To improve data quality, the marketing and advertising industry could establish a “Principles of Data Quality” disclosure; create a roster of items to ask of data suppliers; request transparency—data firm disclosures—including consumer authentication procedures, multiple data source descriptions, model target techniques and testing results, recency of data, integration techniques, data labeling, and top-line descriptions for all of the above; create best practice standards.
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Want to understand Data Science basics? This brief presentation covers the background behind the growth of the Data Science discipline, explains how this growth is affecting careers, gives an overview processes used, and provides a case study to illustrate the application of key principles.
Some say Artificial Intelligence is a broad field that includes everything from simple if-then rules for playing Checkers to complex ensembles of deep neural networks for piloting autonomous vehicles. In marketing, AI is a term that is applied to several very different techniques and functions. However, the bigger questions are: how do you best implement AI and what are the commercial solutions?
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Addressable consumer profiles across media. Actionable data. Connected technology. LiveRamp and RAPP offer suggestions on how to leverage these inputs, using signals from a range of sources including location, transactional and online behavioral data to create more robust consumer/customer profiles and segments that lead to better outcomes.
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