ETL/CONTINUOUS DATA PROCESSING
ETL / Continuous Data Processing
ETL denotes Extract, Transform, and Load. Basically, it describes a 3-stage process that includes the extraction and movement of data from various different sources to a specially designed data warehouse for proper and secure storage.
The process helps to prepare data for analyzing and making important decisions. The process is very similar compared to that of Data Migration with a small difference, the format cannot be changed in the process of Data Migration but on ETL we can change the file format.
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Bringing Data From Different Sources Easily
Installation Of ETL Procedures
Analysis Of Existing ETL System
Designing ETL Architecture
ETL Testing And Deployment
ETL Support And Maintenance
ETL Data Integration
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Data Extraction
Proper data extraction from the source system is required for collecting data to process further just before it is analyzed. The data process extraction has to consume less time and resources and that has to be available for the next step in ETL data integration.
Data Cleaning
Here it involves detecting data errors, data redundancies, invalid data, etc. This method, ensures that the consolidated data is best suited for further analysis.
Data Transformation
This step involves transforming the collected source data into a form that matches the target. Here the step consists of converting the units and dimensions of data that can be directly used for the analysis.
Data Loading
In this step, the cleaned and transformed data will be loaded into the target environment. Based on the kind of target database, the data would be loaded either incrementally or in a single go.
Management Of ETL Procedures
Designing a strong ETL architecture and managing it efficiently is necessary for streamlining the whole procedure of data accumulation and processing. Also, the data sources and the whole ETL procedure can be audited frequently to find out and rectify the major errors.
Data Staging
In this step, the data from one process is made available for the next procedure. Such a staging would save the intermediate results of the ETL procedure which can be useful in case the step fails.
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