Data Engineering Podcast

NOVEMBER 4, 2021

Summary The precursor to widespread adoption of cloud data warehouses was the creation of customer data platforms. Acting as a centralized repository of information about how your customers interact with your organization they drove a wave of analytics about how to improve products based on actual usage data.

Data Warehouse 100

Data Warehouse Business Intelligence ETL System Data Lake 100

Grouparoo

OCTOBER 26, 2021

This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes. This may include a data warehouse when it’s necessary to pipeline data from your warehouse to various destinations as in the case of a reverse ETL pipeline.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 52

Grouparoo

FEBRUARY 9, 2022

ETL testing is also used to verify that the ETL process runs smoothly without any bottlenecks or major performance issues. The testing process is often performed during the initial setup of a data warehouse after new data sources are added to a pipeline and after data integration and migration projects.

Process 52

Process ETL System Data Warehouse Metadata 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. This can be easier when you are using existing cloud services.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 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.

ETL Tools 52

ETL Tools ETL System Data Warehouse Data Consolidation 52

Striim

AUGUST 31, 2023

Treating batch and streaming as separate pipelines for separate use cases drives up complexity, cost, and ultimately deters data teams from solving business problems that truly require data streaming architectures. Finally, kappa architectures are not suitable for all types of data processing tasks.

Data Integration 69

Data Integration Architecture Amazon Web Services ETL System 69

Precisely

APRIL 3, 2023

How can an organization enable flexible digital modernization that brings together information from multiple data sources, while still maintaining trust in the integrity of that data? To speed analytics, data scientists implemented pre-processing functions to aggregate, sort, and manage the most important elements of the data.

ETL System 52

ETL System Transportation Architecture Manufacturing 52