The Alteryx Platform is all about breaking traditional, analytic silos and models by making it easy to access all relevant data needed regardless of location, format or size of that data, and then empowering analysts to perform sophisticated analytics without the need for coding or waiting on other departments.
I’m excited to announce that with the release of Alteryx Analytics 11.0, we are once again breaking the traditional data analytics mold and enabling the analytic enterprise by bridging the gap between IT and analytic teams for governed, scalable, and flexible self-service data analytics.
In Alteryx Analytics 11.0 we’ve expanded our platform support for in-database (In-DB) connectivity to include SAP Hana, Microsoft Azure SQL Database, Microsoft Analytics Platform System, and IBM Netezza. In addition, we enhanced our in-database analytics for, Oracle R and SQL Server 2016, putting the power of big data in the hand of analysts of all skill levels.
Connecting to data should be easy no matter where that data resides, and we understand that not all data assets come from traditional databases or sources. With 11.0, we continue to help analysts tap into nontraditional data assets with a new Zip file connection, enhancements to our SharePoint connector, and a customizable ODBC connector. We’ve also made connecting to the most popular databases - SQL Server and Oracle Database - seamless and easy so that analysts can focus on working with the data instead of how to connect to these data sources.
These new features are key to data workers and analytic leaders as they empower analytic teams the ability to harness all available data, quickly, easily and eliminate the need to code so that full value of existing and emerging data assets can be harnessed. For IT and Data Managers, the In-DB functionality is a benefit to them as it helps them ensure the data policies they have in place are respected since the In-DB connections within Alteryx adhere to the established read, write, and access data governance policies that are in place.
To help analysts and analytics teams build sound insights, we’ve focused on taking the human error mistakes out of certain processes by designing features to help build confidence in creating analytic models with Alteryx Analytics 11.0.
New automated Data Profiling helps analysts quickly and visually understand the health and quality of a dataset prior to building models. Typically data profiling requires a separate team of data specialist, statisticians or data scientist to evaluate the statistical distribution of a dataset and evaluate if it is healthy or complete enough to build models upon. With 11.0 we’re putting this into the hands of every data worker, through interactive visualizations that make interpreting the quality of their data easy.
Once a dataset has been deemed to be of quality by an analyst, we are helping data workers generate fast and accurate expressions with a new Formula tool that provides suggestions, error notifications, auto-completion of expressions and data previews to help deliver the right results. And, as analysts look to expand their skillsets, we’ve made understanding and evaluating linear regression, logistic regression, and decision trees models easy with new intuitive predictive model visualizations.
In addition, we have embedded a new global search function in 11.0. This new search function allows analysts the ability to collaborate and crowdsource answers by tapping into the thousands of analytic experts within the Alteryx Community, as well access all available tools, analytic samples and tutorials without having to leaving the Alteryx Designer interface.
All of these features help analytic leaders empower their analytics team regardless of skillset, and more importantly helps build trust in the accuracy of insights delivered from analytic teams to decision makers.
Many organizations understand that governance is not only needed, but actually useful in empowering data workers and analysts to discover new insights; however for many organizations it’s difficult to achieve data governance within a self-service model. In Alteryx Analytics 11.0, we are helping organizations overcome this challenge.
The new Data Connections Manager in 11.0 ensures IT-compliant data access with a centralized and easy to administer portal. The new Connection Manager allows IT or Data Administrators to centrally create, manage, and share connections across the organization. Analysts and analytic teams no longer have to deal with the challenges of trying to have IT or Data Managers handle individual requests. Now these connections can be created, edited shared or revoked quickly and easily, helping to enforce data governance policies.
Automatically scheduling a repeatable analytic process to run on a set schedule has been a long standing benefit of the Alteryx Platform, with 11.0 we have created a new scheduling experience that supports analytics teams in scaling their analytics processes across the organization. The new Scheduling experience allows individual users to create, manage and schedule workflows that they have access to, while Administrators can see and manage all schedules, as well as control the permissions of who has access to which workflows for scheduling.
Finally in 11.0, we’ve released usage monitoring and reporting features, helping Administrators optimize the performance of analytic workloads, reduce reporting bottlenecks, and understand the usage of Alteryx Designer across the organization for better visibility and control.
The features in Alteryx Analytics 11.0 balance the requirements of IT and Data Managers, while still empowering analysts with the self-service analytic flexibility they need. We encourage you to upgrade to our latest release, or try it out for free and experience these new features for yourself.
Learn more about each of the new features we’ve released in Alteryx Analytics 11.0 by registering for our live webinar, “Bridging the Gap: Self-Service Data Analytics meets Data Governance” and following our 11.0 release blog series.