Business Analysis Interview Questions [Analytics]

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No one knows business analysis like Fhyzics do, an accomplishment demonstrated over years of business analysis practice, teaching and research carried out by Fhyzics Business Consultants Private Limited. Fhyzics business analysis initiatives are supported by FIBBER, A Business Analysis wing, committed to the excellence in business analysis in corporate and academia. FIBAAR’s Business Analysis Schema is a holistic approach to business analysis and the only framework in the world that has the due focus on domains, core competencies, and peripheral competencies. For more details about FIBAAR, please visit

Business analysis skill set is analogous to that of a well-balanced tripod. The three legs represent domain, core competencies and peripheral competencies as laid out in the Business Analysis Schema. In an interview setup, a business analyst who demonstrates exemplary skills in all the three areas are a great asset to companies and it is not an exaggeration that companies are longing to have such business analysts.

Business Analysis Interview Questions [Analytics] are compiled by the consultants and business analysts of FIBAAR and fully customized to the needs of the individual as certain practices and regulatory framework are specific to a given region or country. Since it is a customized eBook as soon as your order is placed, we will need certain information from you to serve you better. On providing the requested information, you will be delivered the Interview Questions within one business day or roughly 24 hours.

Skills expected for a business analyst in analytics domain:
  • Should have intermediate level experience in R/SAS/SPSS/Python
  • Able to understand strong business process related to Oracle Financial module
  • Should handle large data sets and big data systems (Hadoop, Hive, SQL)
  • Strong Microsoft Excel, PowerPoint, and Access skills are required
  • Should have contribution to risk level management, service level agreements are required
  • They need to understand basic statistics and have knowledge of simple analytics techniques including basic predictive modeling
  • Ability to communicate complex quantitative analysis and algorithms in a clear, precise and actionable manner required
  • Should have prior knowledge of data quality principles and data governance
  • Should diagnose and troubleshoot system and able to handle complex programs
  • Should have prior knowledge of data sales principles and quality principles
  • Should be energetic and ready to face challenges with team
  • Ability of Inductive and deductive reasoning is an added advantage

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