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With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse. This is unlike the more traditional ETL method, where data is transformed before loading into the data warehouse.
Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.
In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. You can use stored procedures to handle complex ETL processes, make API calls, and perform data validation.
Replicate can interact with a wide variety of databases, data warehouses, and data lakes (on-premise or based in the cloud). Closing Migrating to a new data warehousing platform can be a challenging endeavor. Get to know all the ins and outs of your upcoming migration. We have you covered !
On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”).
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