So, you’ve decided to take the plunge and boost your product or service with <a href="https://www.sisense.com/product/embedded-analytics/">embedded analytics</a>. It’s a wise decision, as the substantial benefits have become increasingly self-evident, such as faster decision-making, increased ROI, accelerated development, reduced time-to-market, lower TCO, lower burden on IT, and more empowered users, whatever their background and level of technical know-how.
But what might not be so self-evident is which supplier to choose. There’s a bewildering array of vendors claiming to offer you the most state-of-the-art analytics platform. So what sets one vendor apart from the rest? Which factors should you consider and what characteristics should you identify to find the right OEM supplier?
These considerations fall roughly into three categories: technical, usability, and experience. Let’s look at these in more detail.
<a class="fancybox image" href="https://www.sisense.com/whitepapers/compare-top-embedded-bi-vendors-using-g2-crowd/"><img loading="lazy" decoding="async" class="img-polaroid aligncenter" src="https://cdn.sisense.com/wp-content/uploads/G2Crowd_770x250-770x250.jpg" alt="" width="770" height="250" /></a>
<h2>Technical</h2>
First, and most importantly, there’s a load of “must-haves” that you should check to ensure that your choice of provider has the technical capabilities to deliver what you need. And perhaps the best way to check them is to pose a series of questions to any potential supplier, as outlined below:
Scalability, Extensibility, Flexibility
Almost inevitably, software requirements evolve over time. Projects change and grow, and as data becomes available from new sources, it should be integrated and analyzed to keep your BI as fresh as possible. Make sure your BI vendor can answer the following questions:
<ul>
<li>Is your platform scalable, extensible, and therefore future-proof?</li>
<li>How much data, how many users, and how many concurrent queries can your platform handle?</li>
<li>Is your architecture open, so that it’s possible to extend capabilities without waiting for future releases or updates?</li>
<li>Does your technology allow me to employ and benefit from a variety of standards, such as JavaScript APIs, SSO, and REST APIs?</li>
</ul>
Customization and Open APIs
You may want to <a href="https://www.sisense.com/glossary/white-label-analytics/">white-label analytics</a> for customer-facing use by applying your own brand’s look and feel. You may want to tailor functions accordingly with customized content or dashboards, and you may even want to create a <a href="https://www.sisense.com/blog/its-an-apps-world-mobile-analytics-for-all/">white-label mobile app</a>. Similarly, you may want to develop other apps or enhance existing apps as quickly and simply as possible. So you’ll need to ask the following from your preferred vendor:
<ul>
<li>Can your platform be customized to my requirements so I have an embedded BI solution that works for my specific business and architecture needs?</li>
<li>Can your platform embed dashboards, individual widgets, and filters into applications, and enable meto create new widgets, add new menu items, more functionality, and customize the look and feel in line with my branding?</li>
<li>Will your platform enable me to embed analytics into my users’ day-to-day workflow with IoT devices like Amazon Echo, chatbots, and smart devices, to go beyond traditional modes of consumption?</li>
<li>Does the platform have APIs that can enhance or disable existing functionality?</li>
<li>Can these open APIs give access to external developers for quick fixes and enhancements?</li>
<li>Can I create my own visualizations or connect to third-party charts to maximize the visualization possibilities for my analytics?</li>
<li>Which add-ons, libraries, and certified extensions can I download to help users configure new visualizations?</li>
</ul>
Integration and Management
Importantly, you need to be confident that whatever embedded analytics platform you choose will work effectively with your current IT infrastructure, and will seamlessly blend into your existing applications quickly and efficiently. Ideally, it should be easy to install, integrate, and implement, and provide you with the control to assign and administer different levels of access, in the interests of data security. So, you need to ask:
<ul>
<li>Is your platform compatible with my existing systems, configuration, security, and access frameworks?</li>
<li>Can your platform separate and manage access to analytics by roles, groups, and security levels, and ensure that access to the software is controlled?</li>
<li>Can your platform’s security settings be extended to work with custom security hierarchies to enable flexibility of access?</li>
</ul>
Data Access, Connection, Mashup
To get the best results from analytics and to formulate the most on-point business intelligence, it’s essential that you have access to as many data sources and databases as possible, both now and in the future. So, confirm that you can answer these questions with a resounding “Yes!”
<ul>
<li>Does your analytics and BI platform have robust connectors to all forms of data, both live and cached, in the cloud and on-premise?</li>
<li>Can your platform perform ETL quickly and seamlessly between relational database management systems, data warehouses, and third-party applications?</li>
<li>Can your platform retrieve raw sources of data and migrate, integrate, cleanse, mashup, and manage it all to prepare it for analysis?</li>
<li>Does your platform allow me to implement newer data technologies and will it be fully integrated with Big Data sources like NoSQL databases, such as <a href="https://www.sisense.com/blog/postgres-vs-mongodb-for-storing-json-data/">MongoDB</a>?</li>
</ul>
Any platform that can’t positively answer all these questions may leave you needing to buy, install, and integrate further software and hardware to extend the capabilities of your analytics and BI (at considerable extra cost), thereby undermining much of the good work you may have done to implement a solution in the first place.
<h2>Usability</h2>
The second big consideration is usability, both in terms of set-up and ongoing use. This is an issue that affects both the builders of any analytics and BI platform, as well as the end-users. If the need for IT resources and infrastructure can be limited in the implementation phase and reduced in the maintenance phase, then a platform becomes simpler and cheaper to install, customize, and use. Furthermore, it makes a platform faster and more flexible for ad-hoc analysis and even easier for non-technical end-users. Ease of use encourages more individuals to use an analytics and BI platform. When more people throughout an organization develop the habit of using it, it drives more value. The key questions to ask your OEM supplier here are:
<ul>
<li>Do you provide a Single-Stack platform, or do you require supporting infrastructure and resources to run an update?</li>
<li>Is the platform dependent on IT resources to support large, complex data?</li>
<li>Is any extensive data preparation or modeling required?</li>
<li>Can it be used as a self-service platform for non-technical users, or does it require developer / IT expertise to generate results?</li>
</ul>
<h2>Experience</h2>
Finally, it’s important that your OEM supplier really understands what you need, what you want, and what you’re trying to achieve at your organization. You should be sure that your chosen provider knows the challenges you face and how to meet them, and has a good track record of service, so you can be confident you’ll have a positive customer experience. After all, implementing embedded analytics is a big decision with significant spend, which means you need to be certain that you’ll get the help you need to maximize your ROI and get the most value out of your investment. There’s an intangible element of “chemistry” required in the relationship that you have with your supplier, but there are still some things you can do to help select the right partner.
Familiarity with sector, experience with scale, and customer experience
Before you send an RFP to potential providers and put your project out to pitch, do some preliminary research. Take a look at providers’ websites and industry news, to find out whether your preferred potential providers have worked with your industry sector, whether they’ve worked at the scale you require, and whether working with them is usually considered to be a positive experience. This will give you some idea about how well they’ll understand your technical and business needs and how responsive they’ll be to them.
Check out use cases and customer stories published by vendors. Take a look at objective third party analyses of the major players in the marketplace, such as <a href="https://www.sisense.com/gartner-magic-quadrant-business-intelligence/">Gartner’s Magic Quadrant for Analytics and Business Intelligence</a>. And learn what other customers say about the providers you’re considering. There are some great user reviews out there, like the <a href="https://www.g2.com/categories/embedded-business-intelligence#highest_rated" target="_blank" rel="noopener noreferrer">G2 Crowd user satisfaction ratings</a> of the best embedded business intelligence software, and <a href="https://www.gartner.com/reviews/market/analytics-business-intelligence-platforms/vendor/sisense/product/sisense" target="_blank" rel="noopener noreferrer">Gartner’s Peer Insights / Customer Choice</a> for Analytics and Business Intelligence Platforms. We’ve even got our own <a href="https://www.sisense.com/blog/making-sense-of-bi-software-reviews/">guide on making sense of software reviews</a>, to help you make a choice that will be best for you and your organization.
<h2>In summary&#8230;</h2>
Use these questions, criteria, and considerations as a checklist to help you discover which supplier is best placed to provide you with embedded analytics. It’s a critical decision that, if taken correctly, will lead to some wonderful benefits for your business, your users, and your customers.
<a class="fancybox image" href="https://www.sisense.com/whitepapers/compare-top-embedded-bi-vendors-using-g2-crowd/"><img loading="lazy" decoding="async" class="img-polaroid aligncenter" src="https://cdn.sisense.com/wp-content/uploads/G2Crowd_770x250-770x250.jpg" alt="" width="770" height="250" /></a>

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