November 9, 2022

Building Data Products Faster with Sigma & Fivetran

Nate Meinzer
Manager, Partner Engineering
Building Data Products Faster with Sigma & Fivetran

Sigma maximizes the value of your Fivetran connectors to derive insights from your data models.

As organizations embrace the Modern Data Stack, many choose Fivetran to do the heavy lifting of building and maintaining cloud data pipelines. Fivetran’s robust, easy-to-use connectors keep fresh, real-time data flowing into your cloud data warehouse with a fully managed solution. 

But onboarding data into a cloud data warehouse is just the first step in building a value-driven data product. If the end user doesn’t know how to use SQL or relies on a legacy BI tool that can’t scale to meet modern workloads, then they must wait for the data team to curate, model, and design analytics solutions for them. With this bottleneck, it’s no wonder only 20% of analytics solutions will deliver business outcomes.

Named Fivetran’s 2022 Business Intelligence Partner of the Year, Sigma delivers on the promise of self-service, collaborative analytics, and business intelligence. With its intuitive spreadsheet interface, anyone can begin creating spreadsheets and dashboards with no code and unmatchable scale. Sigma allows users to access, model, and derive insights from newly ingested application data once Fivetran syncs it to their Cloud Data Warehouse.

Extract Application Data with Ease

The spreadsheet is the backbone of business analysis, and over 1.2 billion business users are familiar and comfortable analyzing data in a tabular format where data is structured in columns and rows. Unfortunately, application data often arrives as a JSON object, which can be hard to understand with its nested key-value pairs and can’t be processed in many legacy BI applications until it’s been flattened upstream by the data team.

Sigma allows business users to extract values from nested variant columns easily and analyze them within the familiar table & row spreadsheet, with just a few clicks.

Sigma flattens variant data in just a few clicks.

Rapidly Model Data in Sigma

Fivetran replicates relational data models with ease. But deriving value from these models often requires understanding SQL and writing queries with complex joins. Sigma’s JOIN feature allows users to choose their join, preview the results, and model the data without leaving the platform.

Sigma supports left, right, inner, and full outer joins with composite keys, automatic data type matching, comparison operators, and custom formulas. You can also union multiple tables together.

Monitor Data Freshness

Since Sigma queries directly against your Cloud Data Warehouse (CDW), Sigma Workbooks surface the most recent data. Sigma is cloud-native and handles massive workloads with ease, and isn’t constrained by scheduled extracts or aggregate table creation.

The Fivetran Log Connector provides the metadata you need to be certain your data is fresh. By querying this metadata, Sigma can inform business users their Workbook data is up-to-date. 

Scheduled Exports notify users when data refreshes within the Sigma Workbook and sends an alert to the data team when an SLA is missed. The fastest way to lose trust in data is for business teams to find quality and freshness problems before the data team has a chance to mitigate the issues. Sigma makes it easy to ensure that only high quality, up to date data is delivered to your users and maintains the trust and transparency expected of modern data platforms.

Sigma’s Schedule Exports alert users about changes in data quality and freshness. This feature is configurable based on conditional logic.

Fivetran and Sigma make it easier to derive actionable insights from your Modern Data Stack. Connect with Sigma’s expert team of solutions engineers or learn how to set up a Modern Data Stack with Fivetran, Snowflake, and Sigma in under an hour and start uncovering the insights that power your business.

We are Sigma.

Sigma is a cloud analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It requires no code or special training to explore billions or rows, augment with new data, or perform “what if” analysis on all data in realtime.