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Product leaders need analytics that scale with their app, not retrofitted BI tools. Looker offers strong visualizations and tight Google Cloud integration. But its use of LookML, iFrames, and user-based pricing makes it hard to embed in customer-facing products. 

As SaaS teams grow, these constraints slow development, increase costs, and limit flexibility. That’s why more teams are replacing Looker with Reveal—an embedded analytics platform built for speed, scale, and predictable pricing. 
This article breaks down where Looker fits, where it falls short, and why modern SaaS teams are moving on.

Legacy BI systems create technical debt, slow product delivery, and limit user experience. Modern embedded analytics delivers real-time, branded insights, scalable architecture, and predictable costs. This guide compares old and new approaches, outlines how to choose the right platform, and shows how Reveal’s SDK-based solution helps SaaS companies and ISVs modernize without disruption.

Traditional BI tools often fail to handle increasing user counts and expanding data volumes, resulting in higher costs and reduced SaaS product performance. Scalable analytics keeps dashboards responsive, insights up to date, and user adoption strong, all while maintaining cost efficiency. Reveal’s embedded analytics SDK delivers real-time performance, customizable dashboards, predictable pricing, and flexible deployment, making it an ideal solution for modern SaaS products.

Dive into the world of embedded BI (Reveal) and low-code (App Builder) and learn how these tools could accelerate your digital transformation efforts.

Learn how dashboard linking can provide seamless navigation between interconnected dashboards and enhance your data exploration.

As more organizations begin offering analytical capabilities as part of their apps, embedding analytics into your Blazor applications is no longer optional.

Embedding analytics into your React applications brings relevant and timely insights right within your user’s workflow, promoting a data-driven culture and encouraging more analytical thinking.  

While both purpose-built embedded analytics SDKs and iframes allow for the integration of data analytics capabilities in an application, they come with some key differences. In this blog we discuss these two options to determine their pros and cons so that you can decide which is best for you and your end users. 

The fastest way to monetize your data is by embedding white-labeled dashboards directly into your product. While the opportunity is clear, the execution isn’t always easy. Building in-house drains time, money, and dev resources, and choosing the wrong partner can lead to the same bottlenecks that stall monetization efforts.

Data warehousing supplies users with actionable insights and helps everyone within one organization make the right call on everything from marketing strategy and product development to human resources and budgeting.