Enterprise Business Intelligencev1.0

1. Summary

Enterprise Business Intelligence (EBI), in contrast to the newer self-service BI (SSBI) paradigm, has been around for several decades and has reached an impressive state of maturity and widespread adoption. It emphasizes stability, governance, an extensive feature set, industry-specific capabilities, and a measured, deliberate pace of enhancements over a long period. The industry has taken on board lessons learned from the SSBI product category and begun modernizing the user experience, introducing machine learning and predictive analytics capabilities, and enabling cloud deployment options. Its vendors have also succeeded in keeping pricing robust enough for healthy revenue growth.

This means that EBI will continue to thrive by emphasizing its strengths, taking on additional lessons from its SSBI competitors, integrating and enhancing the best of their ideas, and continuing to serve large enterprises’ critical workloads for many more years.

In this report, we explore EBI products and technologies, outline the key differentiating factors between the major offerings, and identify major vendors. We also describe how organizations can take advantage of the EBI feature set in order to achieve their goals and satisfy their stakeholders.

Key findings:

• Most vendors are gravitating towards the general term Analytics for their Enterprise BI offerings; we believe the term to be a bit too generic and continue to use EBI in this report.
• The majority of vendors also offer self-service solutions in addition to their main EBI offering; integration is still a work in progress for many.
• Major differentiating factors between vendors include: pre-packaged industry-specific solutions, specialized applications such as econometrics, financial planning & analysis, business scenario modeling, and user experience enhancements. This is in addition to the base analytics feature set.
• Several vendors base their EBI offerings off of their own relational or in-memory database systems.
• All vendors offer extensive connectivity to on-premises and cloud-based relational and Big Data sources. Some also offer connectivity to cloud applications and to SSBI competitors.
• Predictive modeling and machine learning capabilities are a significant point of new functionality and a focus of vendor enhancements. Voice searching, augmented reality, and mobile enhancements also seem top-of-the-list for additional investment by vendors.
• User experience, while still mostly lagging behind SSBI, is rapidly improving for most vendors.
• EBI puts the IT department at its core. The vendors tailor their platforms to emphasize stability and control, auditing, governance, traceability, data lineage, and master data management. These capabilities are typically not available in self-service tools, though they do make appearances in standalone products for the self-service audience, in much the same way data preparation surfaces in that market.
• EBI vendors typically employ extensive sales forces and experience long sales cycles. The industry typically eschews transparent pricing and is associated with hefty price tags for initial acquisition, annual maintenance, and operations. Pricing pressure from SSBI has resulted in some pricing elasticity and transparency, especially for cloud-specific offerings.
• Implementation of the vendors’ offerings is typically a complex affair. Most enterprises tend to use specialized or vendor-provided consulting resources to augment their IT department.
• Changing EBI vendors is a strategic undertaking since most enterprises have invested years of spending in implementation and skills acquisition. In addition, critical processes that form the core of the enterprise’s operations (e.g. core financials) tend to run on EBI platforms, making a vendor change risky.
• Most vendors offer a variety of capabilities. We have found that the major areas on offer include:
  1. • Built-in relational and in-memory database systems
     • Modern data visualizations
     • Pixel-perfect reporting capabilities
     • A variety of connectors to disparate on-premises and cloud data sources
     • Data integration and visual extract, transform, and load (ETL) aimed at technical users
     • Pre-built, industry-specific solutions and specialized applications
     • Data governance, auditing, traceability, data lineage, and master data management capabilities
     • Predictive analytics and machine learning capabilities
     • Embedding, programmability, and data science platform integration aimed at developers
     • Mobile capabilities for iOS and Android
     • On-premises, public, private, hybrid, and managed cloud deployments