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Oracle Autonomous Data Warehouse updated with new data tools

Oracle is updating its cloud data warehouse platform with new tools that aim to enable users to more easily benefit from data analytics and machine learning predictions.

Oracle is updating its Autonomous Data Warehouse with a series of platform enhancements designed to help make it easier for users to benefit from data. The new updates were revealed in a virtual event today, with Oracle noting that the new features are now generally available.

Oracle Autonomous Data Warehouse is a cloud service that provides data warehouse capabilities that are fully managed and regularly updated. The Oracle service competes against rivals including Amazon Redshift and Snowflake. Among the new capabilities are a series of integrated data tools designed to enable a self-service approach for data loading and transformation. Oracle is also integrating machine learning functionality with its AutoML capability, which helps users select the appropriate algorithm for a given task.

Mike Leone, a senior analyst at Enterprise Strategy Group, said the efforts to improve productivity and efficiency are geared at helping Oracle's database and system administrator users.

Andy Mendelsohn, executive vice president at Oracle
Andy Mendelsohn, executive vice president at Oracle, details new features in the Oracle Autonomous Data Warehouse at a virtual event today.

"With the latest Autonomous Data Warehouse announcements, they're looking to extend that value to more data-centric personas, including data analysts, citizen data scientists and business users," Leone said. "By offering an intuitive drag-and-drop UI and a low-code interface, several phases of the data lifecycle -- including data loading, analysis and building machine learning models -- are being simplified through self-service enablement provided by Oracle."

Updated features in the Oracle Autonomous Data Warehouse

Andy Mendelsohn, executive vice president at Oracle, detailed in today's virtual event what the new capabilities will help to enable.

Among the new features is support for spatial analytics. Mendelsohn explained that spatial analytics uses location information to help inform data insights. For example, retailers will be able to find users within a certain distance of a store, in order to send targeted promotions.

Oracle is also adding support for graph analytics to the Autonomous Data Warehouse. Mendelsohn said the feature will help organizations more easily understand the social networks of customers or users.

Improving access in the Oracle Autonomous Data Warehouse

A key theme of the update is about making it easier to use the technology -- and that starts at the beginning, with data loading.

Mendelsohn said Oracle has added tools to the Autonomous Data Warehouse to make it easy for users to drag and drop data sitting in files, or other data sources into the data warehouse. Oracle has also added tooling that enables users to specify transformations and cleanse data so that it can be useful for analytics and business intelligence.

Oracle's AutoML capability aims to make machine learning more accessible as well. According to Mendelsohn, users can supply data and specify what type of prediction or analysis they are looking for; AutoML will then automatically choose and execute a machine learning algorithm to get best results.

"We're bringing a new set of tools, a new set of rich analytics to empower the data analysts, data scientists and line-of-business developers to more easily get value out of their data," he said.

Enterprise Strategy Group is a division of TechTarget.

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