The process for selecting data analytics and BI software can be a complex, even painstaking process. There are a number of considerations that buyers should take into account during vendor selection and implementation of a new solution. Some basic things to consider include your budget and the price of a given data analytics tool, but there’s also the question of which business problems you are trying to solve.
Buyers are advised to consider who their data analytics and BI users are. Do you require a democratized tool that allows users of any ilk to run analysis on the data that matters to them, or do your data scientists require advanced capabilities that enable them to predict future trends? Your current technology environment will ultimately dictate how you begin your search, especially if you are planning to upgrade from a basic tool. For example, what kinds of data are you looking to work with, and what are your KPIs?
Product capabilities and services offered are also key attributes that require some thought. There are many features that come standard in a large swath of available offerings, but there are some, like AI-driven and augmented analytics, that only those looking to run complex analysis will require. Common support packages include assistance for non-technical users who require self-service, but there’s also sometimes deployment assistance, dedicated use case representatives, and user training modules that can be a great help.
With all this in mind, there are steps you can take to select the provider and partner that will help you solve for your specific use case. Whether you are a CIO, the head of your IT department, or a business analyst or data scientist, Solutions Review recommends the following best practices for selecting data analytics and BI software.
Use all the resources at your disposal
There are lots of worthwhile resources to consider during the research phase if your buying process. Many of the research and analyst houses, like Gartner and Forrester, do an excellent job at covering the marketplace and provide deep research into the overall trends impacting the space. However, not everyone is a technologist, and not every situation warrants the kind of granular analysis that those outlets offer.
It’s best to start by taking an inventory of your unique situation (using some of the criteria we outlined above) to ensure the solution you wind up with meets your business needs. Once you’ve framed your data and analytics needs you can begin doing meaningful research about which vendors line up. Try these resources on for size, and don’t forget about our buyer’s guide and comparison matrix.
Make the vendor prove it
It’s easy to get carried away when browsing vendor websites, and the providers can do an excellent job of selling you on capabilities that, while they are nice to have, don’t really move the needle for your use case or situation. Avoid taking product demos with providers that only want to show you examples of their preferred product capabilities, and make the representative show you only the analytic features relevant to you.
You can also ask prospective vendors to provide references than can attest to the tool’s competency in a similar situation. In-vertical references are best, so we recommend asking for first-hand accounts from similar-size organizations that do business in related industries and analyze similar data types. It’s not about selecting the best overall tool, it’s about selecting the best tool for your (very) specific set of circumstances.
Take scalability into account
Taking scalability into account can sometimes come at odds with selecting the best tool for your situation right now. However, this is an important (and often overlooked) aspect of selecting data analytics and BI software. Of course you’ll want a solution that can handle your current load, but what if the tool can handle only your current load and nothing more? That’s when it may be time to look at other alternatives, or perhaps consider an infinitely scalable cloud BI option.
Your needs may not change much over time, but the flexibility that comes with a more scalable analytics tool can be invaluable should demands arise. Things to consider when we talk about scalability include data volumes, depth of analysis, the number of users you are trying to support, and if you are interested in a cloud-centric product, licenses and costs associated with them.
Consider the total cost of ownership
Data analytics and BI software is just like anything else, and will require some post-buy to get fully up-and-running. Some cost-of-ownership realities to keep in mind include support and services (are they included indefinitely, or for a specific amount of time?), training and certification (do your users need a crash course?), and data storage and maintenance (are there managed services?). There’s also the scalability question again; if your users require more support, functionality, etc, then the price will increase.
Buyers are advised to compile a budgeting plan along with their vendor of choice. Get a pricing outline (in writing) that highlights any and all costs associated with the purchase of their software to make sure there are no surprises later. Vendor lock-in is a real thing, and oftentimes organizations wind up regretting their purchase because they weren’t thorough enough up front.
Don’t overlook “immature” solution providers
We mean immature in a good way. Startups and lesser known providers can sometimes offer more in terms of complexity and value than the larger vendors in the space. Much of this hedges on the size of your organization as well, as the larger your company, the more likely you are to select a data analytics or BI tool that scales to your needs immediately. For small or mid-sized organizations, pay attention to those with a smaller footprint as they are likely to offer perks that the bigger companies aren’t.
We often highlight emerging providers in our Vendors to Watch series, which we release on an annual basis. We also recommend checking out other resources, as the smaller providers make up in feature capabilities and add-ons what they lack in verified user reviews or testimonials. Sometimes you can hit a home run and find an analytics tool that fits perfectly into your environment and provides just what you need.
Latest posts by Timothy King (see all)
- Examining Top Data Analytics Firms in the 2019 Forbes AI 50 - September 18, 2019
- DataRobot Nabs Series E Funding, Unveils New MLOps Solution - September 17, 2019
- Gartner Names 3 Cool Vendors in Privacy Preservation in Analytics for 2019 - September 13, 2019