Platform capabilities allow anyone to independently develop their own path to better decisions. Collectively, this improves analytics maturity and leads to higher value outcomes.
Integrate multiple data sources into a single data store for analytics with hundreds of data connectors and transformations. Analysts and data engineers build data pipelines that extract and load internal and external sources into targets such as a cloud data warehouse or cloud data lake.
Analytics requires clean data to produce accurate and reliable results. Analysts, data engineers, and data scientists prepare and enrich data for trusted analysis.
Automate repetitive analytical tasks to scale insights. Enrich analysis with geospatial and location intelligence. Automated ML automatically creates features, predictive models, and explanations. Users can also add Python and R code into workflows and extract unstructured text data from PDF docs.
Build reports and integrate with BI tools such as Tableau. Visual workflows can be rendered as analytic apps for anyone to self-serve insights. Discover root causes automatically with AI generated insights and data storytelling.
