Decoupling Advanced SQL Interface from Null Handling (2024.7.3 Update)
Learn about the implications of de-activating NULL handling for your analytics.
Learn about the implications of de-activating NULL handling for your analytics.
Never lose your Incorta Notebook work.
Learn tips and tricks for getting the most out of Load Plans!
We bet there is one thing in here you didn't know about working with notebooks in Incorta.
Use hash keys to simplify duplicate record identification.
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 ...
Your MV ran successfully in Incorta Notebook, but when you tried to validate and save the MV, it failed.
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...
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.
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...
Learn how the Data Agent allows you to connect data sources behind your firewall to the Incorta Cloud
Learn more about Data Engineering and Enrichment with Incorta.
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 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.