Data Engineering

ELT is a data processing approach where data is extracted, loaded, and transformed to a target system, optimizing data processing and analytics.

Aggregation is the process of summarizing and combining large datasets into smaller, more manageable ones for analytics and business intelligence purposes.

Wrangling Process is the process of cleaning and transforming raw data into a format that is usable for data analytics.

Learn about stored procedures, their purpose, and their benefits in managing complex database operations, improving maintainability and performance.

Learn about ETL and its advantages and disadvantages. Discover the different types of ETL tools available, including code generators and GUI-based tools.

Learn about data integration, its benefits, and how it streamlines decision-making by consolidating diverse datasets for effective analysis and reporting.

Explore the world of data migration tools, their key features, and best practices to ensure successful data transfers between systems.

Data wrangling is the process of cleaning, transforming, and integrating data to make it suitable for analysis, leading to better decision-making.

Data transformation converts data to a new format or structure for analysis or integration.