ProjectPro

FEBRUARY 8, 2023

Data Integration and Transformation, A good understanding of various data integration and transformation techniques, like normalization, data cleansing, data validation, and data mapping, is necessary to become an ETL developer. Informatica PowerCenter: A widely used enterprise-level ETL tool for data integration, management, and quality.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Ascend.io

AUGUST 31, 2023

Services like AWS Glue , Databricks , and Dataproc have powerful data lake capabilities, where code-heavy processes and agile workflows can transform data into many different forms. There are a range of tools dedicated to just the extraction (“E”) function to land data in any type of data warehouse or data lake.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

DECEMBER 7, 2021

The Importance of a Data Pipeline What is an ETL Data Pipeline? Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

dbt Developer Hub

NOVEMBER 22, 2022

Below is a summary table highlighting the core benefits and drawbacks of certain ETL tooling options for getting spreadsheet data in your data warehouse. It’s also the most provider-agnostic, with support for Amazon S3, Google Cloud Storage, Azure and the local file system.

Data Warehouse 52

Data Warehouse ETL Tools Google Cloud Cloud Storage 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Snowflake is the pioneer in cloud data warehousing.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Edureka

FEBRUARY 9, 2023

Every year, Azure’s usage graph grows, bringing it closer to AWS. These businesses are transferring their data and servers from on-premises to the Azure Cloud. 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

NOVEMBER 30, 2021

Cloud: Technology advancements, information security threats, faster internet speeds, and a push to prevent data loss have contributed to the move toward cloud-native storage and processing. ETL Pipeline Tools Here are some popular tools for building ETL (Extract, transform, and Load) data pipelines.

Process 52

Process Data Pipeline Data Warehouse AWS 52