“A Business that Doesn’t Implement a Strategy of Automation in the Client Acquisition Process is Doomed to have Slow Growth, even Puts itself at Risk of Declining” - Bob Mangat (Author)
The technological revolution has been accompanied by an explosion of data. The amount of data available to a business enterprise at any given point of time, is unprecedented. The objective of Business Intelligence is all about exploiting and utilising this data in order to derive meaningful insights through data analysis, which could drive decision making.
However, the availability of data has not necessarily resulted in data driven decision making for all companies. This is because the availability of huge amounts of data has not simultaneously increased the capability to derive insights from the same.
Consequently, the potential of BI has not been completely realised. In order to address this shortcoming, firms have resorted to implementing Business Intelligence Automation.
For a more detailed understanding of the concept of Business Intelligence, refer to our blog on “What is Business Intelligence?”
Based on the idea of automating the process of Data Analytics, Automation in Business Intelligence helps in extracting valuable insights from data, cover unexpected changes in data and provide a detailed informative report on hidden problems and opportunities in your data. It is a scenario of Moving from Business Intelligence to Machine Learning with Automation.
In this blog, we will look at what is Business Intelligence Automation; consider the gradual evolution of Business Intelligence, Automation and Data Analytics; look at Business Automation and Intelligence Application in business scenarios and consequently evaluate the risks associated with Automation Business Intelligence.
What is Automation in Business Intelligence?
Business Intelligence Automation can be understood as a combination of technologies such as Artificial Intelligence (AI), Robotic Process Automation (RPA) and Business Process Management (BPM) along with automation strategies, in order to deliver, redesign and reconfigure IT processes for enhancing the outcomes of complex business processes.
Automation in Business Intelligence helps in deriving insights automatically which in turn reduces dependency on Data Analysts and Scientists.
Automation Business Intelligence encompasses certain specific technologies. These include:
- Machine Learning
- Cognitive Automation
- Natural Language Processing
- Intelligent Document Processing (IDP)
- Machine/Computer Vision
- Deep Learning
- Intelligent Business Process Management Applications
- Speech Recognition
Business Intelligence, Automation and Data Analytics: The Interconnected Evolution
The idea of Business Intelligence has been around for quite some time now. However, the hype surrounding the same, reached its peak around 2012.
Over the years, there has been a shift of Analytics Value Chain towards Business Intelligence Automation. In this section, we will look at the basic reason which accounted for this transition.
Data Visualization is an important component of Business Intelligence. Business Intelligence Reporting helps in the presentation of data in understandable forms which provides an idea of the current state of business. It helps in answering questions like, “What is the total sale of last month?”, “What has been the website traffic like for the preceding month?”.
However, the process is restricted to having a glimpse of data indicating the existing situation. The Business Intelligence tools are so designed that they aid in reporting on the metrics that they are specifically asked to report on.
Know everything about Business Intelligence Reporting; check out our blog on "Business Intelligence Reporting"
However, there is no scope for Data Analytics being performed outside the purview of what has been explicitly specified by the user. This means that under a normal situation, Business Intelligence software does not provide you with insights other than those which you were explicitly looking for.
This implies that Business Intelligence does not guarantee more Data Analytics on its own. The consolidation of huge volumes of data is not enough to facilitate human analysis which can take months or even years.
There is a missing link in the equation and this is where Business Intelligence Automation steps in. The complete equation is that of Business Intelligence, Automation and Data Analytics. This Automation in Business Intelligence has helped in discovering hidden trends and insights in data automatically, in response to even a slightest change in stored data.
Thus, Business Intelligence Automation saves the precious time which Data Analysts would have otherwise spent on exploring and combining data. On the contrary, the business executives can instead focus on developing appropriate strategies for their business on the basis of insights gained through Automation Business Intelligence.