- ETL solutions improve quality by performing data cleansing prior to loading data in some different repository.
- It provides the foundation for data analytics and machine learning workstreams.
- Makes possible to migrate data between a variety of sources, destinations and analysis tools.
- Enables context and data aggregations so that business can generate higher revenue and/or save money.
- In short, ETL tools are the first essential step in the data warehousing process that eventually lets you make more informed decisions in less time.
Importance of ETL to the business:
Modern Businesses rely on data for almost everything. Hence, the quality & quantity of data matters so that business can make better decisions regarding various concerned parties & to handle all this tedious task ETL shows in importance in following ways:
- Enhanced Business Intelligence
Modern ETL tools break down data silos and give self-service capabilities to the people who understand the data best, letting them draw more informed conclusions from a single source of truth in less time which further helps in increasing system performance simply with keeping data growth.
- High Return on Investment (ROI)
Modern, cloud-based ETL tools replace expensive custom coding and manual transformations with graphical drag and drop development, scalable business rules, and faster, more accurate data processing.
- Enhanced Quality & Consistency
Modern ETL tools include built-in intelligence that continually detects and reflects changes in source and target objects to ensure data consistency – the lifeblood of both strategy and customer experience. Quality of data has improved significantly starting from the old legacy tools to today’s Open source & Real time tools which helps in improving productivity & overall efficiency of businesses in today’s challenging environment.
- Delivers Single Point of view
Managing multiple data sets demands time and coordination, and can result in inefficiencies and delays. ETL combines databases and various forms of data into a single, unified view. This makes it easier to analyse, visualize, and make sense of large data sets. Also, it helps reduces the time gaps in accessing the data, with real – time ETL relevant data can be extracted in seconds that helps in timely accessing the data in a very short span of time.