Citrix Moves Data to Amazon Redshift Fast with Matillion ETL

Citrix, a Fortune 1000 multinational software company, needed to migrate massive amounts of data generated by its FileShare platform to Amazon Redshift, where it could perform data analytics to help inform product improvements and drive success. To do this, Citrix needed an Extract, Transform, and Load (ETL) solution. Matillion ETL, easily deployable from Amazon Web Services (AWS) Marketplace, helps Citrix collate and summarize data and augment it with more traditional business data from Microsoft SQL Server for additional context. Join our webinar to learn how organizations of any size can move data to the cloud quickly, accurately, and affordably with Matillion ETL.
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Spotlight

OTHER ON-DEMAND WEBINARS

The Semantic Layer’s Critical Role in Modern Data Architectures

Many of the most exciting innovations and advancements in data management today are occurring within the semantic layer of data architectures. For example, we’re witnessing new or improved approaches to semantic modeling, data cataloging, data lineage, and more. Even older forms of semantics—such as metadata and virtualization—are being infused with new techniques for augmentation and automation, including intelligent tool algorithms driven by machine learning and the use of graph analytics to generate data maps and automatically document data elements found via graph.
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How to Modernize Data Lake Technologies with Cloud-Based Solutions

tdwi.org

Data lakes based on Hadoop technologies have proved themselves valuable in mission-critical use cases such as data warehousing, advanced analytics, multichannel marketing, complete customer views, digital supply chains, and the modernization of data management.Most Hadoop users are committed to the data lake method of managing data, but they are limited by Hadoop shortcomings in key areas such as cluster maintenance, administration cost, resource management, metadata management, and support for SQL and other relational technologies. Many view cloud-based solutions as the optimal replacement for their data lake, but they are not ready to make such a significant change. The truth is: they don't have to, as the two technologies can coexist.
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What is Anomaly Detection and its Role in Preventative Analytics

DataRPM

Equipment downtime is a multi-billion-dollar problem which will only continue to grow with exploding sensor data. According to IDC, by 2018 a third of industrial companies will be disrupted by “Industrial IoT enabled competitors.” So how can companies monetize their IoT investments for higher operational efficiencies and productivity? Anomaly Detection and Prediction is the silver bullet that companies need to maximize their machine uptime and performance. Watch the on-demand webinar featuring the Dean of Big Data, Bill Schmarzo, Chief Technology Officer, Big Data at Dell EMC and Seth Page, General Manager and Head of Partnerships at Progress DataRPM, to learn how zero factory downtime can be a reality.
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Data Catalogs are Essential But Can they be Fun?

alation.com

In an age of data lakes, enterprise data catalogs are becoming a necessity. Done right, machine learning data catalogs can facilitate discoverability and ensure compliance while fostering the user engagement needed to build a robust data culture. In this webinar, Andrew Brust, analyst at GigaOm Research, and Aaron Kalb, co-founder and chief data officer at Alation, discuss why people are an essential part of successful self-service analytics, and how data catalogs can help foster collaboration and analytics enthusiasm.
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