What are the Basics of ETL Testing?
Now that more organizations are using ETL tools and processes to integrate and migrate their data, the obvious next step is learning more about ETL testing to confirm that these processes are...
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How to take the pain out of batch data loading
Data architects create the strategy and infrastructure design for the enterprise data environment. Data engineers help implement this strategy. They design, build, and manage data pipelines to...
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Near-real time data loading with change data capture
Gone are the days when data could only be analyzed after the nightly, hours-long batch loading completed. Data today is dynamic—it changes constantly throughout the day. Modern enterprises and...
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How to supercharge data team productivity
One of the most frustrating times for a data analyst and a business decision maker is waiting on data. Without data, the world stops, and there is not much they can do about it. IT
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Delta Lake on Databricks: CDC and Batch Ingestion with Matillion Data Loader
As enterprises strive to become data-driven, choosing a cloud data environment is an important strategic decision. The Databricks Lakehouse Platform combines the data structure and data management...
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Matillion at Snowflake Summit 2022: 5 Things You Don’t Want to Miss
It’s almost time for Snowflake Summit 2022! Next week, Matillion will be headed to Las Vegas for the first live Snowflake Summit in two years. We’re proud and excited to be a Double
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How Matillion Built a Framework for Extracting Data from Any API
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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Creating Highly Consumable Quality Data with Data Integration
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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Matillion ETL 1.61 Release: DataOps and GIT Integration Enhancements
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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“Data-Oriented Programming Needs Data Integration”
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 five
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5 Key Data Trends to Watch For in 2022
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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Top 5 Low-Code / No-Code Data Integration Features for Data Teams
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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Bringing Data Pipelines to the Enterprise with Matillion Data Loader 2.0
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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5 Things Not to Miss at AWS re:Invent 2021
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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Data Vault vs Star Schema vs Third Normal Form: Which Data Model to Use?
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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New Survey Results: 5 Ways that Outdated Data Processes are Costing Data Teams Time and Money
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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An Introduction to Data Ingestion
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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Looking at Structured, Unstructured, and Semi-Structured Data (with examples)
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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What is Data Extraction? Everything You Need to Know
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? Why to Use Them, Different Types, and Standard Components
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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