The conditions of peak empiricism in big data and interaction design

An influx of mechanisms for the collection of large sets of data has prompted widespread consideration of the impact that data analytic methods can have on a number of disciplines. Having an established record of the use of a unique mixture of empirical methods, the work of understanding and designing for user behavior is well situated to take advantage of the advances claimed by “big data” methods. Beyond any straightforward benefit of the use of large sets of data, such an increase in the scale of empirical evidence has far-reaching implications for the work of empirically guided design. We develop the concept of “peak empiricism” to explain the new role that large-scale data comes to play in design, one in which data become more than a simple empirical tool. In providing such an expansive empirical setting for design, big data weakens the subjective conditions necessary for empirical insight, pointing to a more performative approach to the relationship between a designer and his or her work. In this, the work of design is characterized as “thinking with” the data in a partnership that weakens not only any sense of empiricism but also the agentive foundations of a classical view of design work

Incorporating Data Governance Frameworks in the Financial Industry

Data governance frameworks are critical to reducing operational costs and risks in the financial industry. Corporate data managers face challenges when implementing data governance frameworks. The purpose of this multiple case study was to explore the strategies that successful corporate data managers in some banks in the United States used to implement data governance frameworks to reduce operational costs and risks. The participants were 7 corporate data managers from 3 banks in North Carolina and New York. Servant leadership theory provided the conceptual framework for the study. Methodological triangulation involved assessment of nonconfidential bank documentation on the data governance framework, Basel Committee on Banking Supervision\u27s standard 239 compliance documents, and semistructured interview transcripts. Data were analyzed using Yin\u27s 5-step thematic data analysis technique. Five major themes emerged: leadership role in data governance frameworks to reduce risk and cost, data governance strategies and procedures, accuracy and security of data, establishment of a data office, and leadership commitment at the organizational level. The results of the study may lead to positive social change by supporting approaches to help banks maintain reliable and accurate data as well as reduce data breaches and misuse of consumer data. The availability of accurate data may enable corporate bank managers to make informed lending decisions to benefit consumers