SAN FRANCISCO & PHILADELPHIA--(BUSINESS WIRE)--Panoply, Stitch and Chartio today announced the availability of the world’s first Automatic Cloud Data Stack. The combined offering enables data analysts and business users to connect to disparate cloud applications and databases to gain valuable business insights through data visualization. The joint solution includes:
- a self-optimizing petabyte-scale data warehouse
- a self-serve ETL pipeline
- a modern business intelligence platform with pre-built business dashboards
Implementing the Automatic Cloud Data Stack eliminates the need for lengthy warehouse setup and configuration, and does away with the need for coding to integrate disparate data sources, perform ad hoc queries and create interactive charts and dashboards. These features are all accessible in an integrated environment for an optimal customer experience.
- Panoply CEO Yaniv Leven says, “In July of this year, Gartner said that augmented analytics, an approach that automates insights using machine learning and natural-language generation, marks the next wave of disruption in the data and analytics market. Two months ago Larry Ellison dedicated the lion’s share of his Oracle OpenWorld keynote specifically to this topic. We’re seeing huge customer demand from professional analysts and citizen analysts who want more and faster access to data. The challenge has always been that to extract information from data, the data had to go through the IT department, and demanded incredible coding resources and technical expertise to put it in an accessible place and format. Well, no more. This collaboration unshackles data from the IT bottleneck and provides analysts with the ability to control the entire pipeline.”
- Stitch CEO Jake Stein says, “This platform enables a best-of-breed data stack at the touch of a button. Users get the time to value and user experience of an integrated solution while maintaining the extensibility of three first-class independent products. For companies that want to build a culture of data-informed decisions, there's no better option.”
- Chartio CEO Dave Fowler says, “By incorporating Panoply, Stitch and Chartio in a single platform, we can extract, transform and load business data into an Amazon Redshift data warehouse and connect it to Chartio all in a few clicks. We’re removing the onboarding bottleneck and allowing everyone in the organization to access and understand data without having to depend on data engineering or IT for setup, approval or access.”
Stitch is a simple, powerful ETL service built for developers. Stitch connects to all your data sources – from databases like MongoDB and MySQL to SaaS tools like Salesforce and Zendesk – and replicates that data to your data warehouse. With Stitch, developers can provision data to analysts and other team members in minutes, not weeks. To learn more, visit http://www.stitchdata.com, read our blog, and follow us on Twitter, Facebook and LinkedIn.
Chartio is on a mission to democratize data across organizations so that everyone can access, explore, transform and visualize their data. To that end, Chartio has built a cloud-based data exploration tool that’s simple enough for every department yet powerful enough for the data team. Chartio has been named a “High Performer” BI tool by G2Crowd in 2016 and 2017. To learn more, visit Chartio.com or follow us on our blog, LinkedIn, Facebook and Twitter.
Panoply is the world’s first Smart Cloud Data Warehouse. Panoply delivers the industry’s fastest time to insights by eliminating the development and coding typically associated with transforming, integrating and managing data. Panoply’s proprietary AI technology automatically enriches, transforms and optimizes complex data, making it simple to gain actionable insights. The company, based in San Francisco and Tel Aviv, is privately held and funded by investors such as Intel Capital, 500 Startups, Blumberg Capital and C5 Capital. For more information and a list of career opportunities, visit https://www.panoply.io, or find us on Twitter, Facebook or LinkedIn.