Knowledge Base Articles
Incorta Notebook Best Practices
We bet there is one thing in here you didn't know about working with notebooks in Incorta.
Use hash keys to compare two records in PySpark
Use hash keys to simplify duplicate record identification.
Query physical schema data from PySpark using the incorta_sql() function
Introduction The incorta_sql() function lets you directly query physical schema data in a PySpark MV without going through the old and cumbersome way. What you need to know before reading this article Previously, you could use spark.sql() to query ...
Incorta MV execution succeeds in the Incorta Notebook but fails to save
Your MV ran successfully in Incorta Notebook, but when you tried to validate and save the MV, it failed.
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...
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...
Incorta Data Agent
Learn how the Data Agent allows you to connect data sources behind your firewall to the Incorta Cloud
Handling Deletes
There are a number of strategies that can be implemented depending on the size of your data and whether the deleted records can be easily identified.
Join Design Considerations
Join definitions are what allow you to create the needed relationships between your data to guarantee you get the results that you expect on your Incorta dashboards.
