Integrated Data Analytics and Data Science
Incorta’s modern analytics makes data science ‘just work’ by tightly integrating big data processing and machine learning into the analytics data pipeline.
- Incorta bundles a preconfigured Spark cluster for running data enrichment tasks including machine learning, and for parallelizing operations such as data loading and data reduction.
- Complex operations can be easily scripted with integrated Python, Scala, R and SQL notebooks.
- An integrated machine learning library makes it easier to set up time-series predictions, outlier detection, classification, and many other models.
- Built in job scheduling makes it easy to orchestrate model retraining, predictions and monitoring.
- Easy to use data analysis and visualization tools provide data validation, insight discovery and presentation of findings.
By merging data management, analytics and data science into a single modern analytics platform, Incorta means more data science with less data wrangling.
Believe in your data from summary to detail
Original, full-fidelity data means the freedom to ask any question, traverse drill paths and hierarchies, perform root cause analysis, explore unlimited perspectives, and go from top-line KPIs to supporting transactional records in the blink of an eye.
From strategic decisions to root-cause analysis, everyone starts with the same dataset.
Unlike a data warehouse, Incorta maintains all of your data in its original form, providing you with an end-to-end view and a single source-of-truth for strategic and operational decision-making, data science and machine learning, and other computational workloads.
This means that with Incorta’s modern self-service analytics, you can analyze large amounts of raw business data in real-time without transformation, while also being able to drill into the details, ask any question, and even train machine learning models.