Microsoft & .NET.NETKey Attributes for Winning with Embedded Analytics in .NET or Java Apps

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By Dean Yao


With software engineering teams innovating to win markets by solving age-old inefficiencies in every industry from healthcare to finance, many are struggling with time to code reporting and analytics features, regardless of development platform.

Whether your development platform is Java or .NET, your software application or product most likely has requirements for Business Intelligence (BI) or analytics, but your development team is also most likely understaffed when it comes to these skills (see Chart 1). For this reason, embedded analytics from a 3rd party may be the best solution.

What BI and Analytics development skills do your technical team lack the most?
Chart 1*: What BI and Analytics development skills do your technical team lack the most?

Taking this approach can address data insight needs with visualizations that integrate easily and securely without diverting attention away from your core application development. With the right embedded analytics software, it doesn’t matter what technology your application is built upon.

Here are some key attributes of “run anywhere” embedded analytics solutions (see Chart 2).

Which type of analytics solutions would be most effective?
Chart 2*: Which type of analytics solutions would be most effective?

Embedding Analytics with APIs

APIs are the key to platform-independent success when embedding 3rd-party analytics. They provide the interface between your application and the embedded analytics solution. APIs enable the integration of both user-facing reporting features and back-end administrative functions of the analytics platform without using the platform’s user interface. The right embedded analytics solution will provide API libraries in a variety of common programming languages as well as a language-independent Web services API.

Customizable Look and Feel of Embedded Analytics

An embedded analytics solution with a customizable look and feel allows for a unified product experience and stronger branding. JavaScript APIs provide interactive data visualizations that are highly customizable and seamlessly integrate with your application’s user interface.

This ensures that users are not distracted by a different look and feel when they turn to the data analysis part of their core application. For more advanced use cases, you even can tailor the specific controls and features available to your users.

Cloud-ready Analytics Software

Embedded analytics software that can be hosted on infrastructures, from the likes of Amazon and Microsoft, provides greater deployment flexibility and ability to efficiently scale on demand. In addition to providing enhanced computing power while reducing data center and IT costs, cloud-based analytics software delivers a more hassle-free maintenance experience.

Painful and resource-consuming processes, like hardware procurement and operating system patching, disappear. Cloud-ready embedded analytics software also provides packaging options for on-premises or SaaS deployments.

Secure Analytics Software

Embedded analytics software also must integrate with your existing security architecture. The right solution will have customizable security options for user database and user authentication methods and support both Microsoft Active Directory and LDAP directory services. If you provide a commercial SaaS offering, support for multi-tenant access, in which a single instance can be segmented into multiple secure tenants, is a key security requirement.


An embedded analytics solution that provides these key features ensures that you can focus on your core business application to deliver products and services in a competitive marketplace, regardless of your development platform. Long live .NET vs. Java.

About the Author

Dean Yao has over a decade of software marketing and product management experience. Prior to leading Jinfonet Software, Dean was a senior product manager at cloud computing startup Nimbula (acquired by Oracle and VM Ware), where he focused on technical best practices, competitive marketing, and product strategy.


The charts used in this article are from Jinfonet State of Analytics in 2017 Report.

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