Pickl AI

NOVEMBER 4, 2024

It enables reporting and Data Analysis and provides a historical data record that can be used for decision-making. Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

OCTOBER 10, 2024

It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments. Typical use cases include ETL (Extract, Transform, Load) tasks, data quality enhancement, and data governance across various industries.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

The MLOps Blog

MAY 31, 2023

The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data. How to set up a data processing platform?

ML 59

ML ML Algorithm Machine Learning 59

Alation

FEBRUARY 20, 2020

Business Intelligence used to require months of effort from BI and ETL teams. More recently, we’ve seen Extract, Transform and Load (ETL) tools like Informatica and IBM Datastage disrupted by self-service data preparation tools. First, there is no easy way to find the data you want to prepare.

ETL 52

ETL Hadoop Tableau Data Scientist 52

Alation

FEBRUARY 20, 2020

With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. The infrastructure to support the ‘logical data warehouse’ is deployed already from Presto to Teradata UDA, etc.

Data Warehouse 52

Data Warehouse Hadoop Data Science ETL 52