In this blog post, I’m going to talk you through how we created a framework to solve a problem. I’ll start by defining the problem, talk you through the framework we built as the solution,
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This is the second article in a five part series on data integration. The series covers the following foundational topics: Data-Oriented Programming needs Data Integration – App and format...
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The Matillion ETL data integration platform continues to get better in Version 1.61! Keep reading for highlights and details in this newest version DataOps enhancements We love supporting our...
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To help deliver consistently quick and scalable value from data, it is vital that data processing pipelines are resilient against change and accessible to all. This is the first article in a
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Wondering what the new year has in store for your data management operations? Paul Lacey and Mark Balkenende, Senior Directors of Product Marketing for Matillion, tackled the topic in a webinar...
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We are surrounded by ever more diverse sets of data. Much of this data is already distributed into the cloud, hosted by a rapidly expanding family of SaaS applications. Data sources underpin the
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The enterprise data universe is expanding exponentially. What used to be a relatively small number of data sources has exploded to thousands of potential sources, and there is no end in sight. The
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We’re back in Vegas! After a year off, AWS re:Invent 2021 is happening, starting on November 29 and running through December 2. Around 20,000 people are expected to attend this year’s event, and...
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In the journey towards gaining value from data, it’s common to convert between formats. As discussed in this article, often it involves using Matillion to move data along the path from...
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We all know that enterprises struggle to keep pace with the complexity and volume of data. But a new survey of 450 data professionals at large enterprise organizations indicates a critical...
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Enterprises are dealing with an unprecedented influx of data, and forecasts indicate that growth will continue at an even faster pace in years to come. Working effectively and strategically with...
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Three kinds of data – structured, unstructured and semi-structured – are regularly used in data warehousing. They are typically used at distinct stages of processing, and different techniques...
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When performing data extraction, organizations retrieve data from various sources–including databases, legacy systems, online transactions, software as a service (SaaS) platforms, web pages, and...
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What is a Data Pipeline? A data pipeline tool manages the flow of data from an initial source to a designated endpoint. An organization’s specific use cases, needs, and requirements determine...
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What is machine learning used for? Machine learning has been around for decades, but in the era of Big Data, this type of artificial intelligence is in greater demand than ever before. Why? Simply...
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The Gartner® Magic Quadrant™ is out for 2021, and Matillion is very excited to be named again in the 2021 Gartner Magic Quadrant for Data Integration Tools. As always, it’s a huge honor to
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Azure DevOps is a highly flexible software development and deployment toolchain. It integrates closely with many other related Azure services, and its automation features are customizable to an...
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An interesting thing has happened with the rise of cloud data platforms. While our data warehouses and data lakes modernized and moved to the cloud, most ETL platforms did not. Traditional ETL...
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In the latest release of Matillion Data Loader, even more of our connectors have schema drift support! Since our announcement of schema drift support, our goal has been to incorporate this...
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We’re excited to announce that Matillion Data Loader v1.23 is here! In this latest release, we have a few new connectors, and a load of pipelines that are now editable and/or support Schema
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