October 11, 2023

Bring Your Own Data to Databricks With Sigma Input Tables

Bring Your Own Data to Databricks With Sigma Input Tables

Bringing your workflows to your cloud data warehouse (and lakehouse) just got even easier. Our engineers at Sigma have been working hard to expand on our pioneering Input Tables functionality by providing expanded support for Databricks. This feature—unique to only Sigma—empowers users to create or update data by inputting information into tables and edit them like a spreadsheet live within cloud data platforms, including Databricks. Whether you are a financial analyst trying to run the latest model for the quarter or a data scientist prototyping advanced AI/ML models, Input Tables on Databricks are here to streamline your workflow.

What Are Input Tables?

Input Tables enable seamless spreadsheet-style write-back to data platforms like Databricks. We built Input Tables—a UI for all user types to create and manage their tables—to leverage cloud data platforms like Databricks and all the elastic compute and machine learning (ML) possibilities that come with these unique data platforms.

Drag and drop Input Tables into existing analysis, add columns, and edit values.

Input Tables allow you to add rows, configure data validation, and even enable auditing for user updates. This unique feature supports an endless variety of use cases like territory management, portfolio modeling, and revenue planning. More information on creating and managing Input Tables can be found here.

Why Databricks?

Databricks stands out due to its robust Artificial Intelligence (AI) and Machine Learning (ML) capabilities, appealing largely to a technical audience. With the integration of Sigma’s Input Tables, we're bridging the gap, enabling business users to also tap into the advanced functionalities that Databricks offers. Input Tables provide a familiar spreadsheet-like interface, making it simpler for business users to interact with complex models hosted on Databricks.

Sigma Input Tables perform write-back the way you always imagined.

Consider an automated forecast model developed within Databricks. Now, with Input Tables, business users can effortlessly provide last-minute updates based on their departmental insights, such as additional orders, enhancing the model's accuracy and relevance.

The integration of Input Tables on Databricks opens up new avenues for collaborative, real-time, and scalable data analytics, transcending the limitations of traditional desktop processes and fostering a more inclusive data-driven culture.

The business user contributes just-in-time data to the forecast model via an Input Table. 

Empowering Use Cases Beyond Excel Limits

Sigma has seen immediate success and adoption of Input Tables across financial services, health care, and retail verticals, among others. The ability to perform VaR modeling on top of diverse portfolio holdings data has particularly resonated with fintech analysts more familiar with spreadsheets than Python. Across all Input Table use cases, we routinely see the following results:

  1. Expanded Access: Provides prompts via Input Tables for users to interact with even the most complex ML models.
  2. End of Extracts: Keeps your data live, governed, and secure in your Cloud Data Platform.
  3. Cloud Scale Capabilities: Lets you truly leverage the power of cloud for use cases historically bottlenecked by desktop processes.

Get Started Now

Learn how to connect to Databricks and enable write access for Input Tables here.

Join Sigma at the Databricks Data+AI World Tour in NYC to learn how our latest product innovations are reshaping the future of analytics in the financial services industry.

Ready to jump into Sigma and check it out for yourself? Start exploring your data today.

Zack Norton
Technical Product Marketing Manager
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