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 Scala 52

Knowledge Hut

NOVEMBER 17, 2023

You ought to be able to create a data model that is performance- and scalability-optimized. Programming and Scripting Skills Building data processing pipelines requires knowledge of and experience with coding in programming languages like Python, Scala, or Java.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS Scala Data Lake ETL Tools 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. Learn about well-known ETL tools such as Xplenty, Stitch, Alooma, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

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 96

Data Science BI Business Intelligence Data Mining 96

Edureka

FEBRUARY 9, 2023

Data engineers must be well-versed in programming languages such as Python, Java, and Scala. The most common data storage methods are relational and non-relational databases. Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Relational and non-relational databases are among the most common data storage methods. ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52