Business analytics and Data Mining techniques can help organizations make sense of -- and gain a competitive advantage from -- all the data that they have in their systems. Business analytics includes “decision management, content analytics, planning and forecasting, discovery and exploration, business intelligence, predictive analytics, data and content management, stream computing, data warehousing, information integration and governance” (IBM, 2013, p. 4).
There are different types of business intelligence analytics that an organization can take advantage of, including predictive analytics, text analytics and text mining, sentiment analysis, customer analytics and business intelligence data mining. Data Mining is the process of analyzing large data-sets to identify trends and patterns in the data. The data can be generated through different sources such as social media, websites, transactions, mobile devices, sensors, etc. The information extracted from this data helps organizations to derive their real business value and generate new business opportunities.
In the light of above information write a 3000 words research report on specific business analytics and Data Mining techniques applications that derive business value and generate new business opportunities in any of the following three (3) industry verticals. Illustrate the impact of these techniques on businesses with examples of application from the chosen domain.
Choose only any THREE (3) domains from the following list:
1. Transportation industry – in this domain the business analytics help stakeholders in making effective decision in Traffic control, route planning, intelligent transport systems and congestion management (by predicting traffic conditions). Also, could be useful for route planning to save on fuel and time, for travel arrangements in tourism etc. revenue management, technological enhancements, logistics and for competitive advantage (by consolidating shipments and optimizing freight movement), etc.
2. Banking industry - Data mining techniques can be used to detect financial fraud, including credit card fraud, corporate fraud and money laundering.
3. Health Care industry - Health care applications include discovery of patterns in radiological images, analysis of microarray (gene-chip) experimental data to cluster genes. Moreover, chronic disease states and high-risk patients can be tracked.
4. Manufacturing industry - Large volumes of data from the manufacturing industry are untapped. The underutilization of this information prevents improved quality of products, energy efficiency, reliability, and better profit margins. Business analytics can be used in solving today’s manufacturing challenges and to gain competitive advantage among other benefits.
5. Education industry - Major challenge in the education industry is to incorporate big data from different sources and vendors and to utilize it. Business analytics can be used to measure teacher’s effectiveness, overall progress of a student over time and effectiveness of curriculum, etc.
6. Customer Relationship Management - Data mining and analytics provides efficient tools to analyze customer data for the purpose of decision-making. Moreover, data mining aids analysis of buying patterns, determination of marketing strategies, segmentation of customers, stores or products.