SCTR7: Data Science and Analytics

Analytics professionals should keep a persistent eye open for opportunities to create cross-functional insights from data. Insights can frequently be leveraged across multiple business domains. However, business silos can restrict ‘forest for the trees’ visibility. To the degree analytics has cross-functional exposure in the organization, for instance via a C-level champion and an Analytics Center […]

The adage ‘garbage-in-garbage-out’ is an analytics mantra so ingrained it has its own shorthand: GIGO. Yet, in the mad, blind rush toward all things ‘big data’, there is the danger of sidelining the crucial-but-dreary topic of data quality, to which GIGO refers. While data quality is not as ‘sexy’ as big data, anyone who wants […]

As an analytics professional, it may perhaps be no surprise that I believe in a world which is susceptible to analysis – a world which yields to scientific inquiry. Further, I believe that if we invest effort, if we exert what Kahneman would call our System 2, we can improve decisions and overcome our tendency […]

Business Analytics E-Learning Courses Developed by SARK7 for Accenture Academy I.  Introduction to Business Analytics FREE ONLINE NOW! ————————————————————— II. Defining the Business Analytics Process Business analytics is a process that transforms data into insights to drive value-creating decisions. It connects organizational problems to data that is analyzed using various methods, software tools, systems, and experts. […]

Increasingly sophisticated analytics tools and methods are available to derive business insight from data.  However, as a discipline which drives insight from data, the crucial ‘last step’ in the analytics process is about organizational decision making.  A sophisticated, intensive analysis may all be for naught if the crucial last step, framing and committing to a decision, misses the […]

As a companion to my recent post “Correlation versus Causation: The Science, Art, and Magic of Experimental Design”, I wanted to offer a more technical exposition concerning data science approaches to focused causal model development. A fundamental question faced by business analytics professionals and data scientists is whether they have a working correlative and causal […]

Recently I was chastised for being ‘unnecessarily obscure’ for reacting to a specious conclusion by suggesting that it risked ‘conflating correlation with causation’. Guilty as charged!  I apologize:  the expression is quite a mouthful and requires unraveling for those unfamiliar with the nuances of the applied experimental method.  However, I feel passionately that this concept […]

  This is a review committee working group for practitioners and academics to establish a formal definition and set of classification criteria regarding business analytics model risk. This group has been established based upon interest and feedback concerning a recent set of posts regarding business analytics model risk: http://tinyurl.com/ktabt3q For those interested, you can join the […]

PART 6 OF 7 IN A SERIES ON ADOPTING ANALYTICS CULTURE LINK TO HEADER ARTICLE LINK TO PREVIOUS ARTICLE (5 of 7) 6.    What particular information is gained from social network analysis and how is it interpreted? To recap, we have established that adopting analytics culture requires organizational change management.  Beyond analytics technology and expertise, […]

Business analytics model risk (part 0 of 5): framing model risk – the complexity genie and the challenge of deciding on decision models Introduction to a series of five articles on model risk Here we introduce a series of five articles seeking to frame, define, and categorize business analytics model risk.  The intention is to […]