Pickl AI

JUNE 7, 2024

Key Features Out-of-the-Box Connectors: Includes connectors for databases like Hadoop, CRM systems, XML, JSON, and more. Data Integrator Studio: Provides a graphical interface for business users and developers to manage data integration tasks. Scalability: Designed to handle large volumes of data efficiently.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

JULY 8, 2024

Organisations leverage diverse methods to gather data, including: Direct Data Capture: Real-time collection from sensors, devices, or web services. Database Extraction: Retrieval from structured databases using query languages like SQL. The Difference Between Data Observability And Data Quality.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

DagsHub

AUGUST 23, 2024

Datafold is a tool focused on data observability and quality. It is particularly popular among data engineers as it integrates well with modern data pipelines (e.g., Source: [link] Monte Carlo is a code-free data observability platform that focuses on data reliability across data pipelines.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 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.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52