ETL is a type of data integration that refers to the three steps (extraction, transformation, loading) used to combine data from multiple sources. It is often used to build a data warehouse. During this process, the data is taken (extracted) from a source system, converted (transformed) into a format that can be analyzed and stored (loaded) in a data warehouse or another system. Extract, load, transform (ELT) is an alternative but related approach, designed to drive processing to the database to improve performance.
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How the ETL Process Works
As an integral part of the data integration strategy of any organization, ETL is a process to combine data from multiple sources, convert it into a consistent format and load it into a destination database. By providing a 360-degree consolidated view of the data, ETL enables business users to keep abreast of changing market dynamics and make smarter decisions at the right time.
Loading of Data
We data in any business application, database, web service or cloud application quickly with the wide selection of Centerprise connectors. We supports a large variety of destinations for your data, including Amazon Redshift, Google BigQuery, Snowflake and more.
Connect to the Data
Do you want custom mashups from multiple input data sources? Relliks Systems make it easy for you. Do you try to combine your data storage silos in the cloud and premises in a single location? We have got you covered.
Visualize the Data
Relliks Systems puts your complete data stream at your fingertips. You can collect live data samples, filter your flow on the fly, monitor data behavior, debug incorrect data events and measure metrics in real time, with everything coming together to help you identify patterns as you go.
Extraction of Data
Relliks Systems supports a large number of native integrations through databases, SaaS applications, local and cloud storage, APIs and SDKs and many other custom sources. Extract data from multiple sources in one place for transformation and loading.
Transformation of Data
We transform data using the intuitive drag-and-drop interface of Centerprise and view the output at any time to find and fix problems instantly. Our code engine allows you to transform and customize your data the way you want. Our Mapper provides automatic OneClick and custom mappings, whether your data is structured or semi-structured.
Streaming of data
Pushing large volumes of data at scale to a data warehouse is difficult. Our pipeline can reliably handle billions of events per day with millisecond potential.