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Self-Governed Business Intelligence

The recent trend towards self-service business intelligence (BI) represents a significant paradigm shift in the way that businesses use data. The driving force behind this business shift is in giving information users the data they need, when they need it, to enable better decision making across the enterprise and reduce the burden on the organization’s IT resources.

As business demands and challenges have increased and the global business environment has become more competitive, the need to analyze and access data quickly, remain agile, and draw rapid insights, has become critical. Self-service BI enables end-users to combine and analyze large amounts of data independently, without the intervention of IT, which has made it a popular model in enterprises.

This focus is reflected in predictions for the future of business analytics and BI: Gartner placed self-service data discovery tools in the forefront of the leaders’ quadrant in the 2015 Magic Quadrant for Business Intelligence and Analytics platforms.

There are well known complaints/drawbacks to the traditional BI model. It can be cumbersome and time-consuming. Requests/briefs can be easily misunderstood, or the wrong data sets may be analyzed. It also places unnecessary time and resource constraints on the organization’s IT area.

The benefits of self-service BI may be less understood:

  • Democratization of Big Data. Self-service analytics makes the process of BI more democratic and inclusive, ensuring that all organizational areas and employees can be involved in the process of cultivating and deriving value from data.

  • Empowered business users. Employees are better empowered and can leverage data to gain informed insights and make better business decisions.

  • Agile and responsive data analytics. Instead of waiting for over-burdened IT or data science areas to prepare their data, users can undertake data exploration and verification, and visualize and report data on their own quicker than ever before.

  • Improved productivity. Self-service BI frees up IT and data science resources, improves the agility of data access and analysis, and makes it possible to make informed decisions more quickly.

As a result of these advantages, business users are adopting standalone self-service tools at an unprecedented rate. But despite the immediate benefits to business users, organizations must be cautious. Self-service BI needs to be implemented with the right overarching governance and procedural care employed. Without appropriate governance, long-term issues can be introduced, resulting in unnecessary downtime, loss of productivity, and negative financial impacts.

Business users are also often unaware of the complexities of data preparation and the risks involved in getting it wrong. Without strong data governance, they may also miss their own errors or draw inaccurate conclusions.

In addition to the internal impacts from a poorly governed self-service BI strategy, there are also very important elements such as regulatory and privacy requirements, government regulations, and legislative provisions that could have serious financial or reputation impacts on organizations. These drawbacks are also managed by a governance strategy.

Refer to the following resources to learn more about self-service BI:


This article is authored by PASS in collaboration with Pyramid Analytics. Pyramid Analytics’ mission is to deliver a Governed Data Discovery and Enterprise Business Analytics platform that gives the power of analytics into the hands of every user, from expert analyst to business executive, to IT professional.

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