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Good Things Come in Threes: Advanced Analytics, Predictive Analytics, and Self-service Analytics

Outlier attended the CDAO (Chief Data & Analytics Officer) event in Chicago.  The 3-day event was chock full of a who’s who from across a wide variety of verticals ranging from Pharmaceuticals to Finance to Aerospace.  Our team had the pleasure of being able to sit down with some of the brightest data science minds in advanced analytics, predictive analytics, and self-service analytics – good things come in threes!

Reading ICYMI: Good Things Come in Threes: Advanced Analytics, Predictive Analytics and Self-service Analytics
Reading Good Things Come in Threes: Advanced Analytics, Predictive Analytics, and Self-service Analytics

The common theme amongst attendees was; how do organizations integrate and leverage new, or existing, data sources in order to achieve a competitive advantage? What struck us is that all of these organizations are trying to find a competitive advantage in their data. 

Some companies are concerned about being able to predict KPIs or important outcomes. Other organizations are struggling with implementing advanced analytics so their teams can be more efficient. Every organization is also having a challenge in hiring top data science talent quickly.  

The topic that resonated most with these Chief Data and Analytics Officers was about self-service analytics and how to actually make that buzzword a reality. Dr. Mike Kim, Chief Technology Officer at Outlier, hosted a speaking session titled: Achieving the ‘Nirvana’ of Self Serve Data Science.  The session was standing room only and provided a springboard for some of the most engaging conversations of the 3-day event. Mike explained how automating business analysis (ABA) can help propel a company to achieve self-service analytics faster than thought possible. 

ABA leverages Artificial Intelligence (AI) techniques to analyze data and find unexpected changes in your data quickly, acting as a virtual business analyst. ABA can find these insights immediately, reducing the dependency on data scientists and serve up those insights automatically. 

In case you missed Dr. Kim’s session, you can check out the webinar here

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