In today’s business world, we are at a stage when analytics has become ubiquitous in all enterprises, but unfortunately, it’s adoption has not. Tune in to hear David McBride, Sushant Ajmani, and Joseph Sursock as they talk about improving the adoption of self-service BI.


 

The Business Intelligence (BI) & Analytics ecosystem has evolved significantly in the last two decades. According to Gartner, most of the enterprises have gradually transitioned from the Semantic era (designed for the IT experience) to the Visual Data Discovery era (designed for the analyst experience) in the last decade or so. A lot of power is vested in the hands of power users, analysts, and mid-management business users who embraced the philosophy of self-service BI. During this period, there was a spike in demand for smarter, faster, and interactive tools that can deliver a compelling and visual-intensive storyline to business users and decision-makers.

Lately, the digital industry has entered the 3rd era of Business Intelligence, i.e., Augmented Analytics (designed for the consumer experience). In this era, the expectations have shifted towards generating relevant, contextual, and actionable insights for decision-makers in a human-friendly manner across multiple consumption mediums. There are 3 KPIs that the Augmented Analytics ecosystem is embracing, i.e., Speed to Actionable Insights, Action TAT and Improving the Self-Service BI Adoption (which currently hovers around 35% as per Gartner). The basic constructs of the Augmented Analytics era are Automation, Machine Learning, and AI (NLP and NLG).

In this podcast, Sushant Ajmani, Joseph Sursock and David McBride discuss the above three eras of Business Intelligence, and how business needs and expectations are evolving year over year and challenging the incumbent BI ecosystem to focus on unmet business needs in the organization. The Podcast host also discusses the value proposition of Course5 Discovery (An AI-powered Augmented Analytics Solution) in the digital landscape, and how Discovery is targeting the unmet operational needs of the business users in Supply Chain, Finance, Ecommerce, Sales & Distribution, and Consumer Insights functions.

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