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FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
A CSV (Comma Separated Values) file is a type of plain text file that stores tabular data in a structured format. Each line in the file represents a row of data, and each value within a row is separated by a comma. CSV files are commonly used for exchanging data between different software applications, such as spreadsheets and databases. They are also used for importing and exporting data from web applications and for data analysis. CSV files can be easily opened and edited in any text editor or spreadsheet software, making them a popular choice for data storage and transfer.
An integrated cloud application and platform service, Oracle offers an array of enterprise information technology solutions. Other company offerings include software-as-a-service (SaaS), platform-as-a-service (PaaS, and infrastructure-as-a-service (IaaS). The Oracle Cloud Infrastructure provides companies the convenience of the public cloud combined with the security and control of on-premises infrastructure. Oracle Cloud Applications help companies streamline their business processes, increase productivity and reduce costs with software applications such as Project Portfolio Management, ERP Financials, Procurement, and more.
CSV File gives access to various types of data in a structured format that can be easily integrated into various applications and systems.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.