Streamlined data discovery powered by AI + Knowledge Graph for reliable

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In the era of AI, nearly every vendor in the market will have their AI narrative. When it comes to data catalogs, the focus is on using AI to enable data analysts to ask questions in everyday business language. For example, they can simply ask, “Find me all the data that is related to Sales activities to calculate total revenue in 2023”. The problem with a typical data catalog tool that has a simple integration of AI is that it could yield inaccurate results. Without a context-aware knowledge graph, the AI won't know whether “2023” refers to fiscal or calendar year and which months of sales data should be incorporated into the “Total Revenue” report. Now, picture your data analysts building business reports using incorrect data for your C-Suite’s crucial decision-making - such a scenario could lead to catastrophic outcomes.

Here's the deal: AI alone is not enough to produce accurate and trustworthy results, especially when dealing with proprietary enterprise data for answering complex business questions. AI needs to be paired with a Knowledge Graph data catalog to provide context, and validate the response based on the “facts” stored within the graph. This is precisely what sets data.world’s Archie apart from the rest. Archie is an intelligent bot powered by Generative AI to help improve data accessibility and improved search results. If you are curious about why a knowledge graph data catalog and Generative AI goes hand in hand, check out this webinar titled WTF is a Knowledge Graph and Why is it Key to AI.

When paired with Sigma, data analysts can now effortlessly find and access the relevant data in plain English. They can then query, visualize, and interact with the live data to perform calculations and scenario modeling, as well as drag and drop various data elements to design their dashboard to gain additional insights. By combining the two solutions, data analysts gain confidence in their analysis, while business owners can trust the information to make critical decisions that shape the future of their company!

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3. Building trust through visibility and transparency, all while enjoying the speed & flexibility of Sigma’s Excel-like user experience

Every client I speak with praises how incredibly user-friendly Sigma is. You can dive right in without any training, just as if you were working on an Excel sheet, with the ability to scale to handle billions of rows. Not only can users work on data stored in the cloud data warehouse live, they also can integrate it with external sources to perform what-if analyses and scenario modeling. While flexibility sometimes involves trade-offs with governance and security, this doesn’t have to be the case.

To build trust among data teams, Sigma partners with data.world to bring full visibility and transparency to the entire data ecosystem journey. Metadata and lineage information, such as germany whatsapp number data Workbook, Data Element, Tag, User, and many more from Sigma, are natively integrated into data.world’s knowledge graph. This allows data analysts to see the full story behind Sigma's Workbooks, finding answers to questions such as which data was used to build this dashboard, the origin of the data sources, and who has access to and owns it - all with just a few clicks.

Below diagram illustrates the use of data.world’s Eureka lineage graph to explore the end-to-end data flows, giving insights into how data flows between systems and transformation, before it is consumed in the Sigma dashboard. This visualization also provides further clarity on how Sigma’s various data elements relate to the broader data ecosystem, providing users with valuable end-to-end visibility.

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Final Thoughts!

In summary, trust is the cornerstone for enterprises to foster a data-driven culture. Data teams require an open, transparent, and collaborative communication environment along with well-documented data assets for effective analysis. This is precisely what the integration between data.world and Sigma brings to our customers.

Last but not least, we believe that trust and flexibility can coexist through robust yet agile data governance programs. Governance need not be overly restrictive, instead, it should provide tools that empower data teams to work more efficiently while ensuring a safe environment. The two companies share this vision and are committed to continuing collaboration to push the boundaries of what is possible to meet our customers' modern data needs. Our goal is to create products that everyone loves and uses.