Intuitive Predictive Analytics Visualizations with Alteryx Analytics

Intuitive predictive analytics visualizations with Alteryx Analytics : Alteryx is the leader in data blending and advanced analytics software. Alteryx Analytics provides analysts with an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks, typical of traditional approaches. Alteryx analytics platform can deliver deeper insights by seamlessly blending internal, third party, and cloud data and then analyze it using spatial and predictive drag-and-drop tools. This is all done in a single workflow, with no programming required. More than 700 customers and thousands of data analysts worldwide rely on Alteryx daily.

Alteryx

Alteryx Designer allows to blend internal, third-party, and cloud-based data, build powerful R-based predictive and spatial analytics applications without any programming and share deep data insight with business decision makers.
Predictive modeling techniques, such as logical regression or decision trees, clustering techniques such as K-centroid clustering and principle component analysis, data investigation techniques, such as scatter plots and association analysis- all can be included with out any programming using Alteryx Designer. Alteryx Server, scale the critical analytic workflows to meet data and analytic requirements, schedule multiple workflows and publish and share analytic applications the organization. Alteryx Analytics Gallery lets to consume, share and publish analytic apps and macros .

Alteryx Designer

Alteryx Analytics 9.5 release specifically focuses on empowering analysts as they progress from using spreadsheets to taking full advantage of the data resources their organization has built around them, allowing them to blend large datasets within databases rather than just subsets of data on their desktops. This replaces the slow and complex SQL coding that has traditionally been used, cutting processing time dramatically for users of Microsoft and Oracle databases. Additionally, 9.5 includes updated visualizations for a number of the Alteryx R-based predictive tools, and an easier way for analysts to share their work in the form of workflows or macros that solve specific analytics problems.

"Over 90% of analytics leaders say that delays in creating the right dataset translates directly into missed revenue and profit," said George Mathew, President and COO of Alteryx. "With Alteryx Analytics 9.5 we extend our leadership position in data blending by delivering even better performance with new in-database capabilities to get analysts the data they need. This approach is dramatically faster than hand crafting code, even when taking advantage of an entire database."

The Alteryx Analytics 9.5 platform delivers new in-database data blending tools, intuitive predictive analytics visualization, Alteryx workflows and macros and many more. Alteryx 9.5 extends the high performance and speed of the product to very large datasets within the databases analysts use every day without requiring hand-crafted SQL coding. These new in-database tools allow analysts to take advantage of their entire database, and will be initially available for Microsoft SQL Server and Oracle databases. Alteryx is introducing the first set of its R-based predictive and data investigation tools with new ways to visualize the results. Today analysts utilizing R are forced to use basic, static visualizations to understand how their models have performed. These new visualizations are designed to make it easier to understand the results of predictive models, driving faster conclusions and recommendations. Initially, visualizations for AB Analysis, Contingency, Frequency and Association tools will be available – with support for other tools in the future. Alteryx 9.5 makes it easier to share pre-configured workflows or packaged macros to solve these problems within an organization by posting them to an Alteryx Server, or with the wider analyst community through the Alteryx Analytics Gallery. This will further reduce the time that analysts spend blending their data and building analytical models.