Defining the Modern Data Landscape – The Need for Speed, Scale and Cost Effectiveness

by Brian Prascak

Defining the Modern Data Landscape - cover

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The purpose of this white paper is to introduce the modern data landscape, including providing perspective on the data and analytics industry – where we’ve been, where we are now, and where we are heading. 

We define the modern data landscape, frame its purpose and direction, with a focus on the fundamental need for actionable insights that are delivered with speed, scale and cost effectiveness.

Over the past 5 years, most enterprises have moved to the cloud, motivated by the dual need for digital transformation of their business, coupled with embracing cloud-based data platforms and tools to realize the benefits of advanced insights and analytics.

We take a look at the areas that are rapidly emerging, including those most suited to support achieving increased speed, scale and cost savings for AI and BI.

About the Author

​​Brian Prascak is an expert in the area of data, insights and analytics, with extensive experience helping companies realize the benefits of using AI / ML and BI across a wide variety of industries and functions in the US and globally. Brian is currently Co-founder and Chief Insights Officer at Naratav, Inc. Before starting Naratav, Brian was Director, Advanced Analytics, Platforms and Data Services at Wawa. Brian has worked with many global organizations, including previously at IBM, Diageo, Mastercard, JPMorgan and AC Nielsen.

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