Unify and Automate Analytics From Data to Outcomes
Platform capabilities allow anyone to independently develop their own path to better decisions. Collectively, this improves analytics maturity and leads to higher value outcomes.
Extract / Load / Transform
With access to hundreds of data connectors, analysts and data engineers can quickly build pipelines that extract and load internal and external sources into targets such as Cloud data warehouses. Transforming data into a form suitable for analytics is just as easy.
Data Prep / Blend / Enrichment
Analysts, data engineers, and data scientists can speed raw data on its journey to insight through interactive preparation. This yields a visual representation that is sharable so others may accelerate their own use cases. Repetitive tasks can be automated.
Analytics / Reporting / Geospatial
Analytics automation supports many outcomes. Integrated or enriched data for enterprise applications or predictive models executed in a cloud data warehouse. Native geospatial insights or reports in BI tools like Tableau trigger actions in operational systems or RPA bots.
Data Science / AutoML / NLP
Artificial intelligence requires good data to produce accurate and reliable results. It also usually demands coding skills. Automated ML overcomes these hurdles by automatically creating features, predictive models, and explanations. Users can also add Python and R code into workflows and extract unstructured text data from PDF docs.
Auto Insight Generation & Exploration
Visual workflows can be rendered as Analytic Apps for anyone to self-serve insights. Analytics automation can also surface insights and anomalies from data automatically using artificial intelligence. All speed decision-making in ways not supported by traditional BI tools.
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