Analytics Solutions and Vendor Comparison Thoughts for Startups and Small Companies
In working with a number of clients, especially smaller enterprises with little to no in-house analytics expertise, the question often arises about which software to use for visualization and analytics. It is especially important when the limits of Excel or Google Sheets have been reached or there is a need for a more robust data and visualization tool. To involve an analytics vendor is occasionally fine, but often clients can be talked in to overly complex and/or expensive software which they will never be able to fully leverage and never see the full value. Often, clients just need a good solution which is workable for a small enterprise, which can evolve in both scale and complexity.
The below table is something I compiled in my research and to help to communicate with clients the analytics vendors that would meet their needs and a logical solution progression they can follow as they grow in their analytical maturity. Though I have worked in the analytics and business intelligence industry for over 12 years, I do not claim to be an expert in all vendors. The below was compiled based on good faith research and I did my best to be accurate, though my assessment may not be 100% perfect. For the most part, I used many vendors from the 2017 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms accessible here, though I did not include all initially. I will add more as time allows, especially around open source options that are available.
Analytics Vendor Matrix Vendor, Licensing, Cost, Development, Deployment, External Sharing, Visualizations, Data Store…docs.google.com
I intentionally did not include any sort of ranking, leaving an organization free to decide for themselves which solution would work best. The table is designed so that one can focus where there is need, whether that be sharing or development complexity or a built-in data store.
In my advising of clients one of the overriding principles I try to convey is that just because a vendor is highly rated according to the Magic Quadrant, the large vendors (Microsoft, Oracle, SAP) are often overkill for smaller organizations, especially startups.
The typical solution path I recommend is the following:
When just starting out, clients would be well-suited to stick with something smaller and free (or less expensive), such as Google Data Studio. A smaller vendor will meet most needs, and will be at a price point that is consumable.
As analytics needs grow, I would recommend you look to a bit more robust of a vendor such as Amazon QuickSight or GoodData or similar. These come with a bit more broad deployment options, including their own data stores, and more robust systems for sharing and integration.
In the longer-term, as analytics needs and capabilities mature, clients will want to look to a more enterprise-level vendor, such as Saleforce’s Einstein Analytics, Microsoft, or similar.