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How embedded analytics improves your application and saves money

By Charles Caldwell, vice president of product management at Logi Analytics

Data is too valuable to not get the most out of analytics, particularly now as we see how the pandemic is reshaping how we do business. Rising materials costs, supply chain stressors, worker shortages and workplace changes are putting a premium on efficiency.

Yet a 2021 study conducted by Forrester Consulting on behalf of Dell Technologies notes what it calls a data paradox: Businesses are gathering data but are struggling with data overload and the inability to extract insights from the data they collect.

Your software teams could build an analytics solution with user interface components or connect to data discovery tools or just rely on traditional business intelligence solutions. But those standalone options have critical limitations when integrated into your application. UI components are single-use-case tools with limited user capabilities and an inability to scale. Traditional BI solutions result in complicated integrations with poor user experiences because, among other things, they lack customizability and rely on static, often dated reports, and users must leave the application to access data and perform analysis in other applications.

Each of those solutions fails to measure up to what an effective embedded analytics solution can provide. In a practical sense, an effective analytics layer within the application provides users with clear visuals and dashboards, streamlined reporting, self-service capabilities and alerts when and where they need them. More broadly, the advantages of an embedded analytics solution are an improved time to market, enhanced functionality and cost savings.

Embedded analytics expedites work

Organizations using an embedded analytics solution can standardize workflows and develop and maintain products in less time, according to an examination of solution options by Enterprise Strategy Group.

The most obvious benefit is that end users can view the data they need right in their existing application's workflow without having to launch, access and toggle back and forth between other applications.

Further streamlining the workflow is the ability to pull data in from an existing technology stack. An effective embedded analytics solution can access data from virtually any source - whether cloud storage, data warehouses, relational databases or proprietary sources - to create a single dashboard.

The solution's out-of-the-box functionality, including rapid-development tools and sample applications, encourages collaboration, maintains consistency and hastens development time.

With no need to set up and equip a team to develop analytics and code from scratch, the ESG report said, developers instead can focus on other aspects of the product and get it to market much quicker.

Embedded analytics enhances functionality

An embedded analytics solution provides developers greater flexibility in product design, increased capabilities, and greater customization, which leads to an improved end-user experience and benefits.

Developers can customize analytics based on what is best for their application instead of making design choices because they work with existing tools. Standardized workflows, the ESG report said, enable users to design, deploy and support their applications and analytics more efficiently.

For end-users, customizable self-service allows them to create dashboards, discover insights, share information and collaborate. They can initiate actions in dashboards as soon as they view information rather than move to another application. Because customized analytics integrates seamlessly with an application, they enhance user interface consistency and preserve the look and feel of the brand.

Embedded analytics allows end-users to easily create the dashboards that will be most helpful to them. It's as simple as that.

Embedded analytics saves money

We know the up-front costs associated with other analytics solutions: hardware, staff and licensing. Licensing in particular weighs on the bottom line because it's focused on the number of users and not whether it meets a business's needs. However, an embedded analytics solution allows for flexible, scaling licensing options based on needs, not users.

What's more, the self-service capabilities reduce the need for support from IT teams or data experts. Users can solve problems themselves or provide details to help support teams resolve issues more quickly. Users can configure dashboards based on their own skills rather than being thrust into an environment they don't understand. Teams don't have to rely on data experts to run reports; they can run reports themselves that best suit their needs. In the end, users get the analysis they need better to understand the ROI on their business's products and services.

The Forrester study noted how businesses need the right technology, processes and culture to overcome the data paradox. An effective embedded analytics solution is a solid first step in that direction. Embedded analytics is easier to use and understand than other alternatives. It hastens time to market for your applications, enhances functionality and saves time.  

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ABOUT THE AUTHOR

Charles Caldwell 

Charles Caldwell is the vice president of product management at Logi Analytics, where he developed the Logi Solutions engineering team from scratch to support OEM, SMB, enterprise and channel partner sales in North America and Europe.

Published Tuesday, July 13, 2021 7:33 AM by David Marshall
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