Implementing RPA with Cognitive Automation and Analytics

Millions of companies in the world today are processing endless documents in various formats. Although Robotic Process Automation (RPA) thrives in almost every industry and is growing fast, it works well only with structured data sources. What about the data that’s not fully structured and comes in varying layouts? To address this problem, there is another aspect of RPA that is taking the industry by storm: cognitive automation. While implementing RPA, you can deploy automations with “cognitive” capabilities. Cognitive automation uses Artificial Intelligence (AI) to learn and understand the same way the human brain works. Thus, it assists humans in making decisions, completing tasks, or meeting goals. Using cognitive automation, you can extract semi—or unstructured data—which is 80% of all data! Data is a precious asset. Businesses struggle to make sense of large volumes of available data and to generate a tangible value from them. Manual business processes barely contain any data that is available for capture. This is where Robotic Process Automation (or RPA) Analytics comes in. RPA bots don’t just automate business processes; they also digitize them. They take the large volume of data and interpret it in near real-time to provide actionable information. In this course, you will be introduced to cognitive automation, the role that AI plays in it, and Automation Anywhere’s cognitive solution, IQ Bot. You will also be introduced to RPA analytics and explore how Automation Anywhere’s Web Control Room and Bot Insight can provide this functionality. As you begin this course, you will learn the six steps to deploy cognitive automation. Next, you will explore the IQ Bot portal – Automation Anywhere’s web-based application for developing the cognitive IQ bots. You will then learn to use the portal by following the IQ Bot workflow. Next, you will learn how RPA analytics help interpret and improve automated business processes. You will see how Bot Insight functions as an RPA analytics platform. You will also explore the different types of RPA analytics and learn how to generate RPA analytics via two mechanisms – the Web Control Room for Operational Analytics and Bot Insight for Business Analytics and CoE Analytics. Finally, you will learn how to use the RPA mobile app to study and edit the default CoE dashboard that is published via Bot Insight.

Regardless of the industry, business process automation is here to stay. Business processes are increasingly being automated through software automation. But how is software automation simplified and made accessible? The answer is Robotic Process Automation or RPA. RPA lifecycle: Intrdocution, Discovery and Design is the first course of the Specialization on Implementing RPA with Cognitive Solutions and Analytics. In this course, you will be introduced to RPA and see how it is combined with cognitive solutions and analytics to enable organizations to adopt the model of a “Digital Workforce” and help them transform the nature of their work. You will also learn about the first two phases of the RPA implementation lifecycle: Discovery and Design. In the Discovery phase, you take a set of business processes and identify those that are suitable and beneficial for automation. In the Design phase, you create a plan for your RPA project. The learning will be reinforced through concept description and guided practice.

To adopt RPA, you begin with the Discovery and Design phases and proceed onto the Development and Testing phase. RPA Lifecycle – Development and Testing is the second course of the Specialization on Implementing RPA with Cognitive Solutions and Analytics. In this course, you will learn how to develop and test bots. For this, you will use Automation Anywhere Enterprise Client (or AAE Client) to record, modify, and run tasks. AAE Client is a desktop application with an intuitive interface, that enables the creation of automated tasks with ease. It features ‘SMART’ Automation technology that quickly automates complex tasks without the need for any programming efforts. The learning will be reinforced through concept description, building bots, and guided practice.