Analytic Process Automation (APA) is using machine learning and analytic algorithms for the automation of data analytics and business process.
APA is the integration of analytics, data science, and process automation and is an easy way of growing users for the business because of its self-service model.
Now is the right time for APA because it provides features of cost savings, value generation, and workforce upskilling.
Please find the below principles:
- Automatic Data Discovery: most difficult task to do is data discovery however machine learning can help in making the process automatic. APA can write automatic processes using machine learning that can make this difficult process easy. This can include assessing data in all variety of formats that includes and not limited to pdf files, weblogs, or automatic programs written for continuous data gathering, etc.
- Auto-Service: APA platforms help in creating an efficient process that improves services by automating insight, auto recommendations and automating business processes. Now analysts have quick access to find and analyse data and they can share it easily. Users have a simple and user-friendly environment to create their own diagnostics. APA platform uses artificial learning to create insights to provide a wider aspect to review that is not accessible by humans.
- Auto-Generation: APA can help organisations to shift from difficult coding to the simple user-friendly environment that is automated. Organisations need to spend a lot on programmers and data scientists which may become a barrier. Now organisations can take help from these modern APA applications that help data analysts to operationalise Artificial Intelligence (AI) and machine learning without any deep knowledge of algorithms and mathematics.
- Auto-Process: APA has its own automated programs that help in delivering insights and triggering actions automatically. It is possible to continuously improve performance and response of business by implementing AI in a business process.