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Webinar – Agile Approaches to Data Warehouse Modernization
December 11, 2015 Blog Big Data webinar

Webinar Abstract

Time is 10pm KL & Singapore time on November 17th  – Click here to register

TDWI Speaker:David Loshin, President of Knowledge Integrity

Date: Tuesday, November 17, 2015

Time: 6:00 a.m. PT, 9:00 a.m. ET  (!0pm Singapore & KL Time)

The conventional approach to data warehousing may satisfy conventional reporting and straightforward analytical needs. Yet outside of the enterprise data warehouse, the information world has rapidly evolved and changed – there are new data sources, streaming different kinds of data, all coming at faster speeds. While we trust our existing data warehouse platforms to meet existing business needs, how can we integrate new technologies to address new business challenges without disrupting the consumers who rely on the trust and security of the established reporting and analysis platforms and applications?

In this webinar we explore the motivations for adopting new technology, consider the organizational and pragmatic challenges to bringing new stuff in, and discuss how to balance adoption into a hybrid environment that can both satisfy the growing cadre of data scientists and not disrupt the existing technical environment trusted by existing data consumers. We will consider alternatives to the conventional data warehouse architecture, including specialty appliances, open source high performance platforms, the need for real-time analytics, and contrast on-premises with growing interest in cloud-based and hosted business analytics architectures. We will particularly focus on blending data warehouse augmentation using Hadoop, and how modern data warehouse applications can best take advantage of Hadoop and similar technologies to rapidly satisfy the business needs for reporting and analysis.

Attendees will learn about:

  • Motivating the adoption of new technology
  • The concept of a logical data warehouse
  • Using a data lake or data reservior
  • The role of data federation and data virtualization
  • Developing a plan for modernization
  • Architecting the hybrid reporting and analytics environment