Abstract
AbstractData analytics projects have brought countless benefits and solutions to the world. As a result, many organizations have attempted to adopt data analytics in order to reap the benefits of these implementations and move forward with projects that involve big data or data science. However, research has shown that more than 50% of these projects fail—either due to incomplete projects or lacking expected business value. Data analytics is often perceived as a complex concept due to the focus on big data, which is characterized by large, disaggregated volumes of data, velocity, and the variety of data (to name a few). The objective of this study was to identify the challenges associated with data analytics projects being implemented. The contribution lies in the fact that, if organizations can identify potential challenges, precautions can be made to diminish the chance of possible pitfalls, therefore improving chances of successful project implementation. A Systematic Literature Review was done in order to identify academic publications relating to selected search terms, followed by a thematic analysis on the search results to identify challenges associated with data analytics projects. The major, most prevalent challenges identified included poor data quality, lack of management support, and miscommunication.KeywordsData analyticsBig dataProjectsChallenges
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