DEMYSTIFYING DATA SCIENCE

analytics8.com

Most companies know that data science and machine learning can have a profound impact on their business, but they often struggle on where to start and how to augment their existing analytics solutions with advanced analytics. Check out this webinar to learn more about data science and machine learning it is not as hard as you may think to get started; and once you do, you will see immediate business value.
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Spotlight

To help reduce massive power demands, many data centers are increasingly using liquid cooling to complement or even replace air cooling systems. The leading provider of closed-loop liquid cooling systems for data centers, Asetek, uses thermal simulation with ANSYS Icepak to optimize cooling system components.

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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How to Build a Data Catalog to Smartly Exploit Your Data Assets

Caserta

Register for this on-demand webinar with the co-founder of Alation where we’ll deep dive into the Data Catalog. You’ll learn why a data catalog is essential for data-driven organizations, methods and tools to democratize your data, and how automation is crucial for consistent re-use of data.
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Planning for a Scalable Enterprise Data Lake

tdwi.org

In this webinar we will discuss a more modern view of the data lake and consider best practices for planning and implementing a scalable enterprise data lake. The flaws in early data lakes were often rooted in the expectations of data consumers who put a premium on self-service data analytics. However, with no data governance mechanisms, data lakes quickly became more of a glorified “dumping ground,” “data swamp,” or “beta lake” for organizational data.In recent years, though, some innovations have allowed the data lake to evolve into an agile yet managed environment for accumulating shared data resources that can be optimally used for competitive advantage. Data lakes have evolved beyond the original on-premises concept based solely on Hadoop and now include pretty much any distributed computing platform (Hadoop, Spark, EMR, serverless, etc.) and any storage mechanism (HDFS, S3, ADLS), either on-premises or in the cloud.
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Modernizing the Legacy Data Warehouse – What, Why, and How

cloudera

The Eckerson Group's Dave Wells and Cloudera's Eva Nahiri share the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
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Spotlight

To help reduce massive power demands, many data centers are increasingly using liquid cooling to complement or even replace air cooling systems. The leading provider of closed-loop liquid cooling systems for data centers, Asetek, uses thermal simulation with ANSYS Icepak to optimize cooling system components.

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