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

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

JUNE 7, 2024

Oracle Data Integrator Oracle Data Integrator (ODI) is designed for building, deploying, and managing data warehouses. Key Features Out-of-the-Box Connectors: Includes connectors for databases like Hadoop, CRM systems, XML, JSON, and more. Read More: Advanced SQL Tips and Tricks for Data Analysts.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

JULY 8, 2024

Handling Missing Data: Imputing missing values or applying suitable techniques like mean substitution or predictive modelling. Tools such as Python’s Pandas library, Apache Spark, or specialised data cleaning software streamline these processes, ensuring data integrity before further transformation.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52