Create, deploy, and maintain analytic applications that engage users and drive revenue. See a Logi demo

Buying BI

Choosing an Embedded Analytics Solution:
5 Commonly Missed Criteria

By Alexandra Thrasher | February 5, 2019
Share on LinkedIn Tweet about this on Twitter Share on Facebook

Application teams looking to embed analytics can choose from dozens of vendors that deliver data visualizations and interactive dashboards. But if you only evaluate basic analytics features, you risk missing out on important sophisticated capabilities, warns Gartner in a recent report.

“Avoid the temptation to focus on providing users with elegant visualizations,” writes Gartner. “You don’t want to pick a platform and realize afterward that the software lacks a back end to get the data in a format that can be plugged into your application. Or maybe it lacks a security model to limit which user roles can view specific data.”

>> Gartner Report: 5 Best Practices for Choosing an Embedded Analytics Platform <<

What guidelines should application teams follow when selecting an analytics platform? Look for vendors that support the sophisticated business intelligence requirements that actually represent your application’s finished state.

Many application teams overlook these five important criteria in their embedded analytics evaluations:

Adaptive Security

Some vendors require you to replicate and maintain two separate security models. Consider whether you have the resources to set up and maintain multiple versions.

Ask vendors:

  • Will you need to replicate and/or maintain two distinct security models?
  • Do they support multi-tenancy?
  • Can you pass tenant, user, role, and rights via trusted APIs?
  • Can you lock down parts of your applications based on user roles and rights?
  • Can you secure a single visualization or dashboard based on user?

Branding and Custom Styling

Some vendors sacrifice customization and white-label dashboards in favor of ease of use. Look for a vendor that gives you total control over branding and styling to make sure the analytics will look and feel exactly like your application.

Ask vendors:

  • Can the analytics look and feel exactly like your brand?
  • Can you apply themes that globally style the analytics to match your application?
  • Can you use CSS and third-party styling frameworks?

Embedded Self-Service

Self-service analytics capabilities empower end users to ask new questions of their data without sending ad-hoc requests to the development team. Rather than exporting data or jumping into another application, users help themselves to what they need in the context of your software.

Ask vendors:

  • How do they support ad-hoc reporting?
  • Can you white-label and embed the self-service capabilities?
  • Can business intelligence users pick their own datasets?
  • Can you save your own analyses, then organize and share those analyses?
  • Can a self-service user create something and pass to your developers for broader adoption?
  • Can you customize capabilities based on user rights and roles to match self-service to their skill levels?

Empowering End-User Actions

Many analytics solutions deliver information and insights in context, but they fail to let users take action right then and there. Advanced capabilities such as integrated workflows, write-back, scheduling, sharing, and alerts empower end users to turn insights into action without leaving your application.

Ask vendors:

  • Can the host application and analytics communicate bi-directionally, passing information back and forth to drive user actions?
  • Can you write data back to a database?
  • Can you include workflows that initiate alerts or processes in other applications or systems?
  • Can you initiate pre- and post-query processes to support complex workflows?

Data Integration

You’ve already invested in your data model and infrastructure. It’s the heart of your application. Make sure your embedded analytics vendor can work with your tech stack.

Ask vendors:

  • Can you connect to your data as is, without specialized schemas?
  • Do you need to replicate your data into a proprietary data source?
  • Does the vendor support real-time analysis?
  • Can you use two different data sources in a single page?
  • Can you use a RESTful endpoint as a data source?

The right evaluation criteria can set you up for embedded analytics success. For more information on evaluating business intelligence and analytics vendors, read our BI Buyer’s Guide >

 

About the Author

Alexandra Thrasher is a customer content program manager at Logi Analytics, where she partners with application teams to get the most out of the Logi platform. Prior to Logi she was a solutions consultant at LinkedIn.

Subscribe to the latest articles, videos, and webinars from Logi.