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How to Build a Data Pipeline in 6 Steps

Ascend.io

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

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Why Data Governance Matters, Best Practices, and How to Build a Strategy

Monte Carlo

With the rise of GDPR and other compliance measures, data security is under more scrutiny than ever before. Yet as organizations invest in more data and more data accessibility, keeping all that data safe and well-maintained has never been more challenging. Table of Contents What is data governance?

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How to Keep Your Project Moving During the Coronavirus Outbreak

Knowledge Hut

While the World Health Organization (WHO) works with leaders from every nation to discover initiatives to precisely analyze, adequately contain, and build up a fitting response for this infection, workplaces are gearing up approaches to effectively deal with issues related to their projects.

Project 98
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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 1: The Set-Up & Basics

Cloudera

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle.

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Upgrade your Modern Data Stack

Christophe Blefari

We need to store, process and visualise data, everything else is just marketing. I often say that data engineering is boring, insanely boring. When you are a data engineer you're getting paid to build systems that people can rely on. Is the modern data stack dying? Something boring. Cloud-first.

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Data Science vs Cloud Computing: Differences With Examples

Knowledge Hut

These servers are primarily responsible for data storage, management, and processing. All cloud models and resources can be accessible from the internet. Access to these resources is possible using any browser software or internet-connected device. Cloud Computing Services can be accessed with the help of the internet.

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How Much Data Do We Need? Balancing Machine Learning with Security Considerations

Towards Data Science

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.