Announcing Visual Data Modeling
Product Marketing, Sigma
Data modeling helps organizations create centralized data definitions that anyone can use to find and understand the data in a data store. But historically, the amount of technical knowledge needed to model data or iterate upon definitions kept business experts out of the conversation.
As more companies seek to create data-driven cultures, it’s necessary to break down the barriers so that business teams can quickly find the most trusted data sources and generate insights without hand-holding from the data team.
That’s why we’re excited to announce our new data modeling capabilities, coming this month. Sigma’s data modeling layer provides an intuitive way to build centralized data definitions and guide data exploration that empowers business teams to thrive. Read on to learn how data and business experts can work in concert to build and iterate data models that fast track insights and drive BI adoption.
Curate Data Sources Without Writing Code
Our team built Sigma’s modeling layer on objects called Data Blocks. These curated sets of data serve as a starting point for analysis. Data teams can pre-build Data Blocks using Sigma’s award-winning visual interface in minutes, eliminating the need to learn proprietary coding languages or manage source code as new business requirements arise. Meanwhile, domain experts in every corner of the organization benefit from instant access to trusted data sources and consistent metrics that provide business context for faster, more informed decisions.
Data Blocks provide greater context by adding descriptions, mapping relationships between tables, providing common calculations, and defining reusable metrics. They can be built entirely through Sigma’s spreadsheet-like interface or with our new SQL Runner, making it possible for anyone to play a role in the modeling process. And Data Blocks can be shared and developed further by business people who are closest to the data using the visual interface, so models never go stale, and data remains useful and up to date.
The best part? You can build the modeling layer as needed and expand it at any time. With this flexibility, anyone can generate insights immediately, rather than needing to determine all aspects of the modeling layer first.
Accelerate Insights from a Single Source of Truth
Curated Data Blocks bypass the frustration of finding, making sense of, and organizing data so people can jump straight into discovery. The Sigma approach combines the power of a curated data experience with the flexibility to access and include other data from the warehouse (or CSV uploads) that is valuable to the analysis. Data teams can quickly build and share Data Blocks, and just as easily give deeper access to those that need it.
Data blocks are a straight-forward way to maintain consistent reports, KPIs, standardized calculations, and foundational data views. At the same time, organizations can empower business experts to safely discover, expand, and share data that is always fresh and secure in the cloud data warehouse.
A Collaborative Environment for SQL Experts and Spreadsheet Users
Data analysis often happens in silos. Most BI platforms focus on SQL programmer or BI experts, not the business people. While some tout friendly UIs for these domain experts to “Explore,” they remain limited. These users tend to experience stagnant dashboards, outdated reports, and frustrating wait times for model changes, leading them to resort to data extracts and spreadsheets for analysis. Not only do these extracts and analyses live outside of the cloud warehouse, but they introduce errors and additional security risks as well.
With Sigma, your company gains access to a single environment built for both the data team (including your SQL gurus) and business experts (that love Excel). Our new SQL Runner provides the coding tools you expect from a data analytics solution, while our visual analysis interface gives anyone the ability to model, explore, analyze, and report data without writing code (with all the power of SQL).
Meanwhile, data remains in the data warehouse and off of individual PCs, and you finally get what the BI community has promised for decades: self-service analytics as it was meant to be— a single source of truth that eliminates data extracts, simplifies analysis, and drives BI adoption at every level of business.