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Expanding data literacy to include data preparation: building a sound marketing analytics foundation

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  • Sidney Anderson

    (Texas State University)

Abstract

The current digital landscape is evolving at an increasingly rapid pace where “data is the new oil” of the global economy. Like oil, extracting value from raw data is a complex process as it is not useful in its raw state. As data continue to be generated and relied upon, data literacy skills are becoming increasingly critical. Since data must be ‘prepared’ prior to its analysis, this paper highlights three core competencies—cleaning, transforming, merging (i.e., data preparation)—that are required to build a sound marketing analytics foundation. Expanding data literacy to include the ability to transform data from its raw state into a usable form will enhance students’ overall level of proficiency and marketability in marketing analytics. It is imperative to include the teaching of data preparation as part of the analytics curriculum in marketing analytics courses to ensure that students attain the greater level of data literacy. Data preparation assignments that will help students enhance their marketing analytics skillset, and increase their overall knowledge and marketability are included.

Suggested Citation

  • Sidney Anderson, 2024. "Expanding data literacy to include data preparation: building a sound marketing analytics foundation," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(2), pages 227-234, June.
    • Handle: RePEc:pal:jmarka:v:12:y:2024:i:2:d:10.1057_s41270-024-00293-3
    DOI: 10.1057/s41270-024-00293-3
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    References listed on IDEAS

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    1. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    2. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    3. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
    4. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    5. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
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