Cloud platforms offer compelling advantages to data delivery teams looking to bring more agility and simplicity to their enterprise data preparation and delivery process.
Learn the best practices that drive a successful data lake implementation.
When implemented as part of an integrated end-to-end data management process in the lake, data catalogs are the key to managing big data at scale and delivering business ready data to users for self-service on-demand access.
Learn the pros and cons of various cloud, on prem and hybrid data lake deployment models.
Learn how you can now catalog, access and control all of your data, on any platform, anywhere — on demand.
Learn how to increase leverage and ROI from investments in real world evidence (RWE) data by empowering business teams to build their own RWE data sets on a self-service, on-demand basis. Features a case study from Astellas Pharma.
Podium Data’s CTO, Bob Vecchione, shares best practice approaches to securing PII data in a data lake.
Presenters Sunil Soares, Founder & Managing Partner at Information Asset, and Dr. Paul Barth, CEO at Podium Data, discuss new principles and best practices for big data governance.
In this webinar, Podium Data and guest Principal Analyst at Forrester Research, Michele Goetz, discuss how companies can accelerate data to maximize business impact.
Imagine the power and impact of shopper-like services for analysts seeking data. Finding the right data quickly is essential in the age of self-service analytics.
This webinar addresses the essential capabilities required to build a successful enterprise-scale data lake that accelerates data delivery to business users and expands analytic insights and agility across the organization.
In this recorded webinar, Paul Barth discusses how a leading pharmaceutical company is accelerating delivery of analytic data to their marketing analysts by migrating their data from a data warehouse appliance to a hosted Hadoop data lake.
Why the “Build It Here” approach to Data as a Service deployment might take longer and cost WAY more.
This interactive discussion will explore in detail what it takes to make a data lake that is truly enterprise ready.