ProjectPro

JANUARY 27, 2023

Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange. This indicates the growing use of the ETL process and various ETL tools and techniques across multiple industries.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

NOVEMBER 17, 2023

Database Knowledge Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you. This involves knowing how to manage data partitions, load data into a data warehouse, and speed up query execution.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 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. ETL activities are also the responsibility of data engineers.

Certification 52

Certification Data Engineer Data Engineering Engineering 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 ETL Tools Data Lake Scala 52

Knowledge Hut

DECEMBER 26, 2023

They use tools like Microsoft Power BI or Oracle BI to develop dashboards, reports, and Key Performance Indicator (KPI) scorecards. They should know SQL queries, SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) and a background in Data Mining and Data Warehouse Design.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

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 Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52