Data Validation Tips
How to validate data between a Incorta report and my legacy BI report.
Knowledge Base Articles
Modeling Schemas, Tables, and Joins
The purpose of this article is help users understand data modeling concepts and best practices in Incorta.
Date Dimension
Date is a common dimension used in most application deployments. It is primarily used to roll up data so it can be viewed across a broad time range, facilitating trend analysis.
Organizing Business Schemas
Introduction Business Schemas are a useful way to group content for business users that can be used in one or more dashboards. They also remove the need to understand all of the underlying data relationships even when they span several source data ...
Formula Columns
An expression can consist of built-in functions, built-in system variables, and other referenceable objects valid for the expression context.
Performance of Materialized Views (MV)
Introduction Incorta Materialized Views are a powerful way to enrich data contained in Incorta tables. Leveraging Spark's processing engine, Materialized Views (MVs) can be defined to introduce enrichments and advanced analytics to reshape your dat...
How to add a Custom Database Connection to Incorta
Setup to a connection a wide variety of connectors for SQL-based, Cloud-based, file system-based sources.
Build Machine Learning Models using Incorta Materialized Views
IntroductionIncorta Materialized Views (MV) provide a way to run PySpark, Scala, and Spark R and can be used for building machine learning (ML) models. We will discuss PySpark, Scala, and Spark R separately. Here are the best practices of using Incor...
Split a Dataset Into Training and Testing Data Sets
IntroductionWhat you should know before reading this articleApplied toLet's GoMulti-class classification data Introduction The train-test split procedure is used to evaluate the performance of machine learning (ML) algorithms. As part of data pre...
Convert Data Type in Incorta Notebook
As a part of data cleaning in Machine Learning, you may need to convert the data from one data type to the other data type. In this article, you will learn how to use Incorta Notebook to covert the data. After you read data in Incorta Notebook, you c...
Save Spark ML Model
Introduction Incorta supports the Machine Learning(ML) model creation process by using Incorta Materialized Views (MV). While you can put the logic of applying the ML model testing and actually use of the ML model for inference in the same MV, the ...
Preview Data in an Incorta Notebook
Preview Data in Incorta Notebook In this article, you will learn how to preview data in Incorta Notebook. Incorta notebook provide methods to let you preview data. using show(), head(), printSchema(), and describe(). incorta.show(df) incorta.hea...
