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Pouria Ghaternabi 7050754 A presentation for Electronic Business Strategies

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Page 1: Business Intelligence

Pouria Ghaternabi 7050754

A presentation forElectronic Business Strategies

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What is Business Intelligence?Raw data

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What is Business Intelligence?Meaningful and useful information

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What is Business Intelligence?To make better decisions

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Who Make the Decisions?

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Data = Right Decision? • What about if you have too much data?

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Will you be able to find the right answer

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For questions such as• How are my sales?• How much will I sell next year?• Are my customer satisfied with my services?• Which other products are my customers

interested in?• Which parts of the business are not profitable?

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How About Those Bad Decisions?

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How About Those Bad Decisions?In 2000$50 million

= $900 million

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How About Those Bad Decisions?

In 1986$5 Million

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How About Those Bad Decisions?

20 years later$7.4 Billion

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How About Those Bad Decisions?

Steven Sasson

1975

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How to Make the Right Decisions?• You need an insight into the data

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Business Intelligence 1.01980s

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Business Intelligence/ Data Warehouse/ Data Mining

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Business Intelligence 2.0

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What is Decision Support System?• Interactive computer-based information

system that supports decision-making activities.

• It is a an application of BI

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What is Expert Systems?• A computer program that simulates the judgment

and behavior of a human or an organization that has expert knowledge and experience in a particular field

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Data Visualization?Goal is to communicate information clearly and efficiently to users via the information graphics selected, such as tables and charts

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Data Visualization?

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Business Intelligence 3.0

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Big Data?

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Big Data“Big data can be defined as datasets that are beyond the ability of common databases softwares to store, manage, capture and analyze”

Ref: Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H., 2011

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wikibon.org/bigdata

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Big Data creates value in several ways• Making data more readily accessible to relevant stakeholders at the

right time creates enormous value of data

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• Enabales experimentaion

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• Improve decision making, minimize risk and unearth valuable insights

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• Segment the population in order to customize products and services to meet the segment needs

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• Innovate new business models, products and services to not only satisfy customers but to capture new opportunities and create new markets.

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Use of Big data as competitive advantage

• Find hidden patterns• Identify new growth opportunities• Precise prediction of consumer behavior• Increases productivity• New sources of value• Catalyst for trend shifting in industries

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Crunch of Big Data

“We’ve never had greater, better analyzed, more pervasive, or increasingly connected computing power and information at a cheaper price in the history of the world”

Ref: McKinsey & Company

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Insight and Recommendation

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“Managers are making bad decisions because of bad data”

Professor Nour El-Kadri

Telfer School of Management

Is BI and Big Data Analytics are the Solution for Bad Decision Making?

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Let’s Challenge This Idea!

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What Might Be Wrong?

Causation

Bias

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Boston Street Bump

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Accelerometer

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Does Good Data Guarantee Good Decisions?

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Peoplewho make the decisions

Processesof decision making

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Why BI May not Enhance Decision Making?

High Concentration of

Analytics Skills

Shifting BI from Conventional Uses to

More Critical Applications

Low Strategic Priority of Data

Accessibility Issues

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Analytic Skills are Concentrated on Too Few Employees

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eBusiness Executives Don’t Manage Data as Good as They Manage Talent, Capital, and

Brand

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ThankYou

Very

Much!

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References• Anderson, C. (2008, June 23). The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. Retrieved November 14, 2014, from

http://archive.wired.com/science/discoveries/magazine/16-07/pb_theory• Assuncao, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya, R. (2013). Big Data Computing and Clouds: Challenges, Solutions, and Future Directions. Journal of Parallel and Distributed

Computing. Retrieved from http://arxiv.org/abs/1312.4722• Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey Quarterly, 56(1), 75–86.• Carneiro, H. A., & Mylonakis, E. (2009). Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clinical Infectious Diseases, 49(10), 1557–1564.• Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188.• City of Boston. (2014). Street Bump Mobile Application. Retrieved November 17, 2014, from http://www.cityofboston.gov/DoIT/apps/streetbump.asp• Elliott, T. (2011, March 9). Business Analytics vs Business Intelligence? Retrieved from http://timoelliott.com/blog/2011/03/business-analytics-vs-business-intelligence.html• Ferrando-Llopis, R., Lopez-Berzosa, D., & Mulligan, C. (2013). Advancing value creation and value capture in data-intensive contexts. In Big Data, 2013 IEEE International Conference on (pp. 5–9).

IEEE. Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6691685• Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2008). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012–1014.• Harford, T. (2014, March 28). Big data: are we making a big mistake? FT Magazine. Retrieved from http://on.ft.com/1qgq8al• Hill, K. (2012, February 16). How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did. Forbes Magazine. Retrieved from http://www.forbes.com/sites/kashmirhill/2012/02/16/how-

target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/• Liautaud, B. (2000). E-Business Intelligence: Turning Information into Knowledge into Profit. (M. Hammond, Ed.). New York, NY, USA: McGraw-Hill, Inc.• Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. Mckinsey Global Institute.

Retrieved from http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation• Nusca, A. (2013, May 14). McLaren CIO: How we’re working with big data. Retrieved from http://www.zdnet.com/mclaren-cio-how-were-working-with-big-data-7000015383/• Panorama Software. (2011). Business Intelligence 3.0: Revolutionizing Organizational Data. Retrieved from http://www.reply.eu/Documents/11174_img_Business_Intelligence_3_0_Whitepaper.pdf• Ponniah, P. (2011). Data Warehousing Fundamentals for IT Professionals. John Wiley & Sons.• Shah, S., Horne, A., & Capellá, J. (2012). Good data won’t guarantee good decisions. Harvard Business Review, 90(4), 23–25.• Simon, P. (2014a, March 11). Big Data Lessons From Netflix. Retrieved from http://www.wired.com/2014/03/big-data-lessons-netflix/• Simon, P. (2014b, March 25). Potholes and Big Data: Crowdsourcing Our Way to Better Government. Retrieved November 17, 2014, from http://www.wired.com/2014/03/potholes-big-data-

crowdsourcing-way-better-government/• Turban, E. (2007). Decision Support and Business Intelligence Systems (8 edition.). Prentice Hall.• Vesset, D., Nadkarni, A., Olofson, C., & Schubmehl, D. (2012). Worldwide Big Data Technology and Services 2012-2016 Forecast. International Data Corporation (IDC). Retrieved from

http://bit.ly/1bHgypq