ON-DEMAND WEBINAR PANEL

How to Democratize Data and Scale Augmented Analytics

FEATURED SPEAKERS | DATA & ANALYTICS LEADERS

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Learn from top strategists and technologists about actionable strategies to effectively democratize data and scale augmented analytics.
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Now available on-demand!

Join this webinar panel for practical advice on how to evolve your business intelligence with augmented analytics, scale data science initiatives, break down enterprise data silos, and optimize your cloud analytics infrastructure at scale.

The discussion will focus on making more data accessible to various stakeholders across your organization and integrating predictive and prescriptive analytics to support smarter data-driven decision-making at scale.

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In this webinar

You will learn about:

  • Democratizing data: making data as consumable as possible while keeping things safe and clean with data stewardship, curation and governance.
  • Augmented Analytics: scaling machine learning, augmented, predictive and prescriptive analysis strategies as they apply to faster insights and business outcomes
  • Integrating AI and BI: sharing AI/ML model outputs with enterprise BI teams to create a 360 degree feedback loop.
  • Data Literacy: the role of a semantic layer as part of a broader data fabric that forms a central repository of enterprise metrics to support self-service BI and scalable data science programs.
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Who should watch

Data and analytics leaders and practitioners (including Chief Data Officers, data scientists, business intelligence, and analytics professionals) who are looking to make data more accessible to everyone in their organization.

Contributors Include

Gal Barnea AWS Redshift AtScale Technical Partner
Gal Barnea

Database Engineering Lead, Amazon Redshift at AWS

Gal leads the Database Engineering team at Amazon Redshift. In this capacity, Gal works closely with Redshift’s most strategic customers word-wide to optimize and maximize the business value they gain from their data warehouse. During his career, Gal built & lead engineering teams oversaw large-scale data and analysis initiatives and worked with some of the world’s largest brands. In his spare time, Gal enjoys cycling in the Bay Area hills and following way too much sports.