Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

ODSC - Open Data Science

JANUARY 11, 2024

Getting Started with AI in High-Risk Industries, How to Become a Data Engineer, and Query-Driven Data Modeling How To Get Started With Building AI in High-Risk Industries This guide will get you started building AI in your organization with ease, axing unnecessary jargon and fluff, so you can start today.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

IBM Journey to AI blog

OCTOBER 22, 2024

Scalable data pipelines: Seasoned data teams are facing increasing pressure to respond to a growing number of data requests from downstream consumers, which is compounded by the drive for users to have higher data literacy and skills shortage of experienced data engineers.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Alation

MAY 24, 2022

This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. The Lineage & Dataflow API is a good example enabling customers to add ETL transformation logic to the lineage graph.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

phData

AUGUST 10, 2023

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Having model-level data validations along with implementing a data observability framework helps to address the data vault’s data quality challenges.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52