Data Analytics – Creating Business Value with Data and Analytics: Supporting Material

This page contains resources used to support TU/e post-master course on Data Analytics (lecturer Zeljko Obrenovic).


Free Resources on Basic Analytic Techniques

Web Analytics

Telling stories with data

  • Story-based inquiry: a manual for investigative journalists, The publication focuses on the hypothesis-based inquiry approach, which takes the basic assumption that a story is only a hypothesis until verified. The methods and skills applying to every step of the investigative process, from conception to research, writing, quality control and dissemination, have been thoroughly analyzed and are well illustrated by case studies in each chapter.
  • Data Journalism Handbook
  • Analytics Meets Mother Goose, Want to get your point across about data? You’d better learn to tell stories. The “last mile problem” of analytics.
  • The Dark Side of Applying Analytics to Journalism, AOL has “designed a system called Seed, a hybrid of journalism and engineering. Seed is based on the idea that editors can figure out what stories to assign by mining data from search engines like Google and social networks like Facebook. If algorithms can tell you what people are talking about, and what they’re searching for, then you know what they want to read.


  • Better Decision Making with Objective Data is Impossible, Data is not the same thing as facts. Data requires analysis — which is replete with subjective interpretation. The objectivity of data is a myth. Modern analytical methods afford creative and flexible uses of data that can support multiple perspectives and competing analyses about the same data sets.
  • Detecting Bias in Data Analysis, How you handle your data — from cleanup through presentation — affects the results you’ll get.
  • Minding the Analytics Gap, a gap between an organization’s capacity to produce analytical results and its ability to apply them effectively to business issues
  • The Emergence of the Extra-Rational Manager, just as revolutions in science are preceded by revolutions in measurement, so, too, are revolutions in business preceded by revolutions in measurement. Could managers improve their ability to manage if they knew who is talking with whom, and how often, and where these conversations are taking place and what the tone of these interactions are?
  • Raising the Bar With Analytics, We can take our technology and put it on partner sites [to help them get] a deeper understanding of what’s happening with customers — what’s working and why.
  • Winning With Data, giving companies “radically improved measurement” capabilities
  • New opportunities for data analysis, the rapid growth of “digital data”  — everything from public records in digital form to information generated from social network traffic  — creates all kinds of new opportunities for statistical analysis — and for statisticians.
  • New Horizons in Data AnalyticsIT Professional, vol.17, no. 4, pp. 20-22, July-Aug. 2015, Analytics has become a hot topic, putting increased pressure on IT organizations to provide new ways of making sense of customer and operational data. The theme of data analytics with application in four areas related to knowledge development and utilization: the institution of education itself, optimizing knowledge sharing in communities, gaining and applying business insights, and the state of the knowledge and skills gap in China.
  • Data Analytics Makes the Transition From Novelty to Commodity, What happens when the use of analytics in business stops being new and different?
  • The Four Traps of Predictive Analytics, Magical thinking, starting at the top, building cottages not factories, seeking purified data.
  • Revisiting Complexity in the Digital Age, Imagine a retailer that has 10 million products and hundreds of variations for each product yet keeps it simple for customers to make a choice. Impossible? Not today. Inc. creates value from its product complexity with simple customer-facing processes, such as search, ratings, reviews and suggestions.
  • A New, Analytics-Based Era of Banking Dawns at State StreetState Street Global Exchange (SSGX), a new business launched in April 2013, which enables the organization to partner with its clients to apply a wrapper of information, insights and analytics around the investment process.
  • Harnessing Quant Power, Framing the problem. Solving the problem. Communicating and acting on results. This new era of computational prowess does not obviate the need for intuition and creativity, and that is especially true in the important first step of framing a problem. Half the battle in problem solving and decision making is framing the problem or decision in a creative way so that it can be addressed effectively.
  • When an IT Project “Goes Red”, Declaring to your whole company that the project everyone is excited about is in trouble can be demoralizing. But it’s exactly what can turn things around.
  • In Experiments We Trust: From Intuit to Harrah’s Casinos, the company’s continued focuses on data analysis and small-scale testing that can scale into company-wide initiatives. These tests run from the use of coupons to offers of free meals or hotel stays, all designed to get customers to spend more money during their playtime.
  • Webcast Recap: Get Started Today Using Analytics, As data floods into the company, as we go from an information desert to an information jungle, the bottleneck at the tops of organizations gets more and more constraining.
  • The Science of Managing Black Swans, “black swan” phenomena are highly unlikely events that have massive impacts on a business or society on the rare occasions they occur. By exploiting many types of data, managers can help prevent (or at least contain) the damage related to black swan events and other risky blind spots. The caveat: organizations should rely less on management experience and intuition and rely more on integrated data to point to potential risks (see Managing Risks with Data).
  • From the Editor: Decision Making in the Digital Age, even when you have plenty of data, making wise decisions about topics like strategy can be challenging. And no matter how much data we collect and analyze, our perspectives are still colored by human foibles.
  • Overheard at MIT, The limitations of data. Not every decision should be data-driven.
  • Lessons From Analytical Innovators, engendering the beliefs, practices, and outcomes characteristic of Analytical Innovators; enabling the success factors required to excel in today’s analytics revolution; creating a framework that shows how your company — regardless of analytical sophistication — can become more like Analytical Innovators; and succeeding in action
  • Innovating With Analytics, Our competition uses a psychological-based methodology and they work closely with psychologists. believes that every psychological theory is different, so it becomes difficult to have something that is concrete as opposed to a mathematical equation. We haven’t seen much in the market quite like it. Plus the unique thing about is that we have billions of data points from the last 17 years to analyze.
  • Why Our Minds Swap Out Hard Questions For Easy Ones, When faced with a difficult question, we often answer an easier one instead, usually without noticing the substitution.
  • Tim Harford on Trial, Error and Our “God Complex”, companies that have a God complex look for smart people (what he calls “little Gods”) to solve complex problems — when what they should really be doing is establishing systematic processes of trial and error.
  • Location Analytics: Bringing Geography Back, The relatively new market of location analytics is expanding the uses of more traditional geographic information system (GIS) technology to include social, geographic, physical and emotional indicators that help organizations better predict trends, according to ABI Research, which forecasts that the location analytics market will grow to $9 billion by 2016.
  • The Secrets to Managing Business Analytics Projects, project managers’ most important qualities can be sorted into five areas: (1) having a delivery orientation and a bias toward execution, (2) seeing value in use and value of learning, (3) working to gain commitment, (4) relying on intelligent experimentation and (5) promoting smart use of information technology.
  • “Mapping the TV Genome” at Bluefin Labs and Big Data’s Big Stats, Software engineers who understand analytics algorithms are in huge demand, and “65% percent of data professionals expect a deficit in expertise in the field over the next five years, according to a report from EMC Corp. The data and analytics marketplace is now worth $64 billion, according to a McKinsey Global Institute estimate.

Business Value




Social media


Big data

Software Analytics

Business Intelligence (BI)



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