As it stands today, the domain of Embedded Analytics has moved away from the “build vs. buy” debate. Organizations generally find more sense in “buy,” now . So the central question has shifted to “what should I look for in an analytics solution provider?”
As always, there are multiple approaches to this debate. It starts from a feature-to-feature comparison between prospective analytics platforms, which mostly ends with little differentiation. Yet there are areas, often assigned lesser weightage in the evaluation, which might turn out to be critical differentiators in making the final choice.
In this blog, we have chosen to examine three key areas and we shall elaborate on each of them further.
Time-to-deployment
A fully custom-built embedded solution can be deployed within short time, if the analytics platform is designed from the ground up for embedding. To check if that’s the case, here’s a quick list that helps:
- Availability of pre-built templates, themes and data visualizations to get started in no time
- Minimal or no coding required to do tailor-made white-labeling customizations for a seamless user-experience
- Extensive API documentation to support core functionality customizations
- Scope for usage of pre-existing development tools and sandbox environments
- Capability to manage and rollout any scale of custom changes easily
These factors definitely weigh high in terms of ease of customization, ease of custom development and acceleration towards the last-mile completion that altogether achieves reduction in time-to-deployment.
Also if you are interested, here’s a set of tips to create a cohesive embedded BI experience in minimal time.
Scope for Scalability
For wide-spread organizational adoption, any embedded analytics solution should be able to handle usage at scale and definitely architected for the cloud. Hence the platform hosting the solution must check the following boxes:
- Reliable infrastructure with clustering and load-balancing abilities
- Round-the-clock systems administration support
- Elastic, scalable databases, either owned in-house or by a third-party vendor
- Consistent responsiveness/performance, regardless of the scale of concurrent users or data volume
- Support for multi-tenancy with on-demand scalability of ‘processing’ capabilities
- Support for in-memory databases or caches
- Ease of managing, monitoring and auditing usage
It’s very important to understand the scalability of an analytics solution, to be used in today’s business environment, where usage can skyrocket anytime. Hence utmost care and precision is recommended while delving into this aspect.
Security and Privacy
At the heart of any modern software architecture built today, lies the aspect of security and privacy. Analytics platforms are no exception to that and it’s a vital cog that shouldn’t be missed in this evaluation for a suitable embedded BI solution.
Here’s a suggested check-list to help with the same:
- Support for secure single sign-on(SSO) with multi-factor authentication(MFA)
- Adherence to suitable regulatory compliances like GDPR, SOC Type 2 etc.
- Adherence with industry-accepted standards, notably for cloud security management (Ex: ISO/IEC 27017), personal data in the cloud (ISO/IEC 27018) and privacy information management (ISO/IEC 27001)
- Clearly defined, publicly available policy on security and privacy
The effective enforcement of regulatory compliances and accepted standards, more specifically to the demography and domain of the organization in interest, is a defining factor in choosing the Embedded BI solution provider.
What we have discussed so far isn’t exhaustive. Yet these are some of the fundamental criteria, that we felt, should be highlighted or even reinforced. Consider factoring these aspects into your evaluation process of embedded analytics platforms, if you haven’t already.
Additionally, if you are interested in considering our solution offering (which has benefited our customers in many ways) as a part of your evaluation, you can get started with our embedded analytics platform here.
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