Brian Prascak is a seasoned data and analytics executive with over 15 years of experience across financial services, consumer goods, retail, travel, and technology. He has held leadership roles at major organizations including JP Morgan, IBM, Diageo, and Wawa, where he guided the development of advanced analytics platforms, AI-powered insights, and enterprise-scale data strategies.
Brian specializes in operationalizing AI/ML and BI, placing a strong emphasis on semantic layers, analytics governance, and cloud-native data architectures. He’s helped teams transform data into actionable insights, build high-performing analytics functions, and accelerate digital transformation through modern, scalable approaches.
A recognized thought leader, Brian frequently speaks and writes on topics such as semantic modeling, data strategy, and the business value of analytics. He advocates for treating data as a product and championing disciplined, governed self-service to deliver continuous, autonomous insights at scale.
October 18, 2022
Defining the Modern Data LandscapeThe purpose of this blog is to introduce the modern data landscape. We want to provide our perspective on the data and analytics industry — where we’ve been, where we are now, and where we are heading. We’ll also discuss…
September 29, 2022
The Rise of the Semantic Layer: Enabling Speed, Scale and Cost Effectiveness To Deliver Actionable Insights and AnalyticsIt’s hard to believe that just 15 years ago, big data and cloud technology emerged with the introduction of Hadoop and cloud vendor offerings. Over the past 5 years, most enterprises have moved to the cloud, motivated by the dual…
May 17, 2022
The softer side of enterprise analytics: Culture, Org Design, Process ManagementMany companies pursuing a path to data-driven decision-making – accelerated through data democratization – struggle with how to define and support the core people, roles, and competencies involved with data (data creators, enablers, and consumers). In many cases, the path…
April 7, 2022
Supporting Intelligent Automation Initiatives with a Semantic Layer to Transform Enterprise Data OpsAs intelligent automation technologies become more prevalent and sophisticated, the need for a semantic layer to provide the data necessary for enterprise operations is becoming increasingly important. This includes improving process and task automation development, data refinement and optimization, interpreting…
February 22, 2022
Developing an Effective Enterprise Data Strategy in the Age of Cloud Data PlatformsMany companies have difficulties developing a roadmap for data, insights, and analytics. This blog stresses the importance of having an enterprise data strategy as the guidepost for articulating an effective set of use cases and a clear roadmap that scales…
February 15, 2022
Accelerate Your Path to Self-Service Data AccessMany companies struggle with making data available quickly and structured in a way to enable the generation of actionable insights, particularly using a self-service delivery model. As the amount of data available via modern data platforms and sources continues to…
February 8, 2022
Developing Smarter, Faster Insights from Business IntelligenceMany companies struggle with making data available rapidly, while structuring and integrating this data effectively to enable the creation of actionable business intelligence insights and analytics. With an ever-increasing amount of data available via modern data platforms, companies need to…