Claude Dashboards Makes Charts Cheap And Definitions Expensive

Anthropic just made a live dashboard about as easy to generate as an answer in a chat window. Building the chart has been the most visible cost of self-service analytics, but Claude Dashboards now pushes that cost close to zero. But keeping that dashboard accurate carries a second cost. Someone still has to maintain the definitions, filters and table choices that determine what each number measures. I expect Claude Dashboards to make that upkeep a much bigger share of what analytics costs.

(Note: Of the companies mentioned in this article, Amazon and Salesforce are clients of my firm, Moor Insights & Strategy. Anthropic is not a client.)

What Claude Dashboards Does

Anthropic put Claude Dashboards into beta on its paid plans earlier this month. A user types a question in everyday language, and Claude pulls the data from a connected source and builds the dashboard. Anthropic lists Amazon Redshift, BigQuery, ClickHouse, Databricks, Snowflake and Salesforce among those sources. It says the dashboard keeps updating as the data changes.

I like that a click on any number in the dashboard shows the query that produced it. Seeing the query is one of the fastest ways for an analyst to double-check a chart before trusting it. Anthropic pitches Claude Dashboards for quick questions and says it’s meant to sit next to the business intelligence tools a company already runs. For anything more involved, a user can send the dashboard from Claude to a partner analytics tool such as Hex, Omni or Sigma. Any deeper analysis then happens in that tool, not in Claude.

Anthropic’s Own Data Team Found That Accuracy Requires Upkeep

More Dashboards Mean More Logic To Keep Straight

Is Selling Dashboards Still A Business?

Investors have sold off whole groups of stocks after Anthropic launches this year. Legal research, cybersecurity and design software companies each took a hit when Anthropic released a tool aimed at their kind of work. BI vendors could look like the next group in line.