3 Signs of Next Generation Analytics
Product life cycles are an interesting thing to examine. There are points at which you begin to see a shift toward the next generation. For software, that is often in response to changes in technology. What is fascinating to see is that often, there can be big changes “under the hood” even though the user experience remains the same.
There are three signals we’re seeing today that are pointing toward a major shift in how business intelligence (BI) companies need to respond to the needs of SaaS providers who use business intelligence in their products.
We only have to look as far as the automobile to see a good example of a product that is beginning to transition into its next generation. The design of a fossil-fueled car has stayed roughly the same for many years. Most recently, cars have become electrified, but it still doesn’t change people’s driving experience. Yes, it’s cleaner and better for the environment, but generally, they still work the same. It still has a steering wheel, a gas pedal, and brakes. It doesn’t really change the way people drive.
Now, consider some of the current business intelligence software players in the market like Qlik, Sisense, Looker, Tableau and others. Most have been around for 20 or more years already. Their software connects to a typical relational database like Microsoft and Oracle using SQL queries. They allow you to create reports and charts. These software products pretty much provide the same functionality that they did when they hit the market several years ago.
For both cars and business intelligence software, there are significant changes happening that are fundamentally changing the way the next generation of BI products need to be built. Specifically, for SaaS providers that use BI in their products, these changes are the:
1) Shift toward serverless technology
By 2025, according to Gartner, half of enterprises will deploy serverless technology in their organization. Serverless computing is a true and exact demand and supply platform for computing power where pricing is based on the actual amount of computing power used instead of paying for a set amount. It offers instant scalability for applications and runs microservices that speed up software development. This provides the flexibility SaaS providers need to stay current in the market. This is essentially the new way to build software.
2) Demand for full data lifecycle automation
SaaS providers wanting to provide BI capabilities have to consider not only the reporting and chart functionality, but also the data prep and post-analysis actions their end users need. That means the SaaS provider has to work with three (or more) different vendors or build the functionality themselves. Either way is less than ideal. Customers of SaaS providers are demanding an all-in-one experience. Automation improves user engagement and user adoption by removing the data management burden from the end users.
3) Requirement for both self-service AND embedded capabilities
In the recent past, SaaS providers had to make a choice between providing self-service capabilities to their end users or being able to embed third-party BI capabilities. SaaS providers could buy self-service software with limited embedded capabilities or buy embedded software with limited self-service capabilities. Today, SaaS providers realize they must have both. The next generation in BI provides that.
These shifts are more than just feature changes. Moving from server-based to serverless technology is not a quick shift and can’t be easily accomplished in the traditional software development world considering how risky product reinvention can be. Nor can automating the full data lifecycle, from data prep through workflows that take action. Being able to offer SaaS providers both self-service AND embedded capabilities was not easily possible until now.
Getting back to the example of the automobile, the underlying platform of the electric car has changed greatly from its fossil-fueled version. Electric engines are more than just a feature change. It’s a complete architectural change. Automobile manufacturers cannot just swap out a fossil-fuel engine for an electric one. They must start from scratch, with a whole new design and assembly line. To unscore that point, a new car takes anywhere from 4–7 years to develop.
In the same way, software companies cannot just decide to use today’s next-generation technologies. While they can fairly easily add more features, these next-generation technologies and capabilities require a brand new architecture. For the most part, today’s BI companies will need to start from scratch. Afterall, architecture is not a feature, which is exactly the mindset we’ve adopted at Qrvey. Those who are already taking advantage of these next-generation technologies and capabilities are far ahead of the curve, and whether these current BI players will be able to transition remains to be seen.
