ETL- Closing the Data Gap

Better data management produces better data analysis. Using a tool designed to extract, transform and load (ETL) data seamlessly transfers data into your data warehouse. It simplifies the process of transferring large volumes of data by batching them.

ETL Defined

The phrase ETL refers to the organization of the three basic steps of data processing. First, it extracts or reads the data from the database or from various collected sources. Second, it transforms the data via a rules-based conversion process so the data fits the new database. Third, it loads the data, or writes it, into the new database.

Tools to Improve Data Migration

While a data lake can assimilate disparate pieces of data, a data warehouse requires homogenized data. In the transformation step, the tool automates record validation, rejects unacceptable data and integrates the data by deleting duplicate records, sorting, filtering, converting, standardizing, translating and verifying the data sources.

Regarding load, these ETL utilities use one of two methods to build or add to the new database both of which reduce data gaps. The first of these is for the tool to use a SQL insert statement to physically insert the new individual records as a new row into the target table. The second method links the ETL process for every record from its source.

Benefits of ETL Utilities

Speed of data movement tops the list of benefits to using an ETL tool, but it has many other benefits over conventional methods of database construction. Its application to existing data streamlines it efficiently to better enable analysis to uncover business insights.

The graphical interface of ETL tools provide one of the speed mechanisms for column and table mapping between the source and target databases. The utilities allow acquisition from a multitude of cross-platform data structures. They can also identify data changes when they occur in the source data and update only it to the target database.

Using an ETL tool provides a ready-made way to transition data without needing to reinvent the wheel by writing your own program. These utilities include operations such as data aggregation, filtering, joining, merging reformatting and sorting. You will also have control over data monitoring, transformation scheduling, version control and a unified method of metadata management.

Succinctly, the use of ETL utilities streamlines an otherwise time-consuming and clunky process. Its major benefits include:

• They’re easy to use, taking care of the coding for you.
• The GUI provides a snazzy visual flow of system logic, allowing you to drag-and-drop to specify rules.
• The utilities provide an operational resilience since these utilities include built-in error-handling.
• ETL tools make a great choice for complex data management that requires moving large data volumes in batches since it helps you with calculations, data changes and integration and string manipulation.
• It makes it a breeze to cleanse data.
• Some ETL tools integrate with existing business intelligence (BI) tools while others have their own BI tools.
• Since they save so much time and effort, these tools provide a high return on investment (ROI).
• ETL tools provide a set of performance-enhancing technologies including cluster awareness, massively parallel processing and symmetric multi-processing.

Contact Starr & Associates to learn how database tools like ETL utilities can help your data mining process to improve process efficiency and customer service. We can help you find simple solutions to develop better business intelligence.