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Embedded analytics seeks to deliver analytical insights to end users, via its integration into another software, for example; a company’s internal web portal (typically, enterprise) or a software company’s product offering (application).
The key to embedding analytics is in creating a seamless experience for the end user whereby the analytics platform forms an inherent part of the application into which it is embedded, rather than two separate tools. In order to not only successfully implement embedded analytics but also to manage the solution in the long run, this guide will show you:
The two essential parts of embedded analytics:
- Self-service: preventing change-request overload
- Embedding, branding and customizing: flexibly and seamlessly
How to manage the embedded analytics solution, including:
- Scaling analytics and data: the most common yet hidden bottleneck
- Change management: the underlying layer of data operations efficiency
- Data integration: quickly and reliably
- Data security: don’t struggle with security and privacy
- Monitoring: analytics over analytics
And how to reap the benefits:
- Developing data products
- Monetizing your application and data
- Pricing: look for a predictable and sustainable formula
Whether you're part of a management, product, solution, or data team, this technical guide is here to help you successfully navigate the complexities of choosing an embedded analytics platform to best suit your needs.
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