Webinars

Archived Webinar

Apache Spark: The New Enterprise Backbone for ETL, Batch and Real-time Streaming

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 data into the lake and also for processing the data on the lake.

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Streaming Analytics for IoT with Apache Spark

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.

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Anomaly Detection: Real World Scenarios, Approaches, and Live Implementation

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.

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Apache Spark Empowering the Real-time, Data Driven Enterprise: The De Facto Choice for Stream Processing and Machine Learning

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.

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The Structured Streaming Upgrade to Apache Spark and How Enterprises Can Benefit

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.

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Real-time Data360 on Apache Spark

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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Self Service Pre-built Pipelines for Building Real-time Streaming Apps

Self Service Pre-built Pipelines for Building Real-time Streaming Apps

Streaming analytics is fast becoming a must-have technology for enterprises seeking to gain competitive advantage from Data.

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Partner Webinar - With Fannie Mae, Hortonworks and Impetus: The Business Impact of Fast Data Analytics

Partner Webinar - With Fannie Mae, Hortonworks and Impetus: The Business Impact of Fast Data Analytics

The promise of big data is greater than ever befor due to an explosion in the number and variety of data sources. This has caused a shift from traditional structured, and batch or periodic data warehouse environments to today's more complex combination of structured with semi & unstructured data, along with the requirement to apply analytics in real-time.

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Spark Streaming Made Easy!

Spark Streaming Made Easy!

Real-time streaming analytics and IoT seem to be the next big thing in the data and analytics industry. As enterprises adopt Apache Spark and Spark Streaming widely, IT teams are facing the challenge to provide the tools and the framework needed to make Apache Spark Streaming an easy-to-use, robust, scalable and multi-tenant service.

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Harnessing the Firehose: Getting Business Value from Streaming Analytics

Harnessing the Firehose: Getting Business Value from Streaming Analytics

The Briefing Room with Dr. Robin Bloor, Dez Blanchfield and StreamAnalytix- Impetus Technologies

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