Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Sigma Computing Adds New Features to Maximize Data’s Value Across the Enterprise and Empower More Teams

New Dataset Warehouse Views Is the First to Enable Anyone to Leverage Data Modeled in Sigma Across Any SQL-Powered Application or System

Sigma Computing, an innovator in cloud-native analytics and business intelligence (A&BI), has extended the power of Sigma to be used throughout the cloud data analytics stack, solidifying it as the single source of truth for data across entire organizations. With this feature, Sigma is the first to provide non-technical users with the ability to create a dataset and write it back to the cloud data warehouse (CDW) for use across the organization without needing to write code. The company is also jump-starting analysis and expediting time to insights with the launch of its first template for customers on Snowflake.

“The new Dataset Warehouse Views feature has been a huge time-saver for us – we model the data once and can use it anywhere,” said Michael Bell, senior director of data science and analytics, Agero. “The key benefit is that you don’t have to be a specialist to contribute to data modeling and curation, which allows us to iterate more quickly and collaborate more effectively. Sigma has really transformed our analytics and business intelligence process, making data analysis accessible to anyone and giving them the confidence needed to take swift action on the new insights they discover.”

Recommended AI News: Samsung Brings In Auto-Fit Flex Mode For YouTube Viewers

Dataset Warehouse Views

New Dataset Warehouse Views make it possible for all data analysis and modeling created in Sigma to be written back to a CDW as a live dataset and used in countless internal and external systems and applications, as well as embedded into custom mobile and web applications, including visualization tools. Sigma automatically generates SQL code for any action taken in the Sigma Spreadsheet, enabling anyone that knows how to use a spreadsheet to query the cloud data warehouse and create datasets that have all of the features of tables, including links. Dataset Warehouse Views stay in sync with the dataset from which they are created because Sigma automatically updates each warehouse view to match any changes published to the dataset.

“The proliferation of SaaS tools has not only resulted in mountains of data but also a number of applications that you need to be able to access all that data in,” said Rob Woollen, CEO and co-founder, Sigma Computing. “With Dataset Warehouse Views, organizations can now rely on Sigma for datasets and analyses wherever they need them. IT and data teams will also no longer have to make the false choice between a portfolio of best-in-class data tools and settling for less performance in a single vendor solution to aid data management because Sigma can easily sit at the center of an organization’s cloud data ecosystem, connecting all the dots and maximizing data’s value.

Related Posts
1 of 5,304

Recommended AI News: Microsoft Signs A 5-Year Deal With The Coca-Cola Company To Transform Global Engagement And Experiences

Templates

Templates provide a pre-built starting point to begin working with data sources, making it easier to build new, complex analyses quickly. Sigma Computing will offer templates for data connections, dashboards, and worksheets to extend the value of Sigma to teams who may not have the bandwidth or ability to create them from scratch. The first template available is for Sigma customers using Snowflake and provides three pre-built dashboards, with underlying worksheets, from secure data connections for the following use cases:

  • Snowflake Account Usage: Pulls account b****** information directly from a Snowflake instance;

  • Snowflake User Adoption: Pulls user adoption information directly from a Snowflake instance.

  • Snowflake Performance Monitoring: Tracks database, warehouse, and individual query performance.

Sigma and its partners will continue to develop templates for the most common Sigma use cases.

“Sigma templates help new customers immediately see the value of their SigmaComputing investment and ensure existing customers are maximizing the value Sigma brings to their cloud data stack,” added Woollen.

Recommended AI News: Hot AI ML Startups: 10 Machine Learning Companies

Comments are closed, but trackbacks and pingbacks are open.