The goal of Business Analytics and Intelligence software is to help businesses access and analyze data and communicate analytics and metrics. But the reality is that the majority of software on the market today only provides a subset of functionality, and those that do provide a more comprehensive solution tend to lack the features that would make them easy to use.
With a crowded marketplace, a potentially complex evaluation process and some fundamental technology decisions you need to make before selecting a vendor, ensuring your decision will scale and grow with your organization can seem like an impossible task.
Here are some factors you should consider when beginning the BI evaluation process.
1. Selecting a Software Stack
Your first step in evaluating a BI solution needs to be understanding the alternatives for extracting intelligence from your data. It is important to understand if your needs are for a business analytics solution or dashboard reporting tool. Business Intelligence or Business Analytics as it is sometimes called, refers to a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes.
By contrast dashboard or report projects have a more limited scope and generally address current requirements rather than future ones. Understanding the type and scope of your initiative and the alternatives available in the market will help you make the correct software stack decision for your organization.
2. Selecting Database Technology
Your next step is selecting the technology configuration that suits your current business needs and will scale for future requirements. Are you going to use a data warehouse scale (‘Big Scale’) technology or will data mart scale technology be sufficient? To determine the database technology for your business analytics project, you will need to consider the volume of your data and rate of increase, the number of users now and in the future, number of data sources, need for ETL, complexity of the data and the scale and scope of the project.
For projects with limited scope and utilizing a single data source, a data mart solution is probably your best bet. When your requirements grow to multiple data sources with terabytes of data and your data analytics needs are constantly growing, a data warehouse is the solution that can support that scale.
Learn more about the implications of Selecting the Right Database Technology for Your Business Analytics Project
3. Selecting a Vendor
If you’ve begun looking for a Business Intelligence (BI) solution, you’ve probably noticed that there are quite a few BI vendors out there. Narrowing the overcrowded field of vendors in order to come up with your own BI short list will usually start with a review of the vendors’ websites. Armed with your short list, you can begin contacting vendors to receive proposals.
Exploring vendors’ websites is a great place to start to understand the differences between vendors. Based on what they share on their websites – and what they don’t, you can create a comparison map to quickly figure out which are right for you and which ones probably aren’t.
4. Launching a Successful Proof-Of-Concept
With your understanding about the software stack, technology platform and a very short list of vendors (no more than one or two), you are now ready to launch a Proof-of-Concept (POC).
Knowing how to launch a successful POC will save time and money and will ensure you don’t outgrow your BI solution. The process is anything but trivial. Getting a vendor to agree to a POC on your data is a critical step but not one all vendors will agree to. Pretty dashboards can be impressive but unless you can actually get your hands on the data and customize the dashboards, you should continue you search. Data analytics is a dynamic field and your requirements will continue to develop and evolve with time. Therefore you have to ensure the solution will fit not only your current needs but has the ability to scale for future requirements.
Check our more POC tips: 5 Tips to a Successful Proof-Of-Concept for Business Analytics Solutions