Unmanaged Self-service leads to Unreliable Insights

Unmanaged Self-service leads to Unreliable Insights
admin | March 21st, 2016

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Can “self-service” be truly autonomous? Can today’s self-service products be used to perform data unification, preparation and analysis to successfully glean relevant, unambiguous business insights in the absence of IT involvement? Enterprises today are ill-prepared for self-service initiatives that are not managed by IT.

Why is self-service attractive?

Self-service Data Unification, Data Preparation (SSDP), and Business Intelligence & Analytics (SSBI) are popular because they offer tremendous latitude to the business users in accessing data sources, performing analyses and building visualizations. By employing these products, business users reduce their dependence on IT in an attempt to achieve more timely insights and shorter time-to-market. Likewise, in their desire to become more data-driven, organizations are augmenting their existing enterprise solutions with self-service products, or else leveraging self-service products when no other solutions are in place.

Potential ramifications of self-service

Organizations should be aware of potential impacts of deploying self-service products including the following:

  • Unreliable insights due to siloed use in which business users define their own rules for analysis.
  • Performance implications when the underlying infrastructure is not managed efficiently, or when data sources are accessed directly without assessing impact.
  • Security risks due to lack of granular security built into the self-service products, necessitating additional security in the underlying data sources.
  • Rise in costs due to many siloed implementations resulting in lack of visibility across implementation.

Is this the era of managed self-service?

IT is unable to keep up with increasing demands from Business. In order for enterprises to foster agility and remain competitive, IT must consider shifting responsibilities such as unification, preparation and analysis of data to business users while at the same retaining control of the underlying environment. Self-service products are in the process of automating discovery and application of best practices such as governance and quality rules, and enhanced collaboaration features. Until these capabilities are sufficiently robust in self-service tools, IT should manage and govern self-service initiatives in order to uphold best practices. Specifically, IT should enact necessary measures such as establishing a solid self-service strategy through collaboration with business, exploiting existing enterprise-scale technologies as part of the self-service initiatives, and bringing enterprise visibility to siloed use.

Category: Managed Self-service Self-service Analytics