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ETL Software is a software that is used to turn raw data into information by the process of extraction, Transformation and Loading that can be used for actionable business intelligence (BI). ETL is a type of data integration that refers to extract, transform, load which is used to blend data from multiple sources. It is often used to build a data warehouse. The process of extracting data from homogeneous or heterogeneous sources is known as Data extraction.
The processing of data by data cleaning and transforming them into a proper storage format or structure for the purposes of querying and analysis is known as data transformation. The process of insertion of data into the final target database such as an operational data store, a data mart, data lake or a data warehouse is known as data loading. At first an ETL system extracts data from the source systems, enforces data quality and consistency standards and conforms data so that separate sources can be used together. Finally, the data in a presentation ready format is delivered by it so that applications can be build up by application developers and decisions can be made by end users.
Generally, data are integrated from multiple applications by ETL systems. It is developed and supported by different vendors or hosted on separate computer hardware. The original data is stored in different systems that are frequently managed and operated by different employees. For example, a cost accounting system contain data from payroll, sales, and purchasing. The most challenging task for most data driven organizations is conversion of data from its raw format into one that makes sense for business users. As most business users are unable to understand the complexities of data models or writing code, they need a software that can do this task for them. They just need the insights gained from analyzing data. So, an ETL software will be helpful in solving this issue by gathering data from sources, changing it into understandable formats, and putting the transformed data in repositories for specific business analytics uses.
Uses of ETL Software:
ETL Software can be used for many process that include:
- ETL Software can be used to automate and streamline data pipeline processes.
- It can reduce the time spent on manual processes of writing code and mapping source data to target systems by making these tasks easily repeatable, cost-effective, and faster.
- It is capable of handling complex data management tasks.
- The organizations can use data from a larger number and variety of data sources by artificial intelligence and machine learning and data sources are more distributed then before by the adoption of the cloud.
- The speed of analytics will be increased as real time data are comes from the Internet.
- Using ETL Software with standardized, repeatable data governance processes helps to ensure data governance that is required to met regulations like GDPR which is accountable for ensuring digital privacy and other regulations.
- ETL Software are also helpful for implementing data quality so that organizations have both trustworthy and accurate data.
Benefits of Using an ETL Software:
Generally, ETL Software help manage data in several ways in an organization. Other benefits include:
- ETL software can scale up and down to accommodate the requirement of business users. Some of the organization needs center on huge batch jobs of big datasets, where as others need a smaller datasets for exploration. All these can be possible to handle by ETL software because of scalability.
- Performing real time operations with data is possible with ETL Software as it is possible for the user to specify the rate at which jobs are performed by competitive tools.
- The process can be automated by using an ETL Software. For this, the ETL process needs to be set up once and then organizations can reuse it as per their requirement in task like nightly batch jobs.
- The governance features offered by an ETL software are highly important for ensuring data integrity and accuracy with in an organization. data lineage for regulatory compliance, metadata management, and lifecycle management are some of the capabilities.