{"id":551,"date":"2019-02-09T13:47:01","date_gmt":"2019-02-09T12:47:01","guid":{"rendered":"https:\/\/www.michaelagreiler.com\/?p=551"},"modified":"2019-02-17T19:12:08","modified_gmt":"2019-02-17T18:12:08","slug":"keynote-about-data-driven-decision-making","status":"publish","type":"post","link":"https:\/\/www.michaelagreiler.com\/keynote-about-data-driven-decision-making\/","title":{"rendered":"Keynote about data-driven decision making"},"content":{"rendered":"\n

This keynote about data-driven decision making, I gave at the International Conference on the Quality of Information and Communications Technology<\/a> in Portugal. I highlight the benefits of data-driven decision making and show which pitfalls are to avoid.<\/p>\n\n\n\n

\u201cYou can\u2019t control what you can\u2019t measure\u201d<\/p>Tom DeMarco<\/cite><\/blockquote>\n\n\n\n


Abstract: <\/strong>Tom DeMarco states that \u201cYou can\u2019t control what you can\u2019t measure\u201d. But, how much can we change and control (with) what we measure? In this keynote, I investigates the opportunities and limits of data-driven software engineering.<\/p>\n\n\n\n

I show which opportunities lie ahead of us when we engage in mining and analyzing software engineering process data.<\/p>\n\n\n\n

I also highlights important factors that influence the success and adaptability of data-based improvement approaches.<\/p>\n\n\n\n

In this keynote about data-driven decision making, I clearly show that understanding the collection process of the data is crucial. This ensures that we understand the quality of the collected data which influences the quality and validity of the analysis and outcome. <\/p>\n\n\n\n

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