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MAA703 Journey of Big data

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To answer this question you need to discuss the key differences between big data and the analytics and how this impacts differently on decision making and measuring performance.

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The generation of huge amount of data having high velocity, volume, value, and variety, has introduced the concept of big data.Before its introduction, there were several technologies which were quite close to the notion of big data. This paper will discuss about these technologies and their comparison with the big data.

Journey of Big data

It starts at 1965 when World’s first data center was established.Before that, business intelligence was introduced in 1958 for producing business insights.In 1976, Material Requirement Planning (MRP) worked as an alternative of big data by providing solutions to big business scenarios.

After that, big data has been discussed in many articles in 1989 and 1999. Besides, Internet of Things (IoT) was introduced (World Economic Forum 2018).decision making- Big data versus previous analytics method In seventeenth century, decision making process was aided by the Quakers. It used to provide quite efficient solutions to decision-making.

In last century, the decision-making techniques used to proceed with policy making and resource allocation for decision making process.Big data, instead, proceeds with goal identification, improvisation, data collection, data refine, tools implementation, and execution (World Economic Forum 2018).Started its journey in 1940, predictive analysis proceeds with the real-time analytics and non-linear programming.

Customer relationship management (CRM) tools used to be a frequent tool for predictive analysis before big data.Big data provides predictive analysis by providing personalized data analysis and data democratization for individual organizations (Harvard Business Review 2006).Earlier, prescriptive analysis used to amalgamate mathematical and computational models and solve the business problems using mathematical sciences.Big data introduced patent software to check the ongoing scenarios and to provide prescribed solutions to analytics. Currently, the biggest potential of big data is prescriptive analytics.

The fundamental analytics technologies are MRP, Business Intelligence (BI), and IoT that can be compared with the role of big data.IoT includes wireless connection of billions of physical devices and sharing data over these devices ).Big data offers management of huge amount of human generated data whereas, IoT provides collection and compression, and edge analysis of large volume of machine generated data.

MRP and Big data

MRP was designed for managing small amount of data of inventory management and production control.It is popular for providing efficient and fast solutions to business problems related to inventory management system (MRPEasy 2015).It helps in data collection, analysis, and design. It works best for production planning.

Fundamental difference between MRP and Big data

Despite perfect inventory control and handling manufacturing process, MRP has certain drawbacks which can be resolved by the big data.MRP is costly, time consuming, and incomprehensive in many cases. On the other hand, big data is cheap and provides real-time solutions to complex analysis.Moreover, big data is able to transform MRP processes.

BI and Big data

The BI tools are very useful in delivering well-structured data response of complex business problems.BI is effective in data visualization, system automation, report generation from a single system, and management solution.Big data, on the other hand, is proficient in new services’ innovation, customer analytics and forgery detection (Debortoli, Müller and Brocke 2014).


Huge changes have come in the analytics world with the help of big data. The processes of predictive analysis, decision making have become more agile for big data.The implementation of big data with the scripting languages have brought all the improvisations that were missing in the past analytics techniques.However, in some cases, like in clustering and segmentation, BI tools are more efficient than big data.


A brief history of big data everyone should read. 

Advantages and disadvantages of using MRP system.

Debortoli, S., Müller, O. and vom Brocke, J., 2014. Comparing business intelligence and big data skills. Business & Information Systems Engineering, 6(5), pp.289-300.

Internet of Things (IOT) Analytics 

A Brief History of Decision Making.

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