layer and analysis
- Insights and opinions on the future direction in this space from the panelists

Don't miss out! Register now:
https://lnkd.in/ezdZ4vpw

Packed takeaways from the #HonestNoBS Dinner in Dallas: 

👍What’s working 
- Each silo does work
- Data immature company, start w/ data warehouse 
- Capture semantics of concepts at a granular level. Let people ask questions using granular concepts
- If you say you are treating data as a product, put your money where you mouth is. 
- Be practical. Don’t force things on people
- Find example of a loss in the business where there was a lack of data ownership 
- Tlk to different Business Unit leaders & ask for their pain points
- Showcase the silos that are being successful & how they are doing it 
- Lunch&learn where BU share what they’ve done & the value they had with data 
- Hackathons involving business & data teams
- Putting AI on every slide :) but at the same time not talking about AI. Just DO IT & talk about the problem 
- GenAI to help “taking care of data” (i.e. metadata)
- Use AI to access good data… but you need to make sure your data is good 
- Stop investing in reporting building. Rather invest in semantics, metadata, knowledge graphs. And then put AI on that 
- Governance for regulation is working. Otherwise, kinda
- Marketing your data. Combination of data provides innovation (and new revenue opportunities)
- Define the critical data elements. That’s what you will govern & focus data quality on. Generates the most value & eyeballs
- DG framework: 1) executive committee that provides direction 2) Working group (VP level) which says which critical data elements 3) Data stewards who do the work. 
- Doing data products without knowing that we are doing it. Not being pedantic. 

👎What’s not working
- Each silo does work. But not working together
- Culture change
- Sense of attachment of the reports you have built
- We should kill “building reports”, make sure that the data is understandable by everyone. Report is just a UI for data 
- Too much power to the folks building reports, not the shining light on the data teams building 
- If you don’t ask the question to the report team in the right way, it’s like ChatGPT it will hallucinate 
- Lack of report governance. Disparate report building
- Lack of consistency & standardization. Same metric, different number. No alignment on terminology. Texas is TX, TEXAS, TEX. 
- Incentivized to run depts in their own way. But not be able to report at the enterprise level 
- Resistance to data ownership. Because the person is the owner. The ones responsible for the process should be accountable. 
- Pay attention to AI but don’t put all your investments in it. Don’t take it as gospel
- Vendors promising to solve tech problems that they can’t & also solving culture/people/process problem 
- Build it & they will come
- CDO are sitting at the kids table

👥 Where does data report to? 
- Moves all over the place (COO, CIO, CFO) because they don’t know what the CDO does and not one wants to own data.
- CIO->COO->CEO
- CTO->CIO->CEO
- CFO->CEO

😎 Where should data ideally report to? COO or CFO. Never CIO 


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