U-Next

SEPTEMBER 7, 2022

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

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

OCTOBER 21, 2022

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Kafka vs Hadoop.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

AUGUST 24, 2021

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. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

DECEMBER 7, 2021

In addition, to extract data from the eCommerce website, you need experts familiar with databases like MongoDB that store reviews of customers. Airflow also allows you to utilize any BI tool, connect to any data warehouse, and work with unlimited data sources.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52