AltexSoft

SEPTEMBER 10, 2021

What is data integration and why is it important? Data integration is the process of taking data from multiple disparate internal and external sources and putting it in a single location (e.g., data warehouse ) to achieve a unified view of collected data. Key types of data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Ascend.io

DECEMBER 14, 2022

Today, a good part of the job of a data engineer is to move data from one place to another by creating pipelines that can be either ETL vs. ELT. However, with the advent of cloud-based infrastructure, ETL is changing towards ELT. ETL has been the traditional way to manage pipelines for decades. This is when ELT came in.

Data Integration 52

Data Integration Raw Data Data Consolidation Data Warehouse 52

Ascend.io

DECEMBER 21, 2022

Now, data teams are embracing a new approach: reverse ETL. Cloud data warehouses, such as Snowflake and BigQuery, have made it simpler than ever to combine all of your data into one location. Today, data teams build ELT pipelines to load the data. Make your data operational. Prevent data silos.

ETL Tools 52

ETL Tools ETL System Data Warehouse Data Consolidation 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. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Data virtualization vs data consolidation.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

JUNE 16, 2022

It enables flow from a data lake to an analytics database or an application to a data warehouse. Amazon Web Services (AWS) offers an AWS Data Pipeline solution that helps businesses automate the transformation and movement of data. The destination can be a data lake or data warehouse.

Data Pipeline 59

Data Pipeline AWS Amazon Web Services Data Consolidation 59

ProjectPro

DECEMBER 7, 2021

To understand the working of a data pipeline, one can consider a pipe that receives input from a source that is carried to give output at the destination. A pipeline may include filtering, normalizing, and data consolidation to provide desired data. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52