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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