Integration Incorta on-Premises Data Sharing with TAZI

OverviewSolutionAdd Incorta as a data source in TAZIUse the Incorta Table or Business View as the Input for a TAZI Business Model   Overview The Machine Learning platform TAZI can receive the data from Incorta and use this data for training the mode...

Integration of Incorta Cloud with TAZI AI Cloud

OverviewSolutionCreate GCS Data Source in TAZICreate the destination in TAZI to write to the shared GCS BucketLoad the data from GCS via the Incorta Data Lake Connector Overview This article discusses integrating Incorta Cloud with TAZI Cloud.     ...

Integration of Incorta and TAZI

What is TAZI?Deployment Scenarios   What is TAZI? TAZI is a machine learning platform that allows continuous learning and Auto-ML functionalities.  When it is used with Incorta, Incorta can be used for ingesting, integrating the data, and preparing ...

Use Markdown lines/comments within an Incorta Notebook

OverviewGetting StartedFormatting   Overview In this article, you'll learn some helpful tips to use Markdown within Incorta Notebook. Markdown helps you take notes, explain the logic, and insert links, tables, etc. in a notebook making your code more...

Getting Started with Spark SQL

IntroductionWhat you need to know before reading this articleStepsNavigationIncorta Notebook for SparkSQLAutocomplete for SparkSQLUse the DESC command to get the list of columnsUse Incorta Notebook Visualization   Introduction Incorta Materialized Vi...

A/B Testing Analysis with Incorta PySpark

OverviewWhat is A/B testing?Case StudyData SetTest HypothesesAnalysis in PySparkLoad the data into SparkClean up the dataCalculate the summary of controlled and treatment groupZTest PySpark UDFCall the PySpark UDFConvert the Resulted Array to DataFra...

Data Harmonization for Multi-Source

Introduction When creating visualizations based on multiple source systems, tables must be aligned to achieve a wholistic view of a business. For example, organizations that migrate from one ERP to another align invoice tables from each ERP to see al...

Incorta Cloud with DataRobot GCP Real-time Prediction API

Create an ODBC Connection to Incorta

Applies to: Any Incorta version On-Prem/Cloud Question: How to configure an ODBC connection?Unable to connect to Incorta using ODBC Overview: Any program that uses Open Database Connectivity (ODBC) to connect to a remote database needs a way to iden...

Multi-Source Table Design

Struggling to wrangle data from multiple sources? Learn about how and when to combine similar data points from disparate sources with three different approaches using the Incorta Platform.

Use Keyboard Shortcuts within an Incorta Notebook

IntroductionWhat you need to know before reading this articleLet's GoEnable Title of a ParagraphRun ParagraphRun All Above or All BelowMove Paragraph UpMove Paragraph DownInsert New Paragraph BelowDelete ParagraphParagraphLine NumbersClear OutputUndo...

Getting Started with Incorta Notebook

Introduction In this article you'll learn how to open the Incorta Notebook. The Incorta Notebook was designed for creating materialized views in Incorta. A materialized view is a physical schema that defines an Apache Spark job. The job consists of a...

Using JDBC to connect to Incorta SQL Interface from DataRobot

OverviewWhat you should know before reading this articleSolutionCreate New Project Select Data SourceCreate JDBC ConnectionBest PracticesOnly Share the Schemas RequiredCreate Business SchemasReuse and Share the Data across Multiple ML ProjectsReferen...

Designing your Physical Schema

This article covers key insights and considerations to consider before creating your first schema!

Physical Schema Naming Conventions

Before designing your physical schemas it is highly recommended to take the time to develop naming conventions. Learn about all the best practices here!