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Getting business ready with Business Analytics

Business analytics and Data analytics: Business Analytics (BA) involves the application of data analytics techniques to improve the business performance. In business analytics, business data is continuously monitored and collected for a specific amount of time. This data is then processed and analyzed so as to ameliorate the business significantly. The aim of business analytics is to identify the data which is relevant to the particular business and use it to improve the efficiency and financial output. Data analytics is a much wider term which includes software development, industries and almost all management ventures. The specificity towards business depends on what separates Data analytics from Business analytics. Business analytics are ever predominant. It has only been rechristened and given fancy names. Role of Analytics in improving Business output: Improved business output is a better organization with efficient resource management without sinking in cost. Analytics can help in optimizing the quantity and quality of the of the business output. Basically, Business analytics is part of the wider term Business Intelligence (BI). Business Intelligence is a descriptive term. It generally involves different methodologies in the collection of raw data. It involves analyzing the raw data, recognizing the patterns, and creating models to aid in business development. Quantitative analysis, mathematical models and complex data are employed by engineers for providing engineering solutions to various business problems. The analysts also make use of more sophisticated computer technologies like artificial intelligence, machine learning and neural networks for segmenting the data and realizing patterns. Challenges in Business Analytics: 1. Executive distrust: Many top-level executives and managers distrust implementation of Business Analytics techniques. They rather tend to be conservative and consider traditional business techniques to be the best. Overcoming such lack of support in businesses is an unenviable prospect. 2. Lack of commitment: One major thing regarding Business Analytics is the need of time to process the data for better analysis to draw conclusions. Many businesses which implement BA techniques lack commitment for sticking to it for a longer period of time. Thus, BA techniques and the businesses tend to fail along with them. 3. Poor coordination: Another challenge faced in the field of Business analytics is the lack of coordination between the various teams. Responsibilities in business analytics are generally split among various teams. If the teams fail to coordinate, then the analytic techniques tend to fail even they are strong. 4. Lack in quality/quantity of data: Many BA implementation techniques fail due to lack of relevant or quality data. This is due to lack of time provided for collection of quality data. The time used to filter, analyze and process the data should be implemented in data collection methodology itself. Example of successful Business analytics implementation: In a short span of time, Axis bank was able to become the third largest private sector bank in India. They implemented robotic learning technologies and deep learning techniques to identify customer behavior patterns. Thus, they were able to predict cases like the customers are prone to leave. They alter these situations by offering more and better promotions. Now they are working on an AI based chatbot to establish better customer interaction For more info : https://www.excelr.com/data-science-course-training-in-mumbai