What Is Self-Service Analytics?

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Self-service analytics describes the use of technology by subject-matter experts to get relevant information without requiring computer coding or substantial information technology support. The purpose of self-service analytics gives business users and stakeholders the capacity to perform day-to-day tasks without “getting involved in a more critical data process.”

Characteristics of self-service analytics include the abilities to:

  • Share and trust data from multiple, disparate sources
  • Find and access relevant data
  • Secure data to meet legal and ethical requirements
  • Handle a wide variety of data formats and diverse types
  • Perform queries easily
  • Run reports without complication
  • Access a usable and more straightforward tool

These attributes make the self-service analytics key to the democratization of data, where everyone has access to information with very few gatekeepers and digital transformation.

Other Definitions Self-Service Analytics Include:

  • “Dynamic reporting capabilities to business users without the need for programming knowledge.” (Paramita Ghosh)
  • “Trends and patterns, obtainable by ordinary business users without technical help.” (Paramita Ghosh)
  • “A form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support.” (Gartner Glossary)
  • “The holy grail of enabling enterprises to take full advantage of their data for digital transformation initiatives related to customer experience, end-to-end business processes, and improved business decision making.”(Forbes)
  • “Technology designed to enable everyone to ask and answer their questions using trusted data to make informed business decisions, not just explore dashboards created by analysts.” (CIO)

Self-Service Analytics Use Cases Include:

  • Just-in-time information that a freight forwarder needs about where to reroute a seed shipment when the destination port has been closed due to political unrest or a strike
  • The automation of data access, preparation, analysis, and reporting for health care professionals so that a patient’s data can be accessed, analyzed, and processed for treatment
  • Financial advice from financial professionals with auto-prepared data that customers find timely and accurate

Businesses Require Self-Service Analytics to:

  • Booster existing business intelligence efforts
  • Gain first-hand insight from buyers
  • Free up Information Technology from the need to tailor data for business, allowing tech professionals to concentrate on their strengths
  • Build trust between IT and business users
  • Improve customer experience and drive growth

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