architectedGovernance is a classic IT topic. But to govern the massive amounts of data now growing organically across the enterprise, you’ve got to think differently than in the past. Birst CEO Jay Larson and I have recently blogged about the building blocks of governance for big data. These topics include:

With this blog I’ll drill down further, delving into platform architecture details.

Do you believe?

But first, let’s talk about the principles, or beliefs, that should inform your governance strategy. For enterprise-class data analytics and business intelligence (BI), these beliefs should include:

  • BI is for everyone – not just analysts or experts.
  • Many cross functional metrics should be defined only once, across the business.
  • The data problem is bigger than the visualization problem.
  • Only a real networked analytics architecture delivers business agility at both the end user and IT/server level.

A two-tier architecture governs data and empowers users

To develop an analytics and BI environment that supports those beliefs, point solutions won’t work. You’ve got to choose an analytics platform that supports a two-tier data architecture. Here’s why: only a two-tier architecture gives CIOs the data consistency required to enable trust across different deployments and deliver the analytic agility business users need to work freely and manipulate local – or enterprise data – transparently.

Take a look at this diagram of a two-tier architecture:

Pookie_Screen Shot 2015-09-24 at 4.22.19 PM_JA

Note the bottom layer. What’s important here, from a governance perspective, is that users are not accessing unmanaged data stores directly. This is what happens with point solutions when there is no means to properly curate the data, and when each solution may point to a different subset of the enterprise dataset. That’s why point solutions can exacerbate BI silos and create inconsistencies in the analysis of enterprise business conditions.

This 2-tier BI analytics platform plugs into centrally managed data sources – data warehouses, data lakes, business applications – and seamlessly unifies them with data generated by decentralized teams throughout the organization.

The platform automatically refines this data and prepares it for analysis by transparently overlaying a consistent set of business rules and definitions, creating a single view for all business users. It delivers an adaptive user experience that seamlessly transitions between reports, dashboards, visual discovery, and mobile.
Winning through governed enablement

In this way, CIOs can meet end-user demand for self-service capabilities without sacrificing governance and trust in the data. A two-tier architecture bridges the gap between centralized BI teams supporting enterprise requirements and user-led decentralized teams looking for greater autonomy and more department-centric use cases.

This is what we mean when we talk about the power of strategic, multi-tenant analytical business intelligence platforms. When CIOs set the standard for bringing together centralized and decentralized data analytics platforms in their organization, they’re not just leading, they’re winning.

To learn how Birst’s two-tier architecture governs data and empowers users, click here.

The preceding is a blog post originally published in CIO on October 1, 2015.