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Embedded Analytics

5 Embedded Capabilities to Make Your Application Shine

By David Abraham
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Application teams across all sectors are embedding dashboards and reports to engage their end users, increase customer satisfaction, and drive revenue. But leading applications understand it’s not enough to embed non-customized dashboards from an off-the-shelf vendor—they need cutting-edge capabilities that will set them apart from the competition. The most successful teams take the time to fully integrate unique analytics into their applications.

Embedded analytics should not only deliver data visualizations, but go deeper and integrate the data and analytics into the fabric of the application.

Make your application shine with these five embedded analytics capabilities:

#1. Full App Integration

Full app integration means adding the analytics where it makes sense in the workflow and user interface. This usually ends up requiring a few technical features, which you can either buy from an analytics vendor or build from scratch. The user shouldn’t have to learn how to navigate or use your analytical tool. Full app integration is about designing interactivity—charts, actions, database write-back—into the workflow in a way that makes sense to the user.

#2. End-User Data Exploration

When it comes to end-user data exploration, we’re talking about a user that needs a little more liberty so they can answer questions using the data presented to them. For instance, they might be asking themselves who is selling the most, or whose sales have declined in the last six months. To allow them to independently find those answers, you need to offer analytics and dashboards that give your end users the capability to do their own calculations, their own drilling, and their own navigation of the data.

#3. Web-Based Content Creation

In embedded end-user content creation, you’re still using the browser to interact with dashboards but giving the end user the ability to create something from scratch. Users are able to select a dataset and efficiently build new visualizations, dashboards, and layouts to do their own analysis. They can then publish those apps for other people to enjoy when they visit an application. This content becomes part of their library to consume.

#4. Operational Reporting

There are two different types of operational reports: pixel-perfect reports and banded reports.

In pixel-perfect operational reports, a precise layout is the most important feature. The reports are called “pixel perfect” because you can control parameters down to the pixel level on the screen. Once the layout is created, you can generate these reports and add data to them. Year-end tax forms are a good example of pixel-perfect reports. In these reports, the labels and layout come first, and then very detailed data is added—it’s all about having a precise layout.

With banded operational reports, the layout is still important but is largely driven by your data. You can organize operational reports into sections, called “bands.” Those bands can repeat within a page or across pages to present aggregated and detailed data. Bands can also be nested, which makes information easy to understand by placing aggregated or group data summaries at the appropriate band level. Examples of banded reports are year-end reports and invoices.

#5. Predictive Insights

More and more, users want to be able to understand what is probably going to happen in the future just as much as they want to understand what happened in the past (and why).

For example, if you’re looking at a sales dashboard for receivables, you might want to understand which customers are most likely to default. Predictive analytics makes this a lot easier to do. That same workflow and interactivity we talked about with full-app integration allows you to filter down to look only at these customers. Once you build and deploy the predictive model, we can make the application actionable and allow your end users to do something to prevent that customer from defaulting.

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Originally published February 13, 2020

About the Author

David Abraham is a Solutions Engineer at Logi Analytics. Before joining Logi, David was a cybersecurity analyst.

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