Data warehouse automation describes the act of automating and optimizing the data warehouse development processes, ensuring consistent and superior quality and productivity. DWA is considered to give complete automation of the whole lifecycle of a data warehousing, from initial source planning to data gathering, data visualization and data interpretation, to effective data integration, documentation and testing. Data warehouse functions can be broadly divided into two major categories: Financial and Operational. Business data is processed and managed by Finance departments, and Operational data is processed and managed by the Operations departments. Both must coordinate and integrate with each other for efficient performance.
The main benefits of data automation solutions are increased productivity, simplified reporting, cost savings, reduced errors and human error, better data governance, better collaboration between people and machines, reduced infrastructure costs and avoidance of data redundancy. Faster, more accurate, and more comprehensive delivery of customer experiences is another important benefit. The ability to process data at light speed, without loss or corruption of data results in improved services and products, and increased customer satisfaction. Reduced operational costs result in improved service levels, reduced personnel costs, and improved customer relations. Data automation solutions also help the company make better use of its human resources and financial resources.
Data warehouse tasks such as data integration, data extraction, data analysis, data cleansing and visualizing, data mining and trend data collection, and data maintenance are the most critical. Automated data entry software reduces manual data entry. Data cleansing removes duplicate data from the database. Trend data provides information about customer purchasing trends over time.
Data automation processes can be effectively used to support all these tasks in production environments. It saves man hours by removing repetitive tasks, greatly improving the productivity of an organization, and increasing efficiency at a minimal cost. Manually conducted tasks can be reduced by automating many business-related activities.
In some cases, it may be very difficult to replace a human administrator for complex tasks that involve complex business logic, or for activities such as data maintenance and analytical processing. Data cleaning tasks eliminate unnecessary data manually. Trends analysis can be performed manually, but it is often not worth the time. It requires human intervention and potential non-contributory data duplication. Automation ensures that the same data is processed time and again without human intervention.
Data automation can be divided into two broad categories: machine learning and business process automation (BPA). Machine learning refers to a set of tasks that are based on different mathematical models for data collection and extraction, in order to achieve specific business objectives. BPA involves different tasks associated with different phases of data collection, like data cleansing, data analysis, data manipulation, and data visualization. A combination of both machine learning and BPA may be more challenging and more efficient. This form of automation is often referred to as a mixed mode automation.
Data cleansing is a primary task performed by a manual system. It usually involves de-duplication of duplicate records. Data cleaning is usually part of machine learning tasks. It involves creation of a query/value map and data analysis. Another process called exploratory data analysis is a type of manual exploration that may sometimes require more supervision than simple de-duplication.
A data collection and manipulation tool is an automated machine learning tool that processes raw data and produces quality reports. Some popular tools include Kebola, Metacafe, and Data Narc. Data Visualization is a popular data collection and manipulation tool. It converts data to images and graphics, sometimes based on text. It is commonly used for graphics and web design purposes.