Business Intelligence

Transforming raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making is the goal of Business Intelligence and is not only of the highest priority at Robotics Centre but a crucial part of digital transformation. A key aspect of achieving this goal is the use of advanced Big Data Analytics and Artificial Intelligence. There are 4 major categories of analytics which increase in complexity, but also significantly increase in value. Each category can be thought of as answering a unique question with respect to your data.

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Real-Time Analytics – What is happening?

Looking at the first question, the first thing to understand from a process flow perspective is “what is happening?” also known as real-time analytics. This is achieved through the deployment of sensors and the gathering, normalization, and classification of real-time data.

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Historical Analytics – Why did it happen?

With the continuous collection of real-time data the second question “why did this happen?”, also known as historical analytics can be posed. This is a form of analytics that looks at data over time forming correlations, patterns, models, and etc.

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Predictive Analytics – What will happen?

With enough historical data the question “what will happen?” also known as predictive analytics can be posed. In this type analysis, historical and real-time data can predict specific outcomes with good accuracy.

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Prescriptive Analytics – How to make it happen?

Moving even further to the last category is the question “How to make it happen?” also known as prescriptive analytics where data science is applied to prescribe decisions and actions to achieve a specific outcome with good accuracy. Prescriptive analytics provide the highest return on investment in term of business intelligence but are the most complex to achieve. As a matter of fact, most industrial operations are considered cutting edge and innovative if they have made it to the historical class of analytics. In reality many industrial operations haven’t even started understanding what is happening.