Self-Service Business Intelligence Resulting in Disruptive Technology

Schlesinger, Peggy a; Rahman, Nayem

doi:10.1080/08874417.2015.11645796

Cited by 39 publications

(29 citation statements)

References 32 publications

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“…When formulating queries, a beneficial way of properly using data from different sources is to apply metadata (also referred to as a semantic layer). The use of metadata to properly formulate queries from different sources ensures that errors are avoided [15,20].…”

Section: Challenge #13: Use Correct Data Queriesmentioning

confidence: 99%

“…A challenge to overcome is to ensure that BI tools can be easily used by non-technical users [2,3,15]. According to Imhoff and White [2], 78% of their 587 respondents rated this challenge as very important; which was also considered one of the highest ratings of the four objectives of SSBI.…”

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

“…According to Imhoff and White [2], 78% of their 587 respondents rated this challenge as very important; which was also considered one of the highest ratings of the four objectives of SSBI. If BI tools are not easy to use and do not support user requirements, users tend to develop their own limited solutions, which are not always correct [15]. The aim is to abandon uniform guessing, when making decisions, by enabling casual users to employ true data-driven BI tools that are easy to use [3,6,15].…”

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

“…If BI tools are not easy to use and do not support user requirements, users tend to develop their own limited solutions, which are not always correct [15]. The aim is to abandon uniform guessing, when making decisions, by enabling casual users to employ true data-driven BI tools that are easy to use [3,6,15]. When casual users have been given the flexibility to choose, use and manipulate the data they need, as well as the support required to understand the underlying algorithms, they are able to make better decisions on time, which improves business productivity.…”

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

“…When casual users have been given the flexibility to choose, use and manipulate the data they need, as well as the support required to understand the underlying algorithms, they are able to make better decisions on time, which improves business productivity. Users can thus more freely conduct analyses in more depth, without help from power users [2,15].…”

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

See 4 more Smart Citations

Implementation Challenges of Self Service Business Intelligence: A Literature Review

Lennerholt¹,

Laere²,

Söderström³

2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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In a traditional Business Intelligence (BI) system, power users serve less experienced casual users. Power users analyze and gather data requested by casual users, and produce the reports and visualizations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organizations fail to implement SSBI. The literature review presented in this paper discusses six SSBI challenges related to "Access and use of data" and four challenges related to "Self-reliant users". Awareness of these ten challenges can help practitioners avoid common pitfalls, when implementing SSBI, as well as guide SSBI researchers in focusing on their future research efforts.

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Section: Challenge #13: Use Correct Data Queriesmentioning

confidence: 99%

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

Section: Challenge #21: Make Bi Tools Easy To Usementioning

confidence: 99%

See 3 more Smart Citations

Implementation Challenges of Self Service Business Intelligence: A Literature Review

Lennerholt¹,

Laere²,

Söderström³

2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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30 Years Business Intelligence: FromData Analytics to Big Data

Linden

2021

Integrated Series in Information Systems

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Cultivating Data Practices Across Boundaries: How Organizations Become Data-driven

Pedersen,

Bossen

2024

Comput Supported Coop Work

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In this paper, we analyze the efforts of a public healthcare business intelligence unit to implement and disseminate their data products and thus make the healthcare organization more data-driven. The paper is based on ethnographic fieldwork in a healthcare business intelligence unit (the BIU) whose mission is to improve healthcare efficiency and quality by making data and data analyses available to healthcare managers and staff. Their primary products consist of a data warehouse and Data Reports, both providing curated and daily updated data for healthcare staff to analyze and visualize. We conceptualize these Data Reports and the data warehouse as boundary objects through which cooperation around data between various users is achieved. Our focus is on the BIU’s efforts to introduce and promote the use of boundary objects to healthcare staff while providing them with the competencies to use them in practice. Efforts that we conceptualize as collaborative boundary work through which a new joint field of working with data is created between the BIU and healthcare staff. Based on the analysis of the ethnographic fieldwork, we point to three important aspects in creating this new joint field: Mobilizing interest, building local capabilities, and propagating data locally. The paper makes three contributions: It adds to our understanding of how new joint fields can be cultivated through collaborative boundary work to make healthcare data-driven; it contributes to the emergent field of data work studies; and finally, it adds to the largely normative literature on business intelligence and self-service business intelligence through an ethnographic analysis of its efforts to make healthcare data-driven.

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Self-Service Business Intelligence Resulting in Disruptive Technology

Cited by 39 publications

References 32 publications

Implementation Challenges of Self Service Business Intelligence: A Literature Review

Implementation Challenges of Self Service Business Intelligence: A Literature Review

30 Years Business Intelligence: FromData Analytics to Big Data

Cultivating Data Practices Across Boundaries: How Organizations Become Data-driven

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