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Business Analytics and It's Impact on Business and Industry

Business Analytics became the most effective thing for business in the last decade. Different multinational corporate companies like Google, IBM, Face book, Yahoo and eBay are the frontrunners in big data and business analytics in their respective business domains 1 .Business Analytics uses big data which is higher and richer data that shows more details about behaviors, activities, and events that happened all around. Business Analytics access this different variety of the data from huge resources with less response time. 2 .Companies that collect data might be used to produce different income generation possibilities. So they need to find out what sort of data they need and how it will be collected, sorted and analyzed. Mr. Kuldeep D. Ghorapade "Business Analytics & Its Impact on Business & Industry" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Digital Economy and its Impact on Business and Industry , October 2018, URL: https://www.ijtsrd.com/papers/ijtsrd18676.pdf Paper URL: http://www.ijtsrd.com/management/business-economics/18676/business-analytics-and-it's-impact-on-business-and-industry/mr-kuldeep-d-ghorapade<br>

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Business Analytics and It's Impact on Business and Industry

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  1. International Journal of Trend in International Open Access Journal International Open Access Journal | www.ijtsrd.com International Journal of Trend in Scientific Research and Development (IJTSRD) Research and Development (IJTSRD) www.ijtsrd.com ISSN No: 2456 INTERNATIONAL CON ITS IMPACT ON BUSINESS AND Organised By: V. P. Institute of Management Studies & Research, Sangli Organised By: V. P. Institute of Management Studies & Research, Sangli Organised By: V. P. Institute of Management Studies & Research, Sangli ISSN No: 2456 - 6470 | Conference Issue – ICDEBI INTERNATIONAL CONFERENCE ON DIGITAL ECONOMY AND TS IMPACT ON BUSINESS AND INDUSTRY ICDEBI-2018 FERENCE ON DIGITAL ECONOMY AND INDUSTRY Business Analytics usiness Analytics & It’s Impact on Business &Industry Industry Mr. Kuldeep D. Ghorapade Department of Fashion Design, CNCVCW, CSIBER, Design, CNCVCW, CSIBER, Kolhapur Assistant Professor, Department Affiliated to Shivaji University, Kolhapur Affiliated to Shivaji University, Kolhapur,Maharashtra, India INTRODUCTION Business Analytics became the most effective thing for business in the multinational corporate companies like Google, Face book, Yahoo and eBay are the frontrunners in big data and business analytics in their respective business domains [1].Business Analytics uses big data which is higher and richer data that shows more details about behaviors, activities, and events happened all around. Business Analytics access this different variety of the data from huge resources with less response time.[2].Companies that collect data might be used to produce different income generation possibilities. So they need to find out what sort of data they need and how it will be collected, analyzed. The sources of the data may be internal or external. The internal data constitutes different business reports, minutes of meetings, proceedings, etc. external sources are customer feedback, reaction of competitors etc. One of the rich source of data is social media now a days. Millions of users use social media websites daily. Social media are computer-facilitated tools that enable the faster exchange of information in virtual networks [3].The most widely used social media websites are book, whatsapp, twitter, instagram and you Millions of videos, data, files are daily uploaded and downloaded. There is no single definition of business Analytics in literature. In fact each author stresses different aspects. BA or BI is defined as the method of converting data into information and subsequently to knowledge [4]. The types of knowledge obtained are about the customer requirements and decisions, about the customer requirements and decisions, organizational performance in the industry and the global trends. Another definition of BI, the BA systems is, BA systems put together the gathering and storage of data and management with analytical tools to present a ready for action and complicated information to the planners and decision makers [5]. This is to assist them to obtain the right time, location and form. The data is mined, extracted, and put to use by means of framing different models. These model different algorithms, operational research techniques and behavioral sciences. This information predicts a lot of things and provides guidelines in the formulation of the strategies in different business domains. So it is a combination of tools aiming to enhance the decision making transforming data into beneficial information and knowledge which is extracted by utilizing data mining tools and analytical techniques KEYWORD: Business Intelligence, Big Data, Predictive Analytics Scope of Business Analytics Business analytics can be used as a solution provider in all walks of life and not only in business. It taking strategic decisions for all business domains. Business Analytics in general are used to detect relationships and patterns in data in order to predict the future by analyzing the past and taking better preventive decisions. Thus, the business analytics aim of use differ from one industry to another a marketer can use the business analytics to predict the customers’ response to an advertising campaign, the customers’ response to an advertising campaign, Business Analytics became the most effective thing for business in the nizational performance in the industry and the global trends. Another definition of BI, particularly the BA systems is, BA systems put together the gathering and storage of data and knowledge management with analytical tools to present a ready- nd complicated information to the planners last last decade. decade. like Google, IBM, are the frontrunners in Different big data and business analytics in their respective 1].Business Analytics uses big data which is higher and richer data that shows more and events that happened all around. Business Analytics access this different variety of the data from huge resources with less response time.[2].Companies that collect data might be used to produce different income generation This is to assist them to obtain the right information at the right time, location and form. The data is mined, and put to use by means of framing different models. These models are framed using different algorithms, operational research techniques and behavioral sciences. This information predicts a lot of things and provides guidelines in the formulation of the strategies in different business So it is a combination of tools aiming to enhance the decision making in an organization by transforming data into beneficial information and knowledge which is extracted by utilizing data mining tools and analytical techniques. [6] what sort of data they need and how it will be collected, sorted and The sources of the data may be internal or external. The internal data constitutes different business proceedings, etc. The customer feedback, responses, One of the rich source of Millions of users use Social media are facilitated tools that enable the faster ion in virtual networks [3].The most widely used social media websites are face , whatsapp, twitter, instagram and you tube. files are daily uploaded and Business Anal Analytics, Business Intelligence, Big Data, Predictive Analytics Business analytics can be used as a solution provider in all walks of life and not only in business. It helps in taking strategic decisions for all business domains. Business Analytics in general are used to detect the relationships and patterns in data in order to predict the future by analyzing the past and taking better preventive decisions. Thus, the business analytics aim of use differ from one industry to another, for instance a marketer can use the business analytics to predict There is no single definition of business Analytics in In fact each author stresses different aspects. BA or BI is defined as the method of converting data into information and subsequently to [4]. The types of knowledge obtained are @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Conference Issue: ICDEBI-2018 | Oct 2018 Page: 74

  2. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 | IF: 4.101 or a product seller can use it to predict the movement of product prices, or it can be used to detect trends such as in banks if a manager wish to recognize the most profitable customers, or alert a credit card customer to a probable fraudulent charge. Thus the business analytics help in answering many questions such as what will happen if the demands of products decrease. Or if suppliers’ prices increase risk to lose money in a new business? Structure of Business Analytics The organization has to understand the thoroughly so that the state of the art solution can be found out. BA is not a common solution to a business problem but varies according to the individual business need. Data mining is part of Business intelligence functionalities as defined by Gartner who described BI as a software platform delivering 14 capabilities divided into functionalities including integration, information delivery and analysis functionality which contain the data mining and predictive modeling. While data mining is considered as the automated process to detect the un known patterns in the structured data of the organization (7) scientists also describe data mining as the process to collect, filter, prepare, analyze, and store data that will be used to create useful knowledge and supporting the business analytics and predictive modeling. The generalized structure of data analytics is divided into different elements 1.Data Source/Data Layer The internal source of data is generated from ERP, CRM, or SCM systems or other spreadsheets, HTML & XML documents, files and spreadsheets. The external data sources are statistical public reports. The other inputs of data are discussions, videos, graphics and other user generated content.(9) 2.ETL Process/Integration layer Extract, Transform, Load This layer extracts the data from different original data sources, inconsistent data, keep the data in required form and structure, integrate all the data together and upload it in defined data warehouse or data mart. The data processing or transformation is done by using programming language, scripting or SQL or a product seller can use it to predict the movement of product prices, or it can be used to detect trends language. Here the transformed data is having different coding, quality than the source data. Non-relevant (repeat & missing) data are excluded. The data warehouses technology is subject-oriented, integrated, volatile collection of data which supports the management’s decision-making process [10]. 3.Data Analysis/Application layer It consists of tools which are used for analysis of integrated data. This analys patterns and exceptions also. Analytical Processing databases) are used to process the data and provides different point of view from all angles of the same data. can be collected within one particular territory, within a limited time frame and of a particular product or product line. component of the application layer is data mining a computational process involving the discovery of patterns in large data sets methods that are at the inte intelligence, machine learning, statistics, and database systems to present useful information to users [12]. The outcomes of the data mining are used for prediction and description reality).The already known variables ar predict the future outcome. various techniques and some of these are listed by Hen et al. (2011) in their publication Data Mining: Concepts & Techniques and analyzed in Stod research text Customer Analytics in the age o social media(2012)are Cluster Analysis, Anomaly Detection, Association Rule mining, methods, Regression analysis & natural language processing. 4.The presentation or display layer It presents the data in user outcome in different performance ere ports is used to monitor the performance of business. The reports can be customized as per the need of the final user. Results are in the form of spreadsheet or dashboards. are derived from dashboards measures the business performance effectively which is a multi built on business intelligence and data integration infrastructure [13] language. Here the transformed data is having quality than the source data. relevant (repeat & missing) data are The data warehouses technology is integrated, time-variant and non- volatile collection of data which supports the making process [10]. er wish to recognize the most profitable customers, or alert a credit card customer to a probable fraudulent charge. Thus the business analytics help in answering many questions demands of products increase, what is the Data Analysis/Application layer It consists of tools which are used for analysis of This analys is identify trends, patterns and exceptions also. OLAP (Online Analytical Processing databases) are used to process the data and provides different point of view from all angles of the same data. Sales data can be collected within one particular territory, me frame and of a particular product or product line. The most significant component of the application layer is data mining a computational process involving the discovery of patterns in large data sets [11] .It involves using methods that are at the intersection of artificial ligence, machine learning, statistics, and database systems to present useful information to users [12]. The outcomes of the data mining are used for prediction and description (describes reality).The already known variables are used to predict the future outcome. The data mining uses various techniques and some of these are listed by Hen et al. (2011) in their publication Data Mining: and analyzed in Stodder’s research text Customer Analytics in the age of social media(2012)are Cluster Analysis, Anomaly Association Rule mining, Classification Regression analysis & natural language business need thoroughly so that the state of the art solution can be common solution to a business problem but varies according to the individual Data mining is part of Business intelligence functionalities as defined by Gartner who described BI as a software platform delivering 14 three three groups groups of of functionalities including integration, information delivery and analysis functionality which contain the While data mining is considered as the automated known patterns in the (8). The other scientists also describe data mining as the process to and store data that will be used to create useful knowledge and supporting the modeling. analytics is divided The internal source of data is generated from ERP, or SCM systems or other soft ware’s, HTML & XML documents, other and spreadsheets. The external data sources are statistical public reports. The other inputs of The presentation or display layer It presents the data in user-friendly manner. The performance ere ports which is used to monitor the performance of business. The reports can be customized as per the need of Results are in the form of spreadsheet or dashboards. The strategic decisions are derived from dashboards measures the business performance effectively which is a multi-layered applications built on business intelligence and data integration graphics and other Extract, Transform, Load This layer extracts the ta from different original data sources, clear the keep the data in required form integrate all the data together and upload it in defined data warehouse or data mart. The data processing or transformation is done by these these d dashboards. The scripting or SQL @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Conference Issue: ICDEBI-2018 | Oct 2018 Page: 75

  3. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 | IF: 4.101 implementing Business Intelligence into decision- implementing Business Intelligence into decision making processes [14] 3.Survival time Analysis This technique shows how loyal the customer is to the brand and what is the will switch to another brand. receives this be havioral information to prolong a customer’s survival time. 4.Forecast the development of strategic business process The use of historical, present and anticipated data can predict the future of the company. potential behavior of the customer can be analyzed which predict future sales, overall strategies of the business. strategies of the business. This technique shows how loyal the customer is to probability of it that he will switch to another brand. The organization havioral information to prolong a orecast the development of strategic business Applications of BA in marketing Marketing department of an organization has the responsibility of identifying, satisfying and retaining the customers using their product or services. data driven digital marketing belongs to the emerging trends in marketing along with cross channel and content marketing.BA proves to be very effective in these marketing activities.BA can be used effectively in below area of marketing. 1.Customer Segmentation and Profiling The marketing decisions are depend upon the results derived from the application of customer segmentation and profiling techniques. used here is RFM model.(figure). This model divides the customers into groups according to the following three metrics values: recency meaning how recently the customer made a purchase; frequency, standing for how often they and monetary value, or how much they spend. other segmental information like demographical segmentation (Age, sex, marital status, and behavioral segmentation (How purchase a product) can be also determined by BA. It also studies the migration of customers from one segment to the other and can be used for effective decision making regarding a product. 2.Supportive analysis for cross selling & up selling Here the previous purchases of specific customer are taken into consideration while selling the products. The market basket analysis identifies interdependencies between the products and clustering them as a model can be used in BA. The affinity grouping model identifies which product attract the sale of other products. T factors increase the sale of the product remarkably. Cross selling and up selling are considered to be the most attractive marketing objectives organizations hope to be achieve when nizations hope to be achieve when The use of historical, present and anticipated data can predict the future of the company. The potential behavior of the customer can be analyzed which predict future sales, profit and organization has the responsibility of identifying, satisfying and retaining the customers using their product or services. The data driven digital marketing belongs to the emerging with cross channel and es to be very effective in these marketing activities.BA can be used effectively Customer Segmentation and Profiling depend upon the results derived from the application of customer profiling techniques. The model used here is RFM model.(figure). This model divides the customers into groups according to the recency meaning how recently the customer made a purchase; frequency, standing for how often they purchase; value, or how much they spend. The other segmental information like demographical Figure 2.RFM model (Source: Hsu (2012)) RFM model (Source: Hsu (2012)) Application of BA in social media Many authors believe that social media analytics presents a unique opportunity for businesses to treat the market as a dialog between businesses and customers; instead of the traditional business customer marketing approaches [15] Different analytics techniques are used in social media. These are 1.Natural language programming (NLP) It is the most common technique and may not be used for processing of real time data. 2.Opinion Mining The Opinion Mining Technique is defined as the effort of finding valuable information contained in user-generated data [17] 3.Sentiment Analysis Sentiment analysis business value in opinions and attitudes expressed on social media, the news, and in enterprise Application of BA in social media Many authors believe that social media analytics status, education) (How often they ty for businesses to treat the market as a dialog between businesses and customers; instead of the traditional business-to- customer marketing approaches [15] purchase a product) can be also determined by so studies the migration of customers from one segment to the other and can be used for effective decision making regarding a product. Different analytics techniques are used in social Supportive analysis for cross selling & up Natural language programming (NLP) It is the most common technique and may not be of real time data. [16] Here the previous purchases of specific customer sideration while selling the products. The market basket analysis identifies interdependencies between the products and clustering them as a model can be used in BA. The affinity grouping model identifies which product attract the sale of other products. These factors increase the sale of the product remarkably. Cross selling and up selling are considered to be the most attractive marketing The Opinion Mining Technique is defined as the effort of finding valuable information contained in analysis software software s and attitudes expressed ews, and in enterprise discovers discovers the the @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Conference Issue: ICDEBI-2018 | Oct 2018 Page: 76

  4. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 | IF: 4.101 4.Defense Sector In Pakistan the focus of the BA model was to minimize the loss of human life fro attack by predicting the future attack frequency and the prospective losses and injuries and its adoption by the government. Challenges in front of BA 1.Infrastructure Big infrastructure is needed to use different BA models in industry. Presently large multinationals like face book, Google, IBM, using it. Large and midlevel companies should consider the use of online platforms for this purpose. Most mid level companies in unaware of online platforms of BA. 2.Agility Change is permanent in every business. The BA model must be agile/ flexible to accommodate the business requirements of the future. 3.Trained Work force Specialized and technically people are needed to handle all BA activities. 4.Privacy Violation The risk in utilizing of big data analytics is obviously the privacy aspects, not all the required information can be easily accessed, so that companies must consider the information from other websites or from individual's private accounts. 5.Integration of current ERP systems with BA models Different online BA models like HADOOP OLAP are not able to integrate with the current ERP systems of the organization. extract the exact information used for decision making. Significance of BA in digital economy of India NASSCOM predicts the Indian Analytics service industry is growing at a CAGR of 25% and poised to touch USD 2.3 billion by 2018.The industry in is expected to almost double by 2020. The analytics service market stands at 35% global market. [25] Digital economy in India is progressing fast due t new internet savvy generation and also government is new internet savvy generation and also government is feedback. [18]. It is again divided into two techniques 1) Lexicon based method upon the vocabulary or words of the person. 2) Machine Learning method – Machine learning uses linguistic features.[19]. Overall, these techniques offer many more linguistic challenges, especially when analyzing Twitter and other micro blogs, which do not contain much information, assume implicit knowledge, involve lots of language variations, emoticons, let domain-specific slang, hash tags and irony that cannot be processed by common BI Applications of BA in manufacturing In majority of manufacturing organization BA services are integrated with existing systems in manufacturing like ERP, MRP, SCM etc. dashboard is also an important tool used by BA. manufacturing industry is benefitted by BA applications in which they can see the real time progress of a process which is visually represented in effective manner. Manufacturing experienced higher manufacturing cost and satisfaction. [20] Applications of BA in Society in general 1.Education Sector BA (Predictive Analysis) models can be used by educational institutes to increase the retention of the student and enhancing their results and achievements.BA also predicts the performance in a specific course during the semester and mark the ones that will fail and have low performance in exams.[21] 2.Agriculture Sector BA models are used to develop a multi criterion support system based on predictive analysis to help the stakeholders having better purchases and the ability to take better sales de knowing the requirements of the green coffee supply chain market in India. [22] 3.Finance Sector The researchers created a BA model to optimize prediction of products and stock market indications. Thus this model allows to set stock indications future values and trading of financial services which will allow investors to increase significantly their returns on investment and reduce the risk [23] . [18]. It is again divided into two Lexicon based method – It depend upon the vocabulary or words of the person. 2) In Pakistan the focus of the BA model was to minimize the loss of human life from the drone attack by predicting the future attack frequency and the prospective losses and injuries and its adoption by the government. [24] Machine learning s linguistic features.[19]. Overall, these techniques offer many more linguistic challenges, especially when analyzing Twitter and other micro blogs, which do not contain much information, assume implicit knowledge, involve lots of ticons, letter-casing, and irony that [19] Big infrastructure is needed to use different BA models in industry. Presently large multinationals IBM, eBay, amazon are Large and midlevel companies should consider the use of online platforms for this level companies in India are unaware of online platforms of BA. In majority of manufacturing organization BA services are integrated with existing systems in SCM etc. The dashboard is also an important tool used by BA. The manufacturing industry is benefitted by BA applications in which they can see the real time progress of a process which is visually represented in Change is permanent in every business. The BA flexible to accommodate the business requirements of the future. ing organizations organizations reducing customer experienced manufacturing higher cost productivity, improved and improved productivity, customer Specialized and technically qualified/trained people are needed to handle all BA activities. Applications of BA in Society in general The risk in utilizing of big data analytics is obviously the privacy aspects, not all the required information can be easily accessed, so that companies must consider the rules of taking information from other websites or from individual's private accounts. (Predictive Analysis) models can be used by educational institutes to increase the retention of the student and enhancing their results and achievements.BA also predicts the students’ performance in a specific course during the that will fail and have Integration of current ERP systems with BA Different online BA models like HADOOP, are not able to integrate with the current ERP systems of the organization. They cannot extract the exact information used for decision BA models are used to develop a multi criterion support system based on predictive analysis to help the stakeholders having better purchases and the ability to take better sales decisions and knowing the requirements of the green coffee Significance of BA in digital economy of India NASSCOM predicts the Indian Analytics service ng at a CAGR of 25% and poised to touch USD 2.3 billion by 2018.The industry in India is expected to almost double by 2020. The Indian analytics service market stands at 35%-50% of the The researchers created a BA model to optimize prediction of products and stock market ions. Thus this model allows to set the ions future values and trading of financial services which will allow investors to increase significantly their returns on investment Digital economy in India is progressing fast due to the @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Conference Issue: ICDEBI-2018 | Oct 2018 Page: 77

  5. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 | IF: 4.101 7.Martin Aruldoss, Miranda Lakshmi Travis, V. Prasanna Venkatesan.” A survey on recent research in business intelligence”. 19 January 2014. Vol. 27 Iss 6 pp. 831 Enterprise Information Management. 8.Osama T. Ali, Ali Bou Nassif and Luiz Fernando Capretz. “Business Intelligence Solutions in Healthcare A Case Study: Transforming OLTP system to BI Solution”. 2013. IEEE 9.NEGASH, S. Communication of Information systems,, 2004, Vol. 13, p. 177 10.INMON, W. H. Building the data warehouse, New York, USA: John Wiley & ISBN 0471081302 11.WITTEN, I. H. and FRANK, E. Data Mining: Practical Machine Learning tool 3rd ed. The Morgan Kaufmann Management Systems. Elsevier/Morgan Kaufmann, 0123748569 12.OLSZAK, C. M., and ZIEMBA, E. Business Intelligence Systems in the Holistic Infrastructure Development Supporting De Organizations. Poland: 2006. Interdisciplinary Journal of Information, Management. Vol. 1. ISSN 1555 13.ECKERSON, W.W. Performance dashboards: Measuring, monitoring business. . 2nd Ed. New Jersey: John Wil Sons, Inc., 2010. ISBN 978 14.STODDER, D. Customer Analytics in the Age of Social Media. [online] 2012, Renton, WA: Data Warehousing Institute (TDWI) 11-04] <https://www.tableau.com/sites/default/files/white papers/tdwi bestpracticesreport_customeranalytics_july2012.p df> 15.LUSCH, R. F., LIU, Y., and CHEN, Y. The Phase Transition of Markets and Organizations: The New Intelligence and Entrepreneurial Frontier. 2010. IEEE Intelligent Systems 71-75. ISSN 5432262 16.MUNOZ-GARCIA, O. and NAVARRO, C. Comparing user generated content published in different social media sources, 2012. [online] In: Proceedings of @NLP can u tag # user generated Proceedings of @NLP can u tag # user generated promoting it by various measures. The advantages are speed, less cost and convenience. BA will become the important facet of this economy. As more and more transactions becomes digital more and mor generate, This data will be the important aspects formulate different BA models. So BA becomes more and more significant and important as the digital economy progresses. The BA scientist dig dipper into this data to make decision making easi businesses. Indian corporate world become more streamlined and can take informed business decisions. Conclusion Business Analytics is an emerging field in India. Use of BA models will get a boost as the digital economy and use of internet become rampant by every citizen in india.BA provides important information which can be well utilized in business for decision making. BA improves the process efficiency, delivery time, reduces cost, increases customer satisfaction levels and add value to the business. Indian corporates are also formulating the strategies based on business analytics in their respective business domains. certainly change the way of doing business. References 1.Davenport, H., and Jill, D. "Big data in big companies." International Institute for Analytics (2013). 2.http://www.sas.com/en_us/whitepapers/iia prescriptive-analytics-107405.html 3.Buettner, R. (2016), “Getting a Job via Career oriented Social Networking Sites: The Weakness of Ties”, 49th Hawaii International Conference on System Sciences (HICSS-49), January 5 Kauai, Hawaii. 4.M. Golfarelli, S. Rizzi, and I. Cella, “Beyond Data Warehousing: What’s Intelligence?” in DOLAP ’04, Washington DC, 2004. 5.S. Negash, and P. Gray, (2003). “Business Intelligence”, in Americas Information Systems (AMCIS), 2003. 6.FATIMETOU ZAHRA MAHMOUD, (2017), ‘The application of Predictive Analytics: Benefits, Challenges and how it can be improved, International Jo Scientific and Research Publications, Volume 7, Issue 5, May 2017 , ISSN 2250-3153 promoting it by various measures. The advantages are Martin Aruldoss, Miranda Lakshmi Travis, V. Venkatesan.” A survey on recent research in business intelligence”. 19 January 2014. Vol. 27 Iss 6 pp. 831 - 866.Journal of Enterprise Information Management. will become the As more and more ore and more data will This data will be the important aspects to So BA becomes more and more significant and important as the digital economy progresses. The BA scientist dig dipper into this data to make decision making easier for the businesses. Indian corporate world become more streamlined and can take informed business decisions. Osama T. Ali, Ali Bou Nassif and Luiz Fernando Capretz. “Business Intelligence Solutions in Healthcare A Case Study: Transforming OLTP system to BI Solution”. 2013. IEEE NEGASH, S. Business Business the the Intelligence. Association Association Intelligence. unication of for for Information systems,, 2004, Vol. 13, p. 177-195 Business Analytics is an emerging field in India. Use of BA models will get a boost as the digital economy e rampant by every citizen in india.BA provides important information which can be well utilized in business for decision making. BA improves the process efficiency, delivery time, reduces cost, increases customer satisfaction levels INMON, W. H. Building the data warehouse, New York, USA: John Wiley &Sons. 3 ed. 2002. WITTEN, I. H. and FRANK, E. Data Mining: Practical Machine Learning tools and techniques ed. The Morgan Kaufmann Series in Data agement Systems. Elsevier/Morgan Kaufmann, Amsterdam: 2005. 2005. Amsterdam: Indian corporates are ISBN ISBN also formulating the strategies based on business analytics in their respective business domains. It will certainly change the way of doing business. OLSZAK, C. M., and ZIEMBA, E. Business Intelligence Systems in the Holistic Infrastructure Development Supporting Decision-Making in Organizations. Poland: 2006. Interdisciplinary Journal of Information, Vol. 1. ISSN 1555-1229 . "Big data in big companies." International Institute for Analytics Knowledge, Knowledge, and and http://www.sas.com/en_us/whitepapers/iia- ECKERSON, W.W. Performance dashboards: Measuring, monitoring . New Jersey: John Wiley & Sons, Inc., 2010. ISBN 978-0-470-58983-0 & & managing managing your your Buettner, R. (2016), “Getting a Job via Career- oriented Social Networking Sites: The Weakness ”, 49th Hawaii International Conference on STODDER, D. Customer Analytics in the Age of Social Media. [online] 2012, Renton, WA: The Data Warehousing Institute (TDWI) [Cit. 2015- 04] <https://www.tableau.com/sites/default/files/white 49), January 5-8, 2016, URL URL M. Golfarelli, S. Rizzi, and I. Cella, “Beyond Data Warehousing: What’s DOLAP ’04, Washington DC, Next Next In In Business Business stpracticesreport_customeranalytics_july2012.p and P. Gray, (2003). “Business in Americas Information Systems (AMCIS), 2003. LUSCH, R. F., LIU, Y., and CHEN, Y. The Phase Transition of Markets and Organizations: The New Intelligence and Entrepreneurial Frontier. IEEE Intelligent Systems. Vol. 25, Iss. 1, p. Intelligence”, Conference Conference on on FATIMETOU ZAHRA MOHAMED MOHAMED The application of Challenges and International Journal of GARCIA, O. and NAVARRO, C. ed content published in different social media sources, 2012. 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