To begin with, ETL stands for “Extract, Transform, and Load. It is a data integration process that gathers data from multiple data sources into a single, consistent datastore. After that, it loads it into a data warehouse or other target system.
Components Of ETL
ETL process consists of three steps that are as follows.
- Extraction– This process consists of extracting data from the source system into the staging area. In addition, there are three extraction methods like full extraction, partial extraction, and partial extraction. Using any of these methods does not affect the performance and response time of the source system. A user needs to have a logical data map before extracting and loading data successfully.
- Transform– This step allows you to perform customized operations on data. In addition, it applies actions or rules to the extracted data to convert it into a single standard format. Furthermore, it consists of various processes like Filtering, Cleaning, Joining, Splitting, and Sorting.
- Load– It finally loads the transformed data into the data warehouse. Sometimes the loading process may be completed instantly and sometimes it may take a lot of time and intervals. In addition, the period of loading particularly depends on the requirements and it differs from system to system.
Important Features Of an ETL Tool
An ETL tool should have a good connection with Excel, FTP, SharePoint, Bloomberg, Thomson Reuter, FIX, FpML, Salesforce, SAP, Cloud, Hadoop, MQ, LDAP, and web services. A good and effective connection between an EL tool and these technologies results in better performance and control. In addition, it should be capable of doing various day-to-day tasks like data conversion, lookup, expression, joining records, splitting data, filtering, ranking, sorting, grouping, looping, and combining data. Some of these tools are highly efficient and can also deal with out-of-the-box tasks like running web methods.
Moreover, ETL tools need to be capable of creating workflows for arranging and connecting these tasks and transformations. Above all, they should be able to give optimum performance in terms of bulk loading, caching, partitioning, and high availability. To further know about it, one can visit ETL Testing Online Training in India. Apart from these, given below are some of the features of an ETL Tool.
- Data Mapping– This feature helps in creating a graphical view for integrating source data to the target destination. In addition, it facilitates data transformation in the staging area before loading to the destination. It helps in building connections among data sources through primary and foreign keys. It ensures data accuracy and integrity throughout its journey to the destination.
- Data Integration– It is the process of ingesting data from various sources into a data warehouse with the help of third-party connectors. In addition, it helps in establishing two-way data sharing by creating a communication channel between multiple siloed systems and data marts and warehouses.
- Workflow Job Scheduling & Automation– It synchronizes data between two or more systems and updates changes automatically between them. In addition, this approach helps in ensuring data quality. Moreover, this process allows departments to share data in real-time on their respective projects.
Best ETL Tools in Market
ETL tools are software that supports various ETL processes like extracting data from disparate sources, scrubbing data, and transferring this information into data warehouses. These tools ensure time efficiency and save plenty of time and effort otherwise spent on importing data manually. In addition, they are capable of handling complex data easily and help in reducing error portability. Above all, it results in improving business intelligence and helps you in making better decisions, and increases your ROI. Many institutes provide ETL Testing Online Course and one can enroll in them to start a career in it. Given below are some of the leading ETL tools in the market.
- BM DataStage
- Oracle Data Integrator
- Informatica PowerCenter
- SAS Data Management
- Talend Open Studio
- Pentaho Data Integration
- Singer
- Hadoop
- Dataddo
- AWS Glue
- Azure Data Factory
- Google Cloud Dataflow
- Stitch
Conclusion
ETL is a data integration process that gathers data from multiple data sources and loads it into a data warehouse. In addition, it consists of three components that are Extract, Transforms, and Load. There are various leading ETL tools available in markets like BM DataStage, Oracle Data Integrator, Informatica PowerCenter, SAS Data Management, and Talend Open Studio.
