Let's Make The World Data Driven

The quest for a single source of truth
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Every company, every business analyst, and every data scientist dreams of having one single source of truth for data. A place where anyone can go to find the information they need to make decisions. The problem with this dream is that it’s really difficult to achieve with the current toolkit. Data is stored in siloed warehouses, visualized in BI tools, and retrieved using complex code that often very few people at a company understand.

As a company grows, so does its data. The tables, visualizations, and reports often become isolated by the department and difficult to find. This means that as a company and its data scale, finding the right information becomes a difficult problem. 
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‍Institutional knowledge in data
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There is more data produced now than ever before. Even small companies with only 50 employees have hundreds of tables for the product, finance, customer support, and marketing teams. When companies experience this problem they traditionally invest in a data warehousing tool, a BI tool, and an ETL tool. The engineering or data team sets up these processes and become the broker of knowledge in the organization. 

Institutional knowledge is a problem faced by most teams but is especially painful in data. Data analysts and scientists spend countless hours trying to find the right stakeholder to ask about a particular table while getting bombarded with requests from managers. Tracking down and understanding siloed information slows decision making down and creates a culture that isn’t able to take full advantage of self-service tools. 

On top of this inefficiency, there’s concern about losing valuable tribal knowledge. Because the average tenure of a data scientist is around 18 months, many data scientists find themselves looking through old tables and trying to understand the mysteries behind the undocumented work. 

The result of all of this is a culture where employees are constantly raising questions to others and where there is a lack of trust in the information. These cultures fall into a cycle of having to create new, but duplicate data, which astronomically increases the already existing quantity. All in all, tribal knowledge, kept by a group of people, is counter-productive and unreliable. 

Secoda to the rescue

At Secoda, we view a data catalog as a feature within an organization’s data workspace. As we continue building the homepage for your data, we believe that to truly enable data discovery and adoption of data products, the data workspace must be easy for data teams to update and maintain while being just as easy to access and consume for business stakeholders.

Secoda is the place to search company data. We’ve built Secoda as a single place for all incoming data and metadata, a single source of truth. The goal of Secoda is to help employees find and understand the right information as quickly as possible. 
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Secoda doesn’t only add context to data, it goes beyond that. Secoda tracks the relationships between people and data to help you to visualize all the interactions between the different collaborators of the enterprise. This allows Secoda to identify who owns data, who is affected by changes, what tables are most commonly used together and the commonly used resources by team or individual. 

Our fascination with this tool came from seeing that companies like Lyft, Airbnb, Uber, and Shopify have built their internal tools to solve the problem. Although some of these tools are open source, they still require configuration and management that a company at our size wasn’t able to provide. 
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So we decided to build a software tool that can make data discovery accessible for companies of any size. Our goal is to help companies build data-driven culture from day one, and we believe that Secoda is the solution. 

Thanks for taking the time to stop by,
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The Secoda Team