Delivers Industry’s First Cross-Platform Root Cause Analysis Feature and Broadens Integration Support to Include Amazon Redshift Spectrum, Apache Druid & Google Ads
Outlier, a pioneer in Automated Business Analysis, announced the release of the industry’s first artificial intelligence (AI) powered cross-platform Root Cause Analysis feature. Root Cause Analysis allows Outlier to not only surface key insights about business changes automatically, but also identify the likely root causes of those changes. As part of this release, Outlier’s offering now extends to its growing list of SQL and cloud services integrations including newly announced support for Amazon Redshift Spectrum, Apache Druid, and Google Ads.
Automated Business Analysis uses AI to find unexpected changes in your data, acting as a virtual business analyst. Outlier automatically surfaces insights across huge amounts of data, reducing the amount of time required to take advantage of opportunities and fix problems. Automated Business Analysis products also work across a myriad of data sources, including cloud-based services and cloud or on-premise storage, to perform this analysis quickly.
“We see increasing demand from customers who have dozens of metrics dashboards and hundreds of databases but still get surprised by unexpected changes. Automated Business Analysis platforms, like Outlier, change their relationship with data by eliminating blind spots hiding behind their dashboards,” said Sean Byrnes, CEO, Outlier. “With the addition of Root Cause Analysis, the insights we provide save even more time and become even more actionable by showing customers where to look for the root cause of the insights we deliver to them everyday. Even better, this feature works across all the different systems where customers store their data, including clouds like Adobe, Amazon, Google, and databases like Druid, PostgresQL and MySQL among others.”
Outlier’s Root Cause Analysis shows the drivers of a change across several dimensions of data, providing the context necessary to take quick action. If a sudden decrease in revenue for a product is identified, Outlier would show specific regions, traffic sources, platforms, warehouses and more that drove the change. Each one of these causes may be managed by different departments in the organization, with teams often geographically distributed, making investigation difficult. Outlier surfaces root causes to users, in a single story, eliminating hours of research and enabling efficient communication across the organization.
“Root Cause Analysis is essential for Gannett when dealing with high volumes of constantly changing data across multiple web and mobile properties,” explained Oskar Austegard, Senior Director, Data Solutions at Gannett USA Today Networks. “Outlier helps us quickly identify opportunities and challenges across web and mobile analytics data. Outlier’s Root Cause Analysis allows us to understand, in seconds, unexpected changes to specific audience segments, as well as the nature of viewer traffic, that we can then address and resolve.”
Automated Business Analysis platforms are fast becoming a necessity for large businesses because it is difficult to uncover meaningful insights, and their root cause, given many organizations have petabytes or even exabytes of data to sift through. Outlier overcomes the data challenge, by using over a dozen forms of statistical machine learning to turn raw data into 4-5 human-readable insights delivered daily.
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