Data Transformation and ETL
Working with large data sources often requires analysis or conversion into new formats for the data to become useful information.
This can take place on a one-off basis when a large amount of data needs to be analyzed once, or it could take place daily as part of an analysis of each day's transactions.
In both cases data transformation involves three distinct steps - extract, transform, load (ETL).
- Extraction of pertinent data from the source location. This could be a structured data source - like database table, or delimted text files - or less structured like text documents or web pages.
- Transformation of the extracted data into something new and more useful. Includes summarizing the data and any other calculations necessary to generate the desired output.
- Loading the new information into its final destination. Examples of this might include a new database table, a PDF report, emailed notifications or generation of web pages.
- Transform your reams of data into useful information.
- Analyze your data and increase your business intelligence.
- Convert data formats as needed.
- Our data needs to be cleaned up and validated.
- We want to convert our data into web pages.
- We want to put our database on the web.
- Our existing nightly batch processing job is taking too long and needs to be optimized.
- Our nightly batch jobs are interfering with our backups.
