Concept explainers
Self-service analytics and its pros and cons.
Self-service analytics includes training, techniques, and processes that empower end users to work independently to access data from approved sources to perform their own analyses using an endorsed set of tools. In the past, such data analysis could only be performed by data scientists. Self- service analytics encourages nontechnical end users to make decisions based on facts and analyses rather than intuition.
Pros associated with self-service BI and analytics.
1. Gets valuable data into the hands of the people who need it the most—end users.
2. Encourages nontechnical end users to make decisions based on facts and analyses rather than intuition.
3. Accelerates and improves decision making.
Cons associated with self-service BI and analytics.
1. If not well managed, it can create the risk of erroneous analysis and reporting, leading to potentially damaging decisions within an organization.
2. Different analyses can yield inconsistent conclusions, resulting in wasted time trying to explain the differences. Self-service analytics can also result in proliferating “data islands,” with duplications of time and money spent on analyses.
3. Can lead to overspending on unapproved data sources and business analytics tools.
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