Launching EDITable: Create & Manage Reference/Meta Data in Power BI / Fabric / Snowflake & more

Join us for our launch webinar on EDITable, a pioneering no-code live writeback product that empowers business users to create and manage reference data, dimensions, and flat tables.

Highlights:

1. Create & manage reference/dimension data from Power BI (e.g., Customers, Regions, Products, GL Accounts etc.) inside your Destination Data Platform (Fabric, Snowflake and more)
2. Create & manage flat tables from Power BI (e.g., Price lists, contracts, campaigns, projects, subscriptions, discounts, claims, tickets, orders etc.) inside your destination Data Platform Tables
3. Designed for business users with no coding experience
4. Robust governance, audit & approval workflow
5. Create and maintain tables in destinations such as Snowflake, Redshift, Azure SQL, SQL Server, and PostgreSQL
6. Enhance your Power BI reports and planning applications

… and more

Webinar with LIVE DEMO:

The webinar will feature a 5-minute live demo where we will show you how to construct a new table in Fabric Data Warehouse and start maintaining it from Power BI.

We will also cover the following in detail during the rest of the live demo:

1. How business users can quickly create a Table inside Fabric data warehouse or other supported database destinations in minutes / migrate their data from Spreadsheets (Create)
2. Edit and maintain reference data and master tables already existing in the Fabric data warehouse (Maintain)
3. Explore the Bulk Edit/Bulk Insert capabilities that set EDITable apart from other solutions
4. How to set Approval workflow with conditions and rules
5. See how to set up and maintain Type 2 Slowly Changing Dimensions with Time Validity, beneficial for applications like Pricing Catalogs, Employee Salary Planning, & Contract Maintenance
6. Track every change with details on who, what, and when with our Audit capabilities
7. Add context to the changes through collaborative commenting
8. We will also share the architectural differences and use cases for the Inforiver Write-Back Matrix Vs EDITable