Multiple business intelligence (BI) platforms in an enterprise are here to stay.
Respondents to an informal social media survey that I've been running for the past couple of years report that 25% of organizations use 10 or more BI platforms, 61% of organizations use four or more, and 86% of organizations use two or more. No matter how hard enterprise IT organizations tried to rationalize and consolidate BI platforms, they were only going to be partially successful. While IT pros were tasked with platform consolidation efforts to get closer to the so-called "single version of the truth" and to achieve efficiencies and cost savings, business users fell in love with and didn't want to easily give up their favorite BI tools.
We called for the need of a "BI fabric" in our initial research in 2017 and later in our 2018 update of this report: Use BI Fabric To Optimize Your Multivendor Business Intelligence Environment, where we defined a BI fabric as:
Technologies and techniques that allow business insights pros to integrate, leverage, and reuse components from multiple business intelligence platforms.
Since then, this BI fabric baby has grown up -- not too much, but slowly, taking baby steps. We expected a much more rapid growth in this market. Enterprise IT's innate resistance to multiple redundant platforms and BI vendors' lack of enthusiasm in investing in integration with direct competitors are the two main factors slowing down BI fabric adoption. But in the end, business users win, and we currently see BI fabric manifesting in one or more of the following architectures and technologies:
A common BI portal: A single place to search, collaborate, create workflows and mash-ups, catalog, and secure objects (metrics, reports, dashboards, data visualizations, etc.) across different enterprise BI platforms. Sample players include BI Hub, Digital Hive, Metric Insights, and ZenOptics.
A common data catalog: A single place to catalog all data sources used by multiple enterprise BI platforms. This is also a single place (a common BI portal can also be used for this function) for data source governance — tagging data sources with the levels of data quality and approved use cases, promoting data sets from development to production, etc. Most of the platforms from The Forrester Wave™: Machine Learning Data Catalogs, Q4 2020, plus productized offerings from global system integrators like LTI's Mosaic Catalog can be used for this purpose.
BI platform as a semantic layer: A BI platform allowing other BI platforms to use its semantic layer as their own. The pickings here are slim, currently limited to players like Microsoft Power BI and MicroStrategy (the former only supports platforms that use XML for Analysis for data connection). Oracle Analytics Cloud and Oracle Analytics Server also support third-party connections to its semantic layer via Java Database Connectivity, but Oracle does not test nor specifically approves any competitor integration.
Platform-to-platform connectors: Capability to display a visualization/dashboard/report from a different BI platform. Current capabilities include Google Looker connectors to Qlik, Sisense, and Tableau and Yellowfin connectors to Microsoft SQL Server Reporting Services reports and TIBCO Jaspersoft.
Metadata integration — import/export of BI platform metadata using an exchange standard. A couple of decades ago, Metaintegration.net seemed like it was evolving as a BI metadata exchange standard. But for now, only IBM, Microsoft, Oracle, SAP, and SAS support the standard. And sadly, these are mostly good for platform-to-platform conversions and initial deployments.
Like it or not, multiple enterprise BI platforms and the need for BI fabric are here to stay.
This post was written by Vice President and Principal Analyst Boris Evelson, and it originally appeared here.