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How DataOS Nails Gartner’s Magic Quadrant for Data Integration

The Modern Data Company

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. Data engineering excellence Modern offers robust solutions for building, managing, and operationalizing data pipelines.

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How DataOS Nails Gartner’s Magic Quadrant for Data Integration

The Modern Data Company

The Modern Data Company has been given an honorable mention in Gartner’s 2023 Magic Quadrant for Data Integration. This capability is instrumental in meeting the analytical demands of various data applications, including analytics, business intelligence (ABI), and data science.

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Leading The Charge For The ELT Data Integration Pattern For Cloud Data Warehouses At Matillion

Data Engineering Podcast

Summary The predominant pattern for data integration in the cloud has become extract, load, and then transform or ELT. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

AltexSoft

What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. The good news is, businesses can choose the path of data integration to make the most out of the available information. Data integration in a nutshell. Data integration process.

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Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

AltexSoft

To get a single unified view of all information, companies opt for data integration. In this article, you will learn what data integration is in general, key approaches and strategies to integrate siloed data, tools to consider, and more. What is data integration and why is it important?

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A Year of Modern: Our Top 2022 Blog Posts — Chosen by You

The Modern Data Company

This post highlights exactly how our founders taught us to think differently about data and why it matters. Here are the cornerstones of this new paradigm: Data ownership is a construct Data pipelines should be accessible to everyone Data products should adapt to the organization, not vice versa.

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5 Real-world Examples of Companies Using Striim for Real-Time Data Analytics

Striim

According to a recent study by KX, US businesses could see a total revenue uplift of $2.6 trillion through investment in real-time data analytics. From telecommunication to retail, businesses are harnessing the power of data analytics to optimize operations and drive growth.