Below the Surface of the Data Lake
An Ethnographic Case Study on the Detrimental Effect of Big Data Path Dependency at a Theme Park
Bibliographic Data
| ID | 5948118 |
|---|---|
| Authors | Jacob Wachmann (ReD Associates), Andreas Juni (ReD Associates), Dave Baiocchi (0009-0000-6937-8579, ReD Associates), William Welser (ReD Associates) |
| Year | 2018 |
| Volume | 2018 |
| Issue | 1 |
| Pages | 631-645 |
| Publication date | 2018-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ethnographic Praxis in Industry Conference Proceedings (CONFERENCE) |
| Journal identifiers | ISSN: 1559-890X • E-ISSN: 1559-8918 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/1559-8918.2018.01226 |
| OpenAlex | W2914642160 |
| Language | EN |
| Citations received | 1 |
| References cited | 3 |
This case-study details how a team of anthropologists and a team of data scientists sought to help a Middle Eastern theme park make use of their big data platform to measure 'the good customer experience'. Ethnographic research within the theme park revealed that visitors yearned to bond with the other members of their group, as they rarely got the chance during their busy everyday lives back home. However, trying to build a measurement of how the theme park delivered on bonding - through the development of a 'bonding index' - turned out to be unfeasible, because the big data platform focused on capturing operational data. The decision to focus on operational data had unintentionally created a path dependency that made the big data setup unfit for answering some of the theme park's most fundamental questions. This is a problem ReD Associates has observed across clients and to solve it this paper suggests that companies start with an open-ended, ethnographic study of their big data needs before they build a big data platform. This will enable companies to be more strategic about their digitalization and thus maximize its impact
Archaeology · Big data · Data mining · Data science · Dependency (UML · Ethnography · Everyday life · Focus (optics · Geography · Path (computing · Political science · Public relations · Sociology · Theme (computing · Theme park · Tourism · World Wide Web · Big Data and Business Intelligence · Computer Science · Customer Service Quality and Loyalty · Technology Adoption and User Behaviour · Artificial Intelligence
| Citations per year | 0.13 |
|---|---|
| Citation span | 2018 - 2018 (1) |
| Highly cited | No |