By using tdwi.org website you agree to our use of cookies as described in our cookie policy. Learn More

RESEARCH & RESOURCES

Available On-Demand - This webinar has been recorded and is now available for download.

Fireside Chat: Delivering Scalable Data Analytics in the Cloud

Webinar Speaker: James Kobielus, Senior Research Director, Data Management

Date: Tuesday, June 6, 2023

Time: 12:00 p.m. PT / 3:00 p.m. ET

Success in the modern economy depends on an enterprise’s ability to deliver high-quality data and analytics into production applications. In order to keep pace with fast-changing business requirements, enterprises need to address key technical challenges such as eliminating data and analytics silos, moving data engineering and machine learning assets to modern cloud infrastructures, and ensuring that the enabling cloud platforms can scale elastically to support mission-critical workloads.

Enterprises everywhere are migrating their data analytics assets to cloud-based platforms and pipelines that offer greater scalability, performance, flexibility, and cost-effectiveness. Typically accessed on a fully managed, pay-as-you-go basis, modern cloud data platforms can support both structured and unstructured data assets. In addition to supporting conventional ETL-based data integration, modern cloud data infrastructure can also provide real-time and low-latency analytics, automated data onboarding and integration, orchestrated data pipelines, data engineering and preparation, self-service data delivery, embedded analytical models, and other sophisticated features.

Join TDWI senior research director James Kobielus and invited guests Kiran Guduguntla from Amazon Web Services and Jonathan Steinert from Accenture in a fireside chat where they discuss:

  • What are the principal steps in an enterprise migration of data and analytics to the cloud?
  • What role can a high-performance cloud computing environment play in advancing enterprise data modernization and digital transformation?
  • How should enterprises architect their cloud environments to handle growing data and analytics workloads?
  • What are the principal approaches for improving the cost-efficiency, self-service accessibility, and programmability of cloud-based data and analytics resources for enterprise use cases?

Guest Speaker

Kiran Guduguntla
Worldwide Go-to-Market Specialist for Amazon EMR
AWS

Kiran is a worldwide go-to-market specialist for Amazon EMR at AWS. He works with AWS customers across the globe to strategize, build, develop, and deploy modern data analytics solutions leveraging Amazon EMR service.

Jonathan Steinert
Accenture AWS Business Group (AABG) Lead, Data & AI Architect
Accenture

Jonathan has been working with clients across industries to solve the improbable by scouring out the root of the data-led transformation journey. He’s a strategically focused professional that is comfortable advising enterprise clients on their global AWS cloud data journey. He invested his last 10 years into data-driven decision-making and custom software development as a certified Master Technology Architect and certified AWS Solution Architect Professional. He’s worked cross-industry to find the unique and mundane patterns of data ingestion, transformation, and persistence to ensure that the data that we collect is used to impact our business partners decision-making.

James Kobielus


Your e-mail address is used to communicate with you about your registration, related products and services, and offers from select vendors. Refer to our Privacy Policy for additional information.

TDWI Membership

Get immediate access to training discounts, video library, research, and more.

Find the right level of Membership for you.