Data Science Dojo

JULY 3, 2024

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Cloud Computing : Utilizing cloud services for data storage and processing, often covering platforms such as AWS, Azure, and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

ODSC - Open Data Science

JUNE 19, 2023

Scalable and flexible infrastructure  — Processing big data requires an infrastructure that adapts to rapidly growing processing needs and different scenarios of data storage and usage. This entails the use of other technologies such as distributed computing, edge computing, and cloud computing.

Big Data 96

Big Data Big Data Artificial Intelligence Artificial Intelligence 96

Alation

JANUARY 17, 2023

Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? A Note on the Shift from ETL to ELT.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Dataconomy

FEBRUARY 23, 2023

This involves creating data validation rules, monitoring data quality, and implementing processes to correct any errors that are identified. Creating data pipelines and workflows Data engineers create data pipelines and workflows that enable data to be collected, processed, and analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Precisely

APRIL 6, 2023

That creates new challenges in data management and analytics. Each new system comes with its own schema, which must be mapped and normalized alongside other data. The best integration tools make it easy to build and deploy data pipelines to accommodate the ever-changing needs of modern financial services organizations.

Data Quality 52

Data Quality Data Pipeline Analytics Analytics 52

The MLOps Blog

DECEMBER 7, 2022

The inherent cost of cloud computing : To illustrate the point, Argentina’s minimum wage is currently around 200 dollars per month. And that’s when what usually happens, happened: We came for the ML models, we stayed for the ETLs. First of all, the origin of the data comes from the two biggest exchanges.

ML 52

ML ML AWS ETL 52