Remove Amazon Web Services Remove Architecture Remove Cloud Storage Remove Data Preparation
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Cloudera Data Platform extends Hybrid Cloud vision support by supporting Google Cloud

Cloudera

The addition of support for Google Cloud enables Cloudera to deliver on its promise to offer its enterprise data platform at a global scale. CDP Public Cloud is already available on Amazon Web Services and Microsoft Azure. Data Preparation (Apache Spark and Apache Hive) .

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Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

For building data lakes, the following technologies provide flexible and scalable data lake storage : . Amazon Web Services S3 . Gen 2 Azure Data Lake Storage . Cloud storage provided by Google . Data lakes can also be organized and queried using other technologies, such as

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AWS vs GCP - Which One to Choose in 2023?

ProjectPro

Google launched its Cloud Platform in 2008, six years after Amazon Web Services launched in 2002. Amazon brought innovation in technology and enjoyed a massive head start compared to Google Cloud, Microsoft Azure , and other cloud computing services. Let’s get started!

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15+ Best Data Engineering Tools to Explore in 2023

Knowledge Hut

Power BI Power BI is a cloud-based business analytics service that allows data engineers to visualize and analyze data from different sources. It provides a suite of tools for data preparation, modeling, and visualization, as well as collaboration and sharing. Some of its key features are mentioned here.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

There are open data platforms in several regions (like data.gov in the U.S.). These open data sets are a fantastic resource if you're working on a personal project for fun. Data Preparation and Cleaning The data preparation step, which may consume up to 80% of the time allocated to any big data or data engineering project, comes next.