Big Data and Analytics: Why You Need a Platform

IBM

Big data is all about delivering value from advanced analytics and a single version of truth at all scales. It’s time to discuss the growing role of data warehousing within your big data analytics ecosystem. Hear James Kobielus, IBM Big Data Evangelist, outline the major components, tool suites, databases, and industry approaches for leveraging of data warehouses within the astonishingly innovative big-data universe.
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Spotlight

As Hadoop and the SQL-on-Hadoop engines mature, leading enterprises are throwing on more diverse workloads and getting highly performant results. Hadoop is no longer relegated to a platform for data science or batch processing - now companies are also pushing traditional Business Intelligence workloads to Hadoop as well.


OTHER ON-DEMAND WEBINARS

Accelerate Decision Making with Real-Time Analytics on AWS

Amazon Web Services, Inc

The number of sources generating continuous, streaming data has exploded in recent years. From website clickstream data to telemetry data from Internet of Things (IoT) devices, the variety, volume, and velocity of data continues to increase. In response, businesses are evolving their analytics approach from batch to real time, and turning to new tools to deliver actionable insights in seconds instead of hours or days. With AWS, you can easily and cost-effectively collect, process, and analyze real-time streaming data at any scale, so you can learn what your applications and customers are doing right now—and respond immediately.
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Building Real-Time BI Systems With Kafka, Spark, And Kudu

Zoomdata

One of the key challenges in working with real-time and streaming data is that the data format for capturing data is not necessarily the optimal format for ad hoc analytic queries. For example, Avro is a convenient and popular serialization service that is great for initially bringing data into HDFS.
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Self-Service Big Data Preparation for Business Users

This webinar discusses how business users can prepare, integrate and cleanse big data – all without having to write code or attend costly training. SAS Data Loader for Hadoop is a new offering that enables you to overcome the gap in available Hadoop skills, unshackle IT and speed access to big data.
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Is Big Data a Big Deal...or Not?

Health Catalyst

The term “Big Data” emerged from Silicon Valley in 2003 to describe the unprecedented volume and velocity of data that was being collected and analyzed by Yahoo, Google, eBay, and others. They had reached an affordability, scalability and performance ceiling with traditional relational database technology that required the development of a new solution, not being met by the relational data base vendors. Through the Apache Open Source consortium, Hadoop was that new solution. Since then, Hadoop has become the most powerful and popular technology platform for data analysis in the world.
Watch Now

Spotlight

As Hadoop and the SQL-on-Hadoop engines mature, leading enterprises are throwing on more diverse workloads and getting highly performant results. Hadoop is no longer relegated to a platform for data science or batch processing - now companies are also pushing traditional Business Intelligence workloads to Hadoop as well.

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