The acronym ETL stands for extraction, transform and load. It signifies the extraction of data from different data sources like SQL, NoSQL DBMS, SaaS platforms, and XML files, the transformation of the data in the staging area, and the loading of the transformed data into a data warehouse application. The data warehouse applications help to generate reports for analytical purposes as per the needs and requirements of the business. For a data-centric company, ETL services are essential for growth and sustainability. The data from the warehouse is then transited using BI tools for the visual representation of data for better understanding.

Components of ETL data warehouse

The components of the ETL data warehouse are summarized as given below:-

Data sources

Data is stored in databases of various types like Oracle, SQL, MySQL, and NoSQL databases. It can be in the form of an excel sheet as well. Data sources are an important component of ETL data warehouse architecture.

Staging area

Raw data from different data sources are collected in the staging area. This data is collected in a format suitable for a data warehouse. Once the data has been assembled in the staging area then it gets transformed into data that is compatible with the data warehouse.

Data warehouse

The prepared data from the staging area is then fed into the data warehouse applications where they are transformed using Business intelligence and data analytics tools.

BI tools

Business intelligence tools and applications convert the data from the data warehouse to reports that are needed for the analysis of data.

What are data engineering services?

Data engineering services is the process of development of data engineering applications that act as a solution for data-centric companies. Data engineers provide consulting services to business owners and leaders to provide cost-effective solutions for data engineering application development. These applications use artificial intelligence, machine learning, big data, and the internet of things for data provision, data processing, and data transformation.

Data engineering is necessary because it plays a crucial role in business sustenance. The growth and development of a company or organization cannot be made possible without the proper implementation of data engineering solutions in the business.

Benefits of ETL services

Improves performance of database

The performance of the database is essential in storing vast information. If the database query execution time is more then it might not retrieve or fetch the data quickly.

Standardizes data collected from multiple sources

Since in the ETL process data is collected from multiple sources like databases, excel sheets, ms access, etc hence we need to standardize them in the staging area to make it compatible with the data ware house where the data is transformed.

Helps business leaders in decision making

Data warehouse in the ETL process helps in generating reports that can help business leaders to make important decisions for business change which can be fruitful for the company’s growth and development.

Resolves data integration issues

Integrating data analytics might cause several issues if they are not properly configured. Hence using ETL services we can resolve the data integration issues.

By Rosalind Desai

Rosalind desai is a passionate blogger and SEO analyst who loves to write on trending tech topics like robotic process automation, cyber security, python technology, and java development.

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