Knowledge Hut

DECEMBER 26, 2023

They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

ProjectPro

JANUARY 24, 2023

A survey by Data Warehousing Institute TDWI found that AWS Glue and Azure Data Factory are the most popular cloud ETL tools with 69% and 67% of the survey respondents mentioning that they have been using them. Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples.

AWS 52

AWS Cloud Amazon Web Services ETL Tools 52

Knowledge Hut

NOVEMBER 17, 2023

Understanding data modeling concepts like entity-relationship diagrams, data normalization, and data integrity is a requirement for an Azure Data Engineer. You ought to be able to create a data model that is performance- and scalability-optimized.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 9, 2023

Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques. Learn about popular ETL tools such as Xplenty, Stitch, Alooma, and others. To store various types of data, various methods are used.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Knowledge Hut

SEPTEMBER 26, 2023

For the Azure certification path for data engineering, we should think about developing the following role-specific skills: Most of the data processing and storage systems employ programming languages. Programming languages like Python, Java, or Scala require a solid understanding of data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Big data pipelines must be able to recognize and process data in various formats, including structured, unstructured, and semi-structured, due to the variety of big data. Over the years, companies primarily depended on batch processing to gain insights.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Different methods are used to store different types of data. Who should take the certification exam?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52