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- Automated schema change handling, data normalization and more
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- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
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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.
Oracle DB is a fully scalable integrated cloud application and platform service; it is also referred to as a relational database architecture. It provides management and processing of data for both local and wide and networks. Offering software-as-a-service (SaaS), platform-as-a-service (PaaS), and infrastructure-as-a-service (IaaS), it sells a large variety of enterprise IT solutions that help companies streamline the business process, lower costs, and increase productivity.
A fully managed data warehouse service in the Amazon Web Services (AWS) cloud, Amazon Redshift is designed for storage and analysis of large-scale datasets. Redshift allows businesses to scale from a few hundred gigabytes to more than a petabyte (a million gigabytes), and utilizes ML techniques to analyze queries, offering businesses new insights from their data. Users can query and combine exabytes of data using standard SQL, and easily save their query results to their S3 data lake.
Oracle DB provides access to a wide range of data types, including:
• Relational data: This includes tables, views, and indexes that are used to store and organize data in a structured manner.
• Spatial data: This includes data that is related to geographic locations, such as maps, satellite imagery, and GPS coordinates.
• Time-series data: This includes data that is related to time, such as stock prices, weather data, and sensor readings.
• Multimedia data: This includes data that is related to images, videos, and audio files.
• XML data: This includes data that is stored in XML format, such as web pages, documents, and other structured data.
• JSON data: This includes data that is stored in JSON format, such as web APIs, mobile apps, and other data sources.
• Graph data: This includes data that is related to relationships between entities, such as social networks, supply chains, and other complex systems.
Overall, Oracle DB's API provides access to a wide range of data types that can be used for a variety of applications, from business intelligence and analytics to machine learning and artificial intelligence.
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.
