IEEE International Conference on Data Engineering Business Intelligence from Voice of Customer L. Venkata Subramaniam, Tanveer A. Faruquie, Shajith Ikbal, Shantanu Godbole, Mukesh K. Mohania IBM India Research Lab, India {lvsubram,ftanveer,shajmoha,shantanugodbole,mkmukesh}@in.ibm.com Abstract— In this paper, we present a first of a kind system, called Business Intelligence from Voice of Customer (BIVoC), that can: 1) combine unstructured information and structured information in an
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insight concerning their experiences with monetization of big data. 1 Corresponding Author 1 Data Monetization: A Retailer’s Journey The ability to monetize a company’s data has been an elusive goal. However, in the era of big data, business intelligence and analytics, and cloud computing, this goal is becoming more achievable. The retail industry, with its exacting merchandising strategies and tight supply chain relationships, has taken the lead in demonstrating that monetizing data can provide
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years, organizations across public and private sectors have made a strategic decision to turn big data into competitive advantage. The challenge of extracting value from big data is similar in many ways to the age-old problem of distilling business intelligence from transactional data. At the heart of this challenge is the process used to extract data from multiple sources, transform it to fit your analytical needs, and load it into a data warehouse for subsequent analysis, a process known as “Extract
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correct the situation quickly. Continental was also able to save $7 million in fraud and reduce costs by $41 million in the first year alone. That was more in one year than the warehouse cost over a six year period. They are a leader in business intelligence and won the Data Warehousing Institute’s Best Practices and Leadership Award in 2004. Continental also was able to save on departure taxes that they constantly overpaid for years. There was a rule that passengers who were in the UK for under
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fully supportive of all our existing business intelligence tools including Jaspersoft, Microstrategy, Pentaho, Tableau, Business Objects and Cognos. There are no new languages to learn. You just load your cluster, connect your favorite query tool and you are up and running. There are two major advantages for a company of our size and requirements in using Amazon Redshift versus a traditional data-warehouse. The first is scalability. Given the current business climate it is difficult to predict
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Week1 Problemk, Behind every decision you make there’s a problem you’re trying to solve. Objectives, After you have a better definition of your problem, now it’s time to get crystal-clear aboutwhat you’re trying to accomplish with your decision Alternatives, u have a well-defined problem and clear objectives, it’s time to finally assess your alternatives and decide, right? Not so fast! First, we should generate alternatives — expand and explore possibilities Consequences, Now comes the time to finally
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reason why I chose this company is because I have done internships in both COMPANY X and Sun Life Malaysia and through that I am equipped with firsthand knowledge about the company. COMPANY X is based in Kuala Lumpur, Malaysia and their primary business lies around Southeast Asia. It is considered a huge company with 1,080 branches across the region and over 40000 employees. The first problem that I see when I was working there is that there were too many paper works. They have been using data
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the year 2000. By their estimates, that number could reach 35 zettabytes (ZB) by the year 2020 (p. 39). The ability to analyze and process the enormous amount of data is a costly undertaking for companies that are behind the curve and a lucrative business for those that are ahead of the game. Each tweet and post contribution from the users that share the web space further buries the proverbial haystack. It is the ability to sift through the data that determines whether a company can gain traction
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CASE #2: CATERPILLAR TUNNELING Functional Business Systems – Overview Each system is different from one another and every system has its pros and cons. An individual business exists in an environment and a business organization is a component within a system. For businesses to survive, the function of the degree in which businesses thrive sync with the environment. Business Intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful
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QTM2000 Case Studies in Business Analytics Spring 2016 Section 01:T/Th 9:45AM-11:20AM – Gerber 102 Section 02:T/Th 11:30AM-1:05PM – Gerber 102 Instructor: Denise Sakai Troxell Office: Babson Hall 318 Office hrs: By appointment only | Phone: (781) 239-6309e-mail: troxell@babson.edu | Course Description (from catalog): This course builds on the modeling skills acquired in the QTM core with special emphasis on case studies in Business Analytics – the science of iterative exploration
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