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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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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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Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

Data lakes, however, are sometimes used as cheap storage with the expectation that they are used for analytics. For building data lakes, the following technologies provide flexible and scalable data lake storage : . Amazon Web Services S3 . Gen 2 Azure Data Lake Storage .

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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

Then, the Yelp dataset downloaded in JSON format is connected to Cloud SDK, following connections to Cloud storage which is then connected with Cloud Composer. Cloud composer and PubSub outputs are Apache Beam and connected to Google Dataflow. There are three stages in this real-world data engineering project.

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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.