In today’s data-centric enterprises there are three primary groups of users working with data and analytics:
Over the years the gap between the data engineers, analysts, business teams has continued to widen.
Traditionally data teams curate tables within a data warehouse, which are queried via report/chart building tools or downloaded via sanctioned access points. This curated model has its advantages when it comes to standardization, but it isn’t free of downsides. When an analyst conceives of a valuable change, the process for incorporating it into the model (even as an experiment) may involve weeks of waiting on data engineers. More often than not, analysts manually and repetitively apply these changes in isolation. This means improvements are confined to laptops and emails, rather than readily available to the entire organization.
And even if analysts push for changes to be incorporated back into the standardized model, their request is likely one of many; this influx of requests can cause data engineers to become a major bottleneck. When this happens, it pulls data engineers away from their own responsibilities and may even delay analyst requests to the point that they become irrelevant and out of date.
Here are a few more challenges facing today’s data engineers:
Sigma builds on decades of best practices regarding data warehouse modeling and access patterns, making many of the same choices an experienced data engineer would make. And unlike any other product, Sigma can express the vast majority of ANSI SQL visually.
The Sigma solution closes the gap between analysts and technologists. Everyone in the enterprise is using the same interface, talking about the same data, and centralized on the cloud data warehouse. All SQL and post-processing are executed using the enterprise’s cloud data warehouse. This simplifies data governance since tables don’t need to be moved or stored at rest in any other system.
Sigma builds on decades of best practices regarding data warehouse modeling and access patterns, making many of the same choices an experienced data engineer would make. And unlike any other product, Sigma can express the vast majority of ANSI SQL visually – and the coverage increases in every new release. Using the solution’s familiar visual interface, both analysts and technologists are able to produce any SQL query desired, a capability other products are unable to match.
One of the fundamental elements of the Sigma solution is the Sigma Worksheet – a basic, reusable unit of analysis, collaboration, and access control. The worksheets function like virtual spreadsheets that live and run in the cloud. Organization members create worksheets to analyze, curate, and share. Admins can endorse worksheets that canonically define the data. Anyone can leverage endorsed worksheets and co-workers’ worksheets as a starting point for new reports and analyses.
Sigma ensures that anyone can use worksheets (instead of SQL) to wrangle JSON, join tables and sheets, and materialize optimized cubes/summary tables. Business analysts can use simple formulas to write part-to-whole, create window functions, fill-down data, and build month-over-month comparisons, without needing to learn a thing about SQL. Because this process is concretely expressed in tables and charts and spreadsheet formulas rather than in abstract code or backend GUIs, the full lineage of transformation is on display for anyone with a question.
Even for a veteran SQL programmer, Sigma Worksheets solve some of the language’s greatest shortcomings, such as: the lack of abstraction and composability; the brittle nature of query debugging; and the high bar to collaboration that’s inherent with any programming environment.
Sigma does the heavy lifting of transforming a web of worksheets into the subqueries, aggregations, joins, and windows necessary to generate efficient queries and correct results every time.
Because Sigma generates and optimizes queries on the fly, the readability and performance of the generated SQL can be improved without any customer intervention. Sigma’s deployment model means that these improvements take effect as soon as product updates are deployed.
Sigma is not trying to impose a new language or an alternative to SQL. The solution brings together best practices that allow technologists and analysts to work together in a collaborative fashion. Anyone in your enterprise can make full use of the data warehouse via Sigma Worksheets and the Qwil compiler that powers them.
Sigma not only removes bottlenecks by empowering business analysts to pursue their own answers, it frees up the time of the highly experienced (and expensive) technical people on your team so they can direct their expert skills at challenges only they can address. At the same time, it extends the value of your curated data to all users across the enterprise.
Simply stated, Sigma doesn’t get in your way. Instead it is an invaluable tool that you and your colleagues can employ as you go about mining, analyzing, and sharing the treasure troves of data now being generated in your field.
Check out these other resources for more information on how Sigma changes how you work.
Sigma makes Cloud Data Warehouse Analytics as accessible and approachable as a spreadsheet by utilizing proprietary Qwill technology to translate actions into queries.
Organizations today face a data glut—but the ability to turn that data into insights continues to be stuck behind technical barriers. Sigma's spreadsheet-like interface makes the data warehouse accessible across your organization.