Storytelling is more than just data visualization. Storytelling provides an organized approach for conveying data insights through visuals and narrative. Data-driven storytelling could be used to influence user actions, and ensure they understand what data matters the most. A good data story is formed by three components: Data analysis - This is the basis of a strong story and mastering the data is an essential part of the process.

Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features. Otherwise, it can lead to a low adoption rate and a poor product experience.

Every application provider has the same goals: to help their users work more efficiently, and to drive user adoption. But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Meeting requirements alone is no longer enough. Today’s users need insightful reporting built on accurate, real-time data. In our eBook, you’ll learn the do’s and don’ts to embedding operational reports, and how to avoid common reporting mistakes.

Outdated or absent analytics won’t cut it in today's data-driven applications. And they won’t cut it for your end users, your development team, or your business. That's what drove the five companies in this eBook to change their approach to analytics. Learn about their unique problems and how, by embedding analytics into their application, they achieved huge returns and greater value than anticipated.

Your application generates vast quantities of data. Left untouched or without the right analytics solution, your data provides little value to you. But, when combined with analytics, it delivers endless insights and opportunities for your end users. If you’ve been wondering how to invest in analytics, this research-based guide will take you through the 4 steps to finding the right solution for your application that will drive the most value.

For 12 years Dresner Advisory Services has run analysis on the importance of business intelligence, and the different providers of embedded BI solutions. BI Defined. Business intelligence is the technological capability to include BI features and functions as an inherent part of another application. You’ll learn: Analysis and Trends on Business Intelligence Users.

Your application’s users are as unique as their data needs. So, give your users the flexibility to truly explore data. Self-service analytics are vital for how your users interact and engage with your application. As you explore analytics solutions for your application, see why self-service analytics— and how they're delivered— can prove critical to the adoption and stickiness of your application.

The world of data analytics is changing fast as organizations look to gain competitive advantages through the application of timely data. As the analytics landscape has evolved, application teams who need to embed dashboards, reports, and other analytics capabilities in their commercial and corporate applications can choose from dozens of solutions.

As organizations become more data driven, their analytics requirements grow. The expectation to do more with their data becomes a moving target for them and the applications that serve them. To stand up to the challenge, applications must evolve to accommodate their users and ensure their success. But what do users really want? Hanover Research recently conducted a survey that investigates the role of analytics from the perspective of knowledge workers, people who handle or use information as pa

According to the 2020 Dresner Embedded Business Intelligence Market Study, embedded business intelligence is crucial for application success. This report explores the current state of BI and why application teams are increasingly choosing an embedded solution.

Does your analytics solution work with your current tech stack and DevOps practices? If not, any update to the analytics could increase deployment complexity and become difficult to maintain. Learn the 5 elements of a DevOps-friendly embedded analytics solution.

No one designs bad dashboards and reports on purpose. So why do so many applications have terrible analytics experiences? Download this ebook for secrets to creating dashboards and reports your users will love.

Selecting the right solution for your embedded analytics is crucial to the success of your application. But with so many solutions and vendors, how do you make this critical selection? Learn about the different approaches to analytics and the pros and cons for each.

If you built your analytics in house, chances are your basic features are no longer enough for your end users. Is it time to move on to a more robust analytics solution with more advanced capabilities? Follow this free guide for tips on making the build to buy transition.

Many teams, as a logical first step, choose to build their own analytics with the help of UI components. But eventually you’ll find that doing it yourself and at scale has hidden costs. Consider these 10 factors when deciding whether you should build analytics features with UI components.

Assumptions mapping is the process of identifying and testing your riskiest ideas. Watch this webinar with Laura Klein, product manager and author of Build Better Products, to learn how to spot the unconscious assumptions which you’re basing decisions on and guidelines for validating (or invalidating) your ideas. You'll learn: Why every product leader goes into a new project with untested, hidden assumptions.

Embedding analytics in software presents some unique opportunities—and poses unique challenges—to software teams. What are best practices when designing the UI and UX of embedded dashboards, reports, and analytics? What should software teams know about implementing security that works with the rest of their products? What should product managers keep in mind when adding an analytics project to their roadmap?