Knowee
Questions
Features
Study Tools

Which transformation is used to load data into a data store or compute resource?

Question

Which transformation is used to load data into a data store or compute resource?

🧐 Not the exact question you are looking for?Go ask a question

Solution

The transformation used to load data into a data store or compute resource is known as ETL (Extract, Transform, Load).

Step 1: Extraction The first step in this process is the extraction of data from various sources. These sources could be databases, CRM systems, files, etc.

Step 2: Transformation The extracted data is then transformed into a format that can be analyzed. This could involve cleaning the data, validating it, or aggregating it.

Step 3: Loading The final step is loading the transformed data into a data store or compute resource. This could be a data warehouse, a data lake, or a database.

This ETL process is a fundamental aspect of data handling and is crucial in data warehousing environments.

This problem has been solved

Similar Questions

Which step in the data value chain is where collected raw data is transformed into a form that’s ready to derive insights from?Data genesisData analysisData processingData storage

3.Question 3What is the Extract, Transform, and Load (ETL) process’s primary purpose in data management?1 pointTo create data pipelines for real-time data movement.To manage data repositories and databases.To extract data from data repositories and store it in raw form.To convert raw data into analysis-ready data by extracting, cleaning, standardizing, and transforming it.

which level in a datawarehouse architecture converts host to datawarehouse format ?a.Data Loadb.Data Transformationc.Data Cleaningd.Data Storage

__________ is a system where operations like data extraction, transformation and loading operations are executed.Question 19Answera.None of the aboveb.Data stagingc.Data integrationd.ETL

What is Data Scaling?

1/3

Upgrade your grade with Knowee

Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.