Webinars

Archived Webinars

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

Single Source of Truth in the Enterprise: From Mirage to Reality : 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.

Mar 21, 2018

Analyst Webinar: Is the Traditional Data Warehouse Dead? : There has been a steady drumbeat in some quarters that the traditional data warehouse is dead, even though it is a fixture at most organizations. Some insist it is too slow and cumbersome to support today’s fast-moving and data hungry organizations while others claim it’s still a critical piece of data infrastructure that companies can’t live without. Somewhere between these extremes lies the truth.

Feb 16 - 17, 2018

Streaming Analytics for IoT with Apache Spark : Modern IoT operations can drive digital transformation by analyzing the unprecedented amounts of data generated from devices and sensors in real-time.

Dec 15 - 16, 2017

Anomaly Detection: Real World Scenarios, Approaches, and Live Implementation : Detecting anomalous patterns in data can lead to significant actionable insights in a wide variety of application domains, such as fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.

Oct 13, 2017

Apache Spark Empowering the Real-time, Data Driven Enterprise: The De Facto Choice for Stream Processing and Machine Learning : Apache Spark is one of the most popular Big Data frameworks today. It is fast becoming the de facto technology choice for stream processing, real-time analytics, data science and machine learning applications at scale. It has moved well beyond the early-adopter phase, is supported by a vibrant open source community and is enjoying accelerated adoption in enterprises.

Aug 23, 2017

The Structured Streaming Upgrade to Apache Spark and How Enterprises Can Benefit : The adoption of Apache Spark to analyze data in real-time is increasing with its ability to handle sophisticated analytical requirements and a common framework for streaming and batch. However, most organizations are also looking for "true streaming" features like lower latency and the ability to process out-of-order data.

May 12, 2017

Real-time Data360 on Apache Spark : Data360 - is a new term and is being used to represent a one-stop shop for all your Big data processing needs.

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