| | December 20198CIOReviewIN MY OPINIONAnalytics has evolved. So have the titles of analytics professionals and conferences on analytics. With the Big Data adjective, analytics is being embraced by more and more organizations and being embedded in the decision-making processes not only at operational levels but also at strategic ones. Yes, the technological landscape for data analytics has changed rapidly, vastly for better. To configure a data analytics infrastructure today, one has a lot more options than it was a decade or two ago. Machine learning and AI are further bringing about renewed hopes in automated analytics especially with respect to financial advisory practices, regulatory compliance, and fraud prevention. In the meantime, the ushering of the CAO role across industries in recent years pointedly highlights the enterprise imperative that analytics be elevated in order for any organization to unleash its fuller potential and exert wider impact to help optimize processes, craft new strategies, and refine tactics, ultimately imparting competitive edge in areas such as product innovation, pricing maneuvers, marketing positioning, customer service, and the like. The fundamentals of analytics, however, have not changed. Any organization attempting to embrace just a Big Data project or a set of analytics technological investments without reasonably ensuring that the analytics fundamentals are in place would be amiss and soon discover the costly wagon-before-the-horse reality which plagued the CRM analytics field more than a decade ago.Analytics is still in the same business. Analytics technologies have changed. However, analytics is still in the same business: make sense of data. Regardless what we call it, insight or foresight generation, the descriptive, predictive, and prescriptive dimensions of analytics remain unchanged albeit the means of arriving at them, the speed of producing them, and their relative values to the business. Across the analytics maturity spectrum, organizations are found to be all over, from those who have established analytical capabilities to harness data to those who may be still struggling with getting the single version of the truth. Often, organizations are more prone to drown in the ocean of data and information than thriving on insights, to be precise, business relevant insights that are actionable, measurable, and profitable. Organizations that may be called analytical are reaping troves of treasures in their data repositories and have largely moved beyond merely the operational use of analytics, as strategic-insight focused analytics are unleashing significantly more value-added (as illustrated in the diagram below).Analytics still sits on the same foundation: data. Data and analytics go hand in hand at any organization. Analytics can rarely flourish on any data foundation that is fraught with quality and integration issues, letting alone data being accumulated at the variety, volume, and velocity unprecedentedly. Processes ensuring a high level of data quality are of paramount importance, and data integrity is a non-negotiable pre-requisite for any analytics endeavors. Data cleansing is now-a-days a much different endeavor than decades ago, thanks to the technological advancements. It is, nonetheless, still a sizable undertaking that needs to be dealt with ANALYTICS: WHAT HAS CHANGED AND WHAT HAS NOT?By Zhongcai Zhang, Chief Analytics Officer, New York Community Bancorp (NYCB)It is in this contextual perspective that an observed tepid demand for analytics at a given organization is often rooted in the problemsThe Analytics PyramidStrategic-Insight-Focused AnalyticsProduction AnalyticsReportingOperational ReportingPrescriptivePredictiveDescriptiveBusiness Impact
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