- Using automated systems to implement and use data extraction and analysis from primary and secondary sources.
- Correcting coding issues and other relevant issues, and removing corrupted data.
- Enhancing the loading of data into and out of various sources/target systems by designing, creating, and putting into effect new ETL processes that use industry standards and best practices.
- Rearranging data in a legible way through the creation and upkeep of databases and data systems.
- Analyzing data to determine its value and quality.
- Making use of statistical methods to find, examine, and analyze patterns and trends in large, complicated data sets that can be useful for diagnosis and forecasting
- Giving important business processes a numerical value so that business performance can be evaluated and compared across time.
- Examining regional, societal, and global trends that have an impact on both.