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!

Business Schema Naming Standards

Similar to physical schemas, before designing your business schemas it is highly recommended to take the time to develop naming conventions if they are not already in place within your organization.

Variables

Read this article to review variable types in Incorta, when you use them, and best practices around using variables.

Incorta Data Agent

Learn how the Data Agent allows you to connect data sources behind your firewall to the Incorta Cloud

Incorta third-party AI/ML platform Integration

Overview Artificial intelligence(AI) and Machine learning(ML) are being applied to various industries.  It is very exciting that Incorta supports integration with third-party AI/ML platforms. When you use AI/ML platform you can leverage the data tha...

Incorta with DataRobot Prediction API Overview

OverviewCode for call to the prediction APILinks to articles that use the APIs under different scenarios   Overview This article is part of the series of articles for integrating Incorta with AI/ML platform. The assumptions are that you have created...