Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. At the heart of this process lie ETL Tools—Extract, Transform, Load—a trio that extracts data, tweaks it, and loads it into a destination. Choosing the right ETL tool is crucial for smooth data management. What is ETL?

ETL 40

ETL Data Integration Data Quality Metadata 40

IBM Journey to AI blog

JULY 1, 2024

Irina Steenbeek introduces the concept of descriptive lineage as “a method to record metadata-based data lineage manually in a repository.” Extraction, transformation and loading (ETL) tools dominated the data integration scene at the time, used primarily for data warehousing and business intelligence.

ETL 100

ETL Automation Metadata Business Intelligence 100

IBM Journey to AI blog

JANUARY 18, 2023

While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale. Metadata plays a key role here in discovering the data assets. Differences exist also.

Data Platform 130

Data Platform ETL Metadata Data Discovery 130

ODSC - Open Data Science

SEPTEMBER 27, 2023

Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

The MLOps Blog

MARCH 15, 2023

In the case of our CI/CD-MLOPs system, we stored the model versions and metadata in the data storage services offered by AWS i.e ” Hence the very first thing to do is to make sure that the data being used is of high quality and that any errors or anomalies are detected and corrected before proceeding with ETL and data sourcing.

ETL 52

ETL Data Drift Machine Learning ML 52

AWS Machine Learning Blog

JUNE 25, 2024

When the automated content processing steps are complete, you can use the output for downstream tasks, such as to invoke different components in a customer service backend application, or to insert the generated tags into metadata of each document for product recommendation.

Automation 123

Automation Prompt Engineering Prompt Engineer Categorization 123

AWS Machine Learning Blog

APRIL 16, 2024

You can use these connections for both source and target data, and even reuse the same connection across multiple crawlers or extract, transform, and load (ETL) jobs. In this post, we concentrate on creating a Snowflake definition JSON file and establishing a Snowflake data source connection using AWS Glue.

Data Scientist 114

Data Scientist Generative AI Machine Learning Auto-complete 114