Best Practices Article Index

[JoeM]

Welcome

This best practices index provides an alternative solution to searching the community. Here, you can browse available knowledgebase articles by category. Some broad categories you can jump to are outlined in the table of contents here!

• Welcome
• Project Execution
• Maintaining and Expanding Incorta
• Monitoring and Hardening Your Environment
• Security and Governance
• Design for Performance
• Dashboarding
• Data Science and Machine Learning
• Schema Design and Data Modeling
• Business Schema Design

Project Execution

Most general software implementation project techniques apply to Incorta. Still, just as Incorta is a unique solution in the Unified Data Analytics Platform (UDAP) space, there are some specific things to be aware of when implementing Incorta. The articles in this section provide guidance to help you succeed with your Incorta projects.

• Preparing for Incorta
• What to focus on during implementation
• Most Common Implementation Challenges
• Testing
• End-User Adoption
• Tracking Adoption

Maintaining and Expanding Incorta

Once you start deriving value from Incorta, you will likely find more use cases where Incorta can help your business. Incorta is flexible enough to be used in many applications. As you continue and grow your usage of Incorta, you will want to ensure that Incorta stays in tip-top shape so that your users always have the experience they expect.

• Incorta Solution Topology
• Preparing for New Initiatives
• Managing Work Across Environments
• Upgrading
• Migrating Content Between Environments
• Maximizing Memory Available by Removing Unused Entities
• Migrating OBIEE Reporting to Incorta
• Customize the Look and Feel of Incorta with CSS
• Embedding Incorta Dashboards into your Favorite Application
• Using Playlists to Showcase Incorta Dashboards on a Monitor
• Maintaining Incorta Health Over Time

Monitoring and Hardening Your Environment

This section is organized to help Incorta implementers understand the final steps to ensure your Incorta environment is in prime production running condition. Please dive into the sub-sections below to explore these practices further. It is worth noting that some of these best practices are only applicable to customers with on-premises installations of Incorta. Many of these activities are handled for our Incorta Cloud customers.

• Backup and Restore Strategy
• Disaster Recovery
• Load Balancing/Distribution and High Availability Using Multiple Loader Services
• Log Rotation
• Inspector Tool
• Useful Scripts
• Monitoring
• Alerting

Security and Governance

Security in Incorta encompasses object (dashboards, schemas, et cetera) access, data access, and role permissions. Incorta provides the tools and integrations necessary for controlling what your users have access to, the level of permissions they have once logged into Incorta, and what data they can see. While Incorta provides native user authentication and authorization features, most organizations will benefit from integrating Incorta with their existing security tools to reduce administration time. The following articles will further detail the various Incorta features and touchpoints with other applications that together make up Incorta Security.

• SSO Best Practices
• Integrating with Active Directory
• Managing and Securing Content
• Sharing Incorta Objects
• Record Level Security
• Sharing Data and Content

Design for Performance

As you set up your Incorta topology and install Incorta, there are lots of levers you can pull to optimize the general performance of your Incorta clusters. Incorta product documentation can point you in the right direction for tuning your environments, but on top of that, it is well worth familiarizing yourself with some concepts that will help performance as you design your solutions.

• Dashboard Design for Performance
• Join Design Considerations
• Performance of Materialized Views (MVs)
• Formula Columns
• Near Real-Time Reporting
• As of Date Reporting
• Load Plans and Sequential Groups

Dashboarding

Getting your dashboards right so that they effectively communicate insight is vital. Explore the articles below for best practices for designing and building Incorta-based dashboards.

• Dashboard Design Principles
• Dashboard Design Best Practices
• Using the NEW Dashboard Free Form Layout
• Dashboarding with Other Visualization Tools
• Pivot Tables
• Advanced Maps
• Custom Map Shapes with Incorta
• Using Incorta Line Chart
• Dynamic Group-by and Dynamic Measures
• Incorta Mobile
• Other Considerations
  • Formulas
  • Displaying the last time data was refreshed
  • Variables
  • Export Dashboards and Dependencies
  • Drill Down within an Insight
  • Drilling Across Insights
  • Avoid Page Navigation When Scrolling
  • Using Playlists to Showcase Incorta Dashboards on a Monitor

Data Science and Machine Learning

Incorta caters to Data Scientists by providing lots of options for in-depth analysis. You can use the integrated Notebook editor to build models in the language or languages (PySpark, R, Scala, Spark SQL, and PostgreSQL) that you prefer. Incorta has also invested in Machine Learning and provides tools to make your life easier.

• Building Machine Learning Models using Materialized Views
• Install a Python Package in Incorta Cloud
• Getting started with Machine Learning in Incorta Guide
• Find and Fill Missing Data in an Incorta Notebook
• Preview Data in an Incorta Notebook
• Save a Spark ML Model
• Converting Data Types in an Incorta Notebook
• Split a Dataset into Training and Testing Data Sets
• Using a SparkR DataFrame for Selecting, Filtering, and Grouping your Data
• Saving a Pandas DataFrame as a Materialized View (Convert to Spark)
• How to handle Date Time in Spark MV
• Incorta Cloud with DataRobot GCP Batch Prediction API
• Using JDBC to Connect to Incorta SQL Interface from DataRobot
• Incorta On-premises with DataRobot Batch Prediction API
• Run SQL Queries from PySpark and Incorta Notebook
• Generate Profile Reports using Pandas Profiling package within Incorta Notebook
• Exploratory Data Analysis using SweetViz and Incorta Notebooks
• Share prediction results from AI/ML Platform with an Incorta On-Premise Deployment
• Incorta Third-Party AI/ML platform integration

Schema Design and Data Modeling

This section is organized to help Incorta practitioners understand the best practices when designing Incorta schemas and doing any necessary data engineering and data loading of those schemas. Please dive into the sub-sections below to explore these practices further.

• Connecting to Data
• Physical Schema Naming Conventions
• Designing your Physical Schema
• Data Engineering & Enrichment
• Data Load Strategy
• Load Plans and Sequential Groups
• Query physical schema data from PySpark using the incorta_sql() function
• Query business schema data from PySpark using the incorta_sql_pg() function
• Other Helpful Topics
  • Handling Deletes
  • Snapshotting Data
  • Handling Hierarchical Data
  • Date Dimension
  • Variables
  • Understanding Incorta SQLi

Business Schema Design

Defining Business Schemas in Incorta allows for a separation between the sometimes obscure naming conventions of your data sources and the business-friendly naming conventions in your company. Beyond that, they provide a level of abstraction that offers consistency to your business users even if you need to shift the physical data model definition. It is always a good idea to use business schemas/views when building your dashboard content, and there are some essential concepts to keep in mind as you design your business schemas.

• Understanding the Record Grain of Business Views
• Organizing Business Schemas
• Regular vs. Analyzer Views
• Business Schema Naming Conventions
• Using Formula Columns in Business Views
• Business Views for 3rd Party Visualization Tools