Data integration is vital when developing an effective business intelligence strategy, as it helps developers combine data from various sources and efficiently integrate them. This information can give businesses a real advantage over their competitors, so having a robust ETL team is vital.
What is the ETL process?
The ETL (Extract, Transform, Load) process is the process that helps developers to extract a company’s data from various sources, transform it, and then load it into the data warehouse (DW) system. It can help to maintain data integrity, meaning businesses can rely on it to make better, more results-driven decisions.
- Extract – This process involves extracting structured and unstructured data from sources, including emails, web pages, SQL or NoSQL servers, and CRM systems and placing it in a staging area.
- Transform – Once the data is in the staging area, it can be processed (transformed). This can include: filtering, cleansing, performing calculations, conducting audits, and formatting the data.
- Load – Once the data has been transformed, it can be moved from the staging area to the existing data warehouse.
How can ETL help with business intelligence?
Many businesses rely on the ETL process to give them a consolidated data view to drive better business decisions. This is down to:
- Automatic Batch Data Processing – Current ETL tools run on scripts that can execute masses of specific tasks in the background. ETL processes include batch processes such as moving large volumes of data between two systems simultaneously. Sometimes the volume of this data can increase to millions of events per second which is where automatic batch data processing can help.
- Big Data Analytics & Data Quality – Even if a company has access to vast volumes of data, this won’t matter if it is just left in its raw form. Data needs to be analysed and structured well to offer valuable business insights. The ETL process ensures data quality as well, through the removal of duplicates and standardisation.
- Data Mapping – Data mapping is vital for many data management processes, as it is the process concerned with matching fields from one database to another. It simplifies database functionalities such as integration, migration, transformation and warehousing.
- Master Data Management – Master data management uses data integration and ETL to create a single master record containing all business-critical data – ensuring the data is consistent and reliable.
The benefits that ETL processes can bring to business intelligence include:
- Better efficiency: ETL processes can help developers more easily integrate data from all available sources – saving time on reporting and analysing.
- Better insights: Breaking down data silos and organising data more systematically will help drive better business insights.
- Data quality improvement: The ETL process will resolve potential conflicts or inequalities within the data during the integration process.
- Data analytics precision: Effective data integration with ETL helps increase analytics accuracy through various dashboards and reports.
If your business needs to expand its ETL team or you want to kickstart your ETL career, the team at Agile Recruit are here to listen to your requirements. Get in touch with us to learn more about how we can help.