Self Service Analytics

Self Service Analytics

ENABLE AND SUPPORT SELF-SERVICE ANALYTICS IN FOUR SIMPLE WAYS 

“Rapid advancements in artificial intelligence, Internet of Things and SaaS (cloud) analytics and BI platforms are making it easier and more cost-effective than ever before for non-specialists to perform effective analysis and better inform their decision-making.” 

– Carlie J. Idoine, research director at Gartner

The way the organizations are embracing self-service analytics to help them enabling their sales and marketing professionals to be more competent and data-driven. Self-service analytics tools are encouraging business professionals to generate queries and reports on their own, which enables them to have potential insights without depending on data scientist to do that.  

Data and analytics leaders are increasingly adapting self-service analytics to support a data-driven culture within their organizations. This means that business users can learn easily to use analytics more easily and they can benefit themselves from effective BI tools which in turn drive favorable business outcomes in the process.  

Self Service Analytics

Four areas to build a strong foundation for self-service analytics (Recommendations by Gartner); 

  1. ALIGN SELF-SERVICE INITIATIVES WITH ORGANISATIONAL GOALS AND CAPTURE ANECDOTES ABOUT MEASURABLE, SUCCESSFUL USE CASES; to get the good outcomes for the organization, it is crucial to confirm the value of self-service approach in analytics and communicating its impact and likely successes. This also builds confidence and justifies the continued support for it.  Furthermore, self-service analytics encourages business users practice it to support their organisation various areas on their own.  
  1. INVOLVE BUSINESS USERS WITH DESIGNING, DEVELOPING AND SUPPORTING SELF-SERVICE; trust can be preserved between It teams and business users when they are executing successfully a self-service initiative. Forging trust by long term collaboration can result in long term self-service success. 

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  1. TAKE A FLEXIBLE, LIGHT APPROACH TO DATA GOVERNANCE; the success of self-service initiative depends largely on its data and governance model’s flexibility which should be enough to enable and support the free-form exploration of self-service users.  
  1. EQUIP BUSINESS USERS FOR SELF-SERVICE ANALYTICS SUCCESS BY DEVELOPING AN ONBOARDING PLAN; enthusiastic business users must be supported by analytics leaders in terms of guiding them carefully on how to use new tools for their specific business problems. An onboarding plan can help them automate and standardised this process by making it far more effective to use self-service analytics throughout the organisation.  
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