The search algorithm today is honestly the easier part of the puzzle, having been commoditized by ecosystems like Elasticsearch and SaaS products like Algolia.
The real challenge lies in building relevancy into data discovery (View Highlight)
The very reality of data science and analytics lies at the intersection of technology and business. No data team can be successful without human-led context about business, users, and entities (View Highlight)
This is when we realized that, when it comes to data, creating shared context is a team sport.
Why? No one person ever has full context about data. Some context is business-focused, so only the business analyst or stakeholder knows it. Some context is technical, known by the data engineer. And some context is buried deep in the data, like weird anomalies in a column, known by the data analyst. (View Highlight)
