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Business Intelligence and Data Mining Session 14 Section 3 Instructor: Michael Sutton, PhD, CMC, AdmA, MIT EMBA 512 Fall 2015 Business Analytics Online analytical processing (OLAP) is multidimensional data analysis that is initiated by a business user and consists of complex reporting mechanisms, analyses, and data visualization —Codd et. al. (1993), Providing OLAP (On-line Analytical Processing) to UserAnalysts: An IT Mandate Boise State Executive MBA Program Fall 2015 2 Biz Analytics—Hot Topic BIG Data—What is It? Biz Analytics—Where did They Come From? Biz Analytics—What are They Like Now? Agenda Biz Analytics: Core Principles Types of Biz Analytics Data Quality Analytics Descriptive Analytics Diagnostic Analytics Prescriptive Analytics Predictive Analytics Semantic Analytics Boise State Executive MBA Program Fall 2015 3 http://www.informationbuilders.es/intl/co.uk/presentations/four_types_of_analytics.pdf QUIZ: What do Beer and Business Analytics Have in Common? Boise State Executive MBA Program Fall 2015 4 http://blueharbors.com/demand-analytics-software-continue-2017/ Why Are Business Analytics Such a HOT Topic? [1] Boise State Executive MBA Program Fall 2015 5 https://oneragingbull.wordpress.com/ Why Are Business Analytics Such a HOT Topic? [2] Boise State Executive MBA Program Fall 2015 6 http://www.slideshare.net/smongeau1/acfe-presentation-on-fraud Why Are Business Analytics Such a HOT Topic? [3] Boise State Executive MBA Program Fall 2015 7 VERACITY BIG DATA: What is It? [1] Boise State Executive MBA Program Fall 2015 http://med.cornell.libguides.com/HINF5008 VIABILITY 8 Data in Motion BIG DATA: What is It? [2] Data Usefulness Data in Many Forms http://www.patrickcheesman.com/how-big-data-cantransform-your-understanding-of-your-customers/ Data at Scale Data Uncertainty Boise State Executive MBA Program Fall 2015 9 “Data. Data. Data. I cannot make bricks without clay!” 1989, Erik Larson, author of “The Devil in the White City” and “In The Garden of Beasts,” wrote a piece for Harper’s Magazine, which was reprinted in The Washington Post: BIG DATA: Where Did It Come From? [1] Conclusion: “The keepers of big data say they do it for the consumer’s benefit. But data have a way of being used for purposes other than originally intended.” “The term Big Data, which spans computer science and statistics/econometrics, probably originated in the lunch-table conversations at Silicon Graphics in the mid-1990s, in which John Mashey figured prominently.” —Diebold, F. X., Cheng, X., Diebold, S., Foster, D., Halperin, M., Lohr, S., ... & Shin, M. (2012). A Personal Perspective on the Origin (s) and Development of “Big Data”: The Phenomenon, the Term, and the Discipline. (Working Paper). Retrieved from: http://www.ssc.upenn.edu/~fdiebold/papers/paper112/Diebold_Big_Data.p df See: Press, G. (May 9, 2013). A Very Short History Of Big Data. Forbes. http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-ofbig-data/ Boise State Executive MBA Program Fall 2015 http://www.mblast.com/marketing-return-on-investment/big-data-social-lead-discovery/ Sherlock Homes and the Etymology of the ‘Big Data’ Case 10 http://www.healthcareimc.com/node/727 Business Analytics: Where Did It Come From? [2] Boise State Executive MBA Program Fall 2015 11 http://www.slideshare.net/smongeau1/acfe-presentation-on-fraud Business Analytics: What’s It Like Now? Boise State Executive MBA Program Fall 2015 12 Business Analytics Core Principles: ADHD-RAT G IV E F Analyze, Discover, Haggle, and Decide (ADHD) upon an appropriate action, based on information that is: Relevant Actionable Timely Graph all metrics. Interact with information at the speed of business. Visualize data to highlight information patterns. Exercise 4: 5 min. Exercise gut feelings and intuition through simulation Forecast by enhancing visual patterns. Surma (2011), Case Study 2.1, (p. 27-32), Alpha Chain Stores: demonstrated business requirements analysis and proposed solution approach Boise State Executive MBA Program Fall 2015 13 What are the 6 Types of Business Analytics? [1] Boise State Executive MBA Program Fall 2015 14 http://sctr7.com/2014/07/09/twelve-emerging-trends-in-data-analytics-part-1-of-4/ What are the 6 Types of Business Analytics? [2] Boise State Executive MBA Program Fall 2015 15 http://digitalmarketingstrategy.ucd.ie/data-analysis-marketing-making-data-relevant/ Data Quality Business Analytics [1] Boise State Executive MBA Program Fall 2015 16 Data Quality: a perception or an assessment of the fitness of data to serve its purpose within a given context. Characteristics/Metrics of data quality include: Data Quality Business Analytics [2] Accessibility Accuracy Appropriate presentation Completeness Consistency across data sources Update status Relevance Reliability Boise State Executive MBA Program Fall 2015 17 https://tdwi.org/articles/2012/05/01/feature-ten-goals-for-next-generation-data-quality.aspx Data Quality Techniques Boise State Executive MBA Program Fall 2015 18 Decision Management Solutions - From Business Intelligence to Predictive Analytics http://www.slideshare.net/jamet123/from-business-intelligence-to-predictive-analytics Descriptive Business Analytics [1] http://whybinoexcuses.com/2015/03/09/moving-fromdescriptive-to-predictive-analytics-with-big-data/ http://www.collings.co.za/2011/07/message-over-media.html Boise State Executive MBA Program Fall 2015 19 Descriptive Business Analytics [2] looks at data and analyzes past events for insight as to how to approach the future. looks at past performance and understands that performance by mining historical data to look for the reasons behind past success or failure. Almost all management reporting such as sales, marketing, operations, and finance, uses this type of postmortem analysis. Boise State Executive MBA Program Fall 2015 Descriptive models/tools: quantify relationships in data in a way that is often used to classify customers or prospects into groups related to products and services. can be used, for example, to categorize customers by their product preferences and life stage. can be utilized to develop further models that can simulate large number of individualized agents and make predictions. For example, descriptive analytics examines historical electricity usage data to help plan power needs and allow electric companies to set optimal prices.” http://www.rosebt.com/blog/descriptive-diagnostic-predictive-prescriptive-analytics Descriptive analytics: 20 Diagnostic Business Analytics [1] Boise State Executive MBA Program Fall 2015 http://www.clickz.com/clickz/column/2323767/getting-started-with-real-time-analytics https://www.andertoons.com/business/cartoon/4619/i-think-i-speakfor-all-of-us-when-i-say-what-in-gods-name-are-you-talking-about 21 Diagnostic Business Analytics [2] used for discovery or to determine why something happened. For example, for a social media marketing campaign, you can use diagnostic analytics to assess the number of posts, mentions, followers, fans, page views, reviews, pins, etc. Thousands of online mentions that can be distilled into a single view to see what worked in your past campaigns and what didn’t. Boise State Executive MBA Program Fall 2015 Ask specific questions: “Where should we look?” (Discovery/Alerts) “Why did it happen?” (Query/Drill down) http://www.ingrammicroadvisor.com/data-center/fourtypes-of-big-data-analytics-and-examples-of-their-use Diagnostic analytics: 22 http://www.informationbuilders.es/intl/co.uk/presentations/four_types_of_analytics.pdf http://www.equest.com/category/cartoons/cartoons-2013/ Predictive Business Analytics [1] http://www.opsrules.com/supply-chain-optimization-blog/topic/analytics Boise State Executive MBA Program Fall 2015 23 Predictive Business Analytics [2] must be executable at a decision point action/events likely to happen Identify past patterns to predict the future turns data into valuable, actionable information. uses data to determine the probable future outcome of an event or a likelihood of a situation occurring. encompasses a variety of statistical techniques from modeling, machine learning, data mining and game theory that analyze current and historical facts to make predictions about future events. For example, some companies use predictive analytics for the entire sales process, analyzing lead source, number of communications, types of communications, social media, documents, CRM data, etc. Ask specific questions: “What will happen next” (Predictive Modeling) “What is the pattern?” (Statistical Modeling) Boise State Executive MBA Program Fall 2015 http://www.rosebt.com/blog/descriptive-diagnostic-predictive-prescriptive-analytics Predictive Analytics: 24 http://www.kdnuggets.com/2014/12/cartoonunexpected-data-science-recommendations.html Prescriptive Business Analytics [1] http://www.allanalytics.com/author.asp? section_id=1859&doc_id=277140 Boise State Executive MBA Program Fall 2015 25 Prescriptive Analytics: Prescriptive Business Analytics [2] automatically synthesizes big data, mathematical sciences, business rules, and machine learning to make predictions and then suggests decision options to take advantage of the predictions. goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the decision maker the implications of each decision option. suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and illustrate the implication of each decision option. provides a laser-like focus to answer specific questions. In practice, prescriptive analytics can continually and automatically process new data to improve prediction accuracy and provide better decision options. Ask specific questions: “What is the best action?” (Optimization) “What if we try this?” (Random Testing) Boise State Executive MBA Program Fall 2015 26 https://s-media-cacheak0.pinimg.com/736x/1f/dc/bb/1fdcbb 4964fe7b7824d09e3e4aa0a6b7.jpg Semantic Business Analytics [1] https://metaeconomics.wordpress.com/ Boise State Executive MBA Program Fall 2015 27 Semantic Business Analytics [2] a semantic knowledge model is a way to abstract disparate data and information, from linked, unstructured and structured data. knowledge modeling is about describing what data means and where it fits. we more easily understand and abstract knowledge. Consequently it helps us to understand how different pieces of information relate to each other. Uses links between IP Address nodes to build patterns, relationships, and meaning through the application of an Ontology concepts (controlled vocabulary) and Taxonomy of terms (BT, NT, RT, SN) For example, portfolio modeling in the financial services sector: Cannot simply analyze past performance Must take into account external indicators, political events or unrest, currency issues —impact company stock price. Need an underlying infrastructure that caters for dynamic changes to interrelated knowledge relevant to the portfolio. Ask specific questions: “Why is this possible?” “What does this mean?” (Random Testing) http://sparklingspur.com/all-about-appleiphone-4s-features-full-specification-and-price/ Boise State Executive MBA Program Fall 2015 https://fbhalper.wordpress.com/2007/11/29/whats-a-semantic-model-and-why-should-we-care/ Semantic Analytics: 28 http://daselab.cs.wright.edu/pub/2013-02-Siemens-BIGDATA.pdf Semantic Business Analytics [3] Boise State Executive MBA Program Fall 2015 29 http://daselab.cs.wright.edu/pub/2013-02-Siemens-BIGDATA.pdf Semantic Business Analytics [4] Boise State Executive MBA Program Fall 2015 30 http://daselab.cs.wright.edu/pub/2013-02-Siemens-BIGDATA.pdf Semantic Business Analytics [4] Boise State Executive MBA Program Fall 2015 31 http://lod-cloud.net/state/ Semantic Business Analytics [5] Boise State Executive MBA Program Fall 2015 32 https://onthegocio.wordpress.com/2 013/05/06/big-data-offers-no-value/ Boise State Executive MBA Program Fall 2015 http://blogs.position2.com/web-3-0-the-new-interactive-world http://www.informationbuilders.es/intl/co.uk/presentations/four_types_of_analytics.pdf Pause? 33 Section 3 Recap Boise State Executive MBA Program Fall 2015 34
