Webinars

Archived Webinars

Oct 23, 2019

Keys to establish sustainable DW and Analytics on the Cloud :

Cloud adoption is inevitable to implement digital transformation and drive customer expectations. For a seamless transition of your analytical layer to modern cloud platforms, powerful automation is crucial at a process, code, and data level. However, this transition is not the end, but the beginning of creating sustainable business outcomes through a democratized and extensible data architecture. These outcomes are realized through the cloud architecture’s scaling options and the ease of advanced analytics, establishing a data-driven culture, and monetizing data for increased/new revenue.

Sep 27, 2019

Anomaly Detection with Machine Learning at Scale (India) : Organizations are collecting massive amounts of data from disparate sources. However, they continuously face the challenge of identifying patterns, detecting anomalies, and projecting future trends based on large data sets. Machine learning for anomaly detection provides a promising alternative for the detection and classification of anomalies.

Jul 26, 2019

Featuring Forrester - Keys to formulating an effective data management strategy in the age of data : Companies who are leaders in the digital transformation revolution have mastered how they manage data. In order to compete with them, it is important that all businesses have a comprehensive data management strategy. A solid data management strategy should address the needs of all areas of business – from operations, marketing, and sales to service, finance, and more. But how can enterprises formulate a strategy that provides all business functions with quick and complete access to the data, analytics, and machine learning that they need, both now and in the future?

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.

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