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There's a saying that rings particularly true when applied to the world of data analytics, "A chain is only as strong as its weakest link." As businesses dive into data analytics, they must choose a solution with an analytics engine (i.e. the backend) that's as strong as its presentation of results and insights. To make the best selection for your business, you must arm yourself with some basic analytics engine knowledge that not every vendor is willing to share with potential customers.

But how does the average business know exactly what to look for and be wary of, as well as which questions to ask when deciding among analytics products?

Understanding the Backend

When we talk about analytics engines, what we're referring to the backend of data analytics solution. The engine is the component where algorithms run, and where data is crunched, including preprocessing, cleansing, and scrubbing.

The outcome of the engine's processing is results, or insights, which must be organized and made sense of, then ultimately shown to a business's stakeholders or users. At this point in the process, when it is being determined exactly how the results will be shared, analytics becomes a frontend issue.


Why Due diligence is Critical

When businesses deal with an analytics vendor of any size (from startup to sizeable), they should require a “proof of concept” (POC) or a pilot from the vendor. If the vendor refuses to offer a POC / pilot, this should be seen as a major red flag. Many vendors insist on tying customers into a long contract. If you haven't done a pilot, and down the road you don't like the results of your analytics' backend, be warned: you will be stuck in a bad relationship.

When searching for the best analytics solution, you must not fall victim to common pitfalls of many vendors' backend solutions. But to avoid doing so, first you must also learn how to recognize the backend's flaws.

The Good and the Bad of Analytics Engines and APIs

Preparation is the key to success, right? If you're an informed buyer, you're less likely to make a bad decision regarding your analytics engine selection.

Let's first break down the better-known choices businesses face when choosing a vendor:

1. Businesses can license an analytics engine or an analytics API directly from a provider
2. Businesses can use an analytics vendor that is simply placing a wrapper over an engine or analytic API they have licensed from another vendor
3. Businesses can work with a vendor who owns its own engine:
   1. But does not offer bundled services to perform the analytics work
   2. And does offer bundled services to perform the analytics work

What does your business need to know about these scenarios?

The first question you should ask any vendor is, "Have you developed your own analytics engine or are you licensing it from a third-party?"

What many vendors fail to disclose that they don't actually own their analytics engine, but they are licensing the engine or analytics API from a different vendor. This can be a huge problem when the analytics results are not meeting your expectations, because your provider cannot make any changes since they don't own the engine.

With an API service, data is sent to the API provider; data is processed, and the results are returned. An API's advantage is that it is relatively easy to implement; it is also typically quite fast. The negative – and it's a big one – is that if you don't like the results of your analysis, with an API, there is not much you can about it.

The shortfalls must be handled manually with the creation of custom wrappers and vendors must reach out to the API service they're leasing from to request necessary changes. (Spoiler alert: often, an API provider maybe unwilling to make the changes, and when they do, it may not be in a timely manner).

Plus, because multiple analytics vendors license the same API, there is a lack of competitive advantage. In short, a plethora of vendors are essentially offering the same product, with different packaging. Why do some vendors take this route? Simply put, building an analytics engine takes a lot of manpower and a remarkable amount of time.

But even licensing directly from an API provider or using a vendor that built and owns its engine comes with a set of deficiencies. In both cases the customers must still roll up their sleeves and do the tricky data analysis work themselves, hiring a team of data scientists to run the project.

Still, a solution – though lesser known that the previous three – now exists.

The Answer? Solution as a Service

There is a fourth scenario to add to the mix; one that puts a newer, improved spin on analytics: Solution as a Service.

Through a single vendor, Solution as a Service marries some of the industry's best data scientists with a powerful data analytics engine that is owned, built, and manipulated by the vendor. The combination of software and people is a truly powerful, synergistic solution.

Solution as a Service creates a seamless answer for businesses. If issues with or questions about the engine's results arise, they can be directly and immediately addressed by the Solution as a Service software development team and data scientists. There is never a disconnect between the customer and the software provider, eliminating the time-consuming and costly struggles businesses face when dealing with API integrators and engines.

In the case of a Solution as a Service provider like PolyVista, the engine is owned and built by the PolyVista development team. Plus, PolyVista offers a pilot program that allows new customers to see the power behind their product and team.

This confidence in their technology and team also means that PolyVista is willing to work on month-to-month contracts with clients. One fixed, monthly price includes both software and professional services and will contain no additional, hidden fees or costs.

You'd want to try most things before you buy them, right? Data analysis should be no different, and Solution as a Service can help.

Summary

When choosing an analytics engine, businesses must ask informed questions and request a “proof of concept” or a pilot to guarantee a vendor's backend is as effective as the frontend. Few analytics vendors admit that they have licensed their backend analytics engine from a third-party. A licensed engine creates a disconnect, but troubles also arise with vendors who own their engine, but do not offer services to do the analytics work. The solution lies with Solution as a Service, which marries a powerful analytics engine with intuitive frontend and data scientists through a single vendor.