Webinars

Archived Webinars

Jun 14, 2019

Build Spark-based ETL Workflows on Cloud in Minutes :

Learn how you can visually design and manage Spark-based workflows on Amazon EMR and Databricks with StreamAnalytix

ETL on cloud is more relevant than ever, as most businesses now operate either partially or fully in the cloud. However, there’s a lack of solutions that can simplify and automate the complex cloud ETL process. Moreover, traditional tools are unable to leverage cloud-native services on Amazon EMR or Databricks.

Apr 12, 2019

Instantly Convert Teradata ETL and EDW to Spark – On Cloud or On-premise : Teradata has been a popular choice for analytical data processing. As data complexity increases, more and more enterprises need the flexibility and scalability advantages of ‘modern data architecture’ technologies. The sophisticated algorithmic and statistical analytics, and interoperability, would also enable businesses to handle vast and complex data at high speeds.

Mar 08, 2019

An Easy Approach to ETL with Apache Spark - Visually prepare, integrate, and transform data as it arrives : Executing analytical queries on massive data volumes with traditional databases and batch ETL processes is complex, expensive, and time-consuming.

Jan 25, 2019

Solving the EDW Transformation Conundrum : Enterprises looking to modernize the data warehouse have been facing the dilemma of choosing between migration of legacy systems and total re-engineering. While migrating the systems as is is not the best transformation choice for all workloads, total re-engineering can be complex and disrupt business processes.

Dec 19, 2018

Planning your Next-Gen Change Data Capture (CDC) Architecture in 2019 :

Traditional databases and batch ETL operations have not been able to serve the growing data volumes and the need for fast and continuous data processing.

Nov 30, 2018

EDW Transformation - A Retrospective and Outlook : The enterprise data warehouse (EDW) has been the heart of decision support for more than two decades. But the game has now changed. The new age of advanced data analytics is placing bold demands on all aspects of our current infrastructure, platforms, architecture, tools, and management processes. Our essential ability to manage new data and fast data at massive scale will determine how quickly we can evolve to being real-time, data driven businesses.

Oct 17, 2018

Apache Spark: The New Enterprise Backbone for ETL, Batch and Real-time Streaming : In spite of investments in big data lakes, there is wide use of expensive proprietary products for data ingestion, integration, and transformation (ETL) while bringing and processing data on the lake.

Oct 12, 2018

Transforming Real-time Customer 360 with Apache Spark :

Enterprises have realized that a consistent, complete and real-time view of customers across systems and channels is the key to transform the customer experience. However, achieving an accurate and real-time customer 360 view is challenging.

Jul 26, 2018

Streaming Architecture: Top Ten Requirements To Evolve To A Real-time Enterprise : Streaming data ingestion, ETL, and integration along with real-time machine learning are becoming more and more critical capabilities as enterprises look to create and monetize the real-time enterprise.

May 03, 2018

Operationalizing Enterprise 360 - Create a Single Source of Truth : Complex and fragmented data systems make it challenging to define a 'single source of truth' for data that provides a comprehensive single view of the enterprise. Enterprises are pushing for higher levels of data integrity that can drive business insights quickly and easily up and down and across the enterprise.

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