ON-DEMAND WEBINAR PANEL

How to Bridge Data Science and Business Intelligence

FEATURED SPEAKERS | DATA & ANALYTICS LEADERS

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Learn how to bridge Business Intelligence and Data Science to make smarter data-driven decisions at scale using a semantic layer.
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Now available on-demand!

Join Data and Analytics leaders and strategists for a webinar panel discussion on data strategies for eliminating the silos between BI and Data Science teams using a semantic layer.

Our featured speakers will share practical guidance and examples from how they build a data infrastructure and architect a strategy to support both BI and Data Science programs. You will hear best practices for creating an analytics feedback loop between your Data Science and BI teams as well as how to create a common language for your data across the company.

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In this webinar

You will learn about:

  • Gaining business alignment across BI and Data Science teams
  • Reducing data prep for your Data Science & BI teams
  • Creating governed and consistent access to features, numerics, categoricals, hierarchies, dimensions and measures
  • Simplify and accelerate feature engineering for more powerful ML models
  • Operationalize Data Science by publishing model results to BI consumers through the semantic layer
  • Publish model outputs (e.g. forecasts, suggested actions) to broader audiences through BI tool
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Who should watch

Data-driven Leaders and Practitioners (e.g., Chief Data Officers, Data Scientists, Data Literacy, Business Intelligence, and Analytics professionals) looking to bridge the gap between Data Science and BI workloads and/or teams to make smarter decisions at scale.

Contributors Include

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Harendra Kanuru

Engineer Manager, Big Data and Analytics at The Home Depot

Harendra is an engineering manager at The Home Depot within enterprise analytics and reporting, where he leads multiple data engineering teams in developing and designing BI products focused on site analytics for homedepot.com. Harendra has years of experience building, optimizing, and maintaining multi-petabyte ETL and ELT pipelines to enable analytics visualization tools, build custom analytics applications, and support data science applications. Harendra is deeply interested in enabling and simplifying the experience and application of big data analytics for all consumers.