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Data Literacy: Developing Skills on Exploring Big Data Applications

Author

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  • Dimitar Christozov

    (American University in Bulgaria, Blagoevgrad, Bulgaria)

  • Katia Rasheva-Yordanova

    (University of Library Studies and Information Technologies, Sofia, Bulgaria)

Abstract

The article shares the authors' experiences in training bachelor-level students to explore Big Data applications in solving nowadays problems. The article discusses curriculum issues and pedagogical techniques connected to developing Big Data competencies. The following objectives are targeted: The importance and impact of making rational, data driven decisions in the Big Data era; Complexity of developing and exploring a Big Data Application in solving real life problems; Learning skills to adopt and explore emerging technologies; and Knowledge and skills to interpret and communicate results of data analysis via combining domain knowledge with system expertise. The curriculum covers: The two general uses of Big Data Analytics Applications, which are well distinguished from the point of view of end-user's objectives (presenting and visualizing data via aggregation and summarization [data warehousing: data cubes, dash boards, etc.] and learning from Data [data mining techniques]); Organization of Data Sources: distinction of Master Data from Operational Data, in particular; Extract-Transform-Load (ETL) process; and Informing vs. Misinforming, including the issue of over-trust vs. under-trust of obtained analytical results.

Suggested Citation

  • Dimitar Christozov & Katia Rasheva-Yordanova, 2017. "Data Literacy: Developing Skills on Exploring Big Data Applications," International Journal of Digital Literacy and Digital Competence (IJDLDC), IGI Global, vol. 8(2), pages 14-38, April.
    • Handle: RePEc:igg:jdldc0:v:8:y:2017:i:2:p:14-38
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