The public cloud software-as-a-service (SaaS) market is projected to be worth more than $157 billion in 2020, and for good reason. Businesses are increasingly moving to the cloud and service-based cloud applications are helping companies digitize and optimize all of their critical functions. But as data moves to the cloud, so does the need for new data pipelines and analytic solutions.
Here are some of the SaaS industry’s biggest analytics challenges:
Solve The Key Challenges of Software Providers
SaaS applications are built on data, but the size, diversity and velocity of that data has never been more challenging. Analytics applications not only be able to process all types of data, including semi- and unstructured, but also have the power and performance to analyze all of that data in realtime.
Data is no longer measured in megabytes, it’s measured in terabytes and even petabytes. This level of analysis requires not only a fully cloud-native analytics platform, but also one that uses the latest in microservice architecture to get the job done in seconds and minutes rather than days or weeks.
SaaS solutions aren’t built in a vacuum. They must increasingly connect to disparate data, customers and third-party systems. This requires analytics solutions that have robust APIs to effortlessly move data, analytics and insights where they need to go in realtime.
Users don’t have time to wade through mountains of information that isn’t relevant to them. They demand their software experiences are tailored to their own needs. But personalization places a huge burden on traditional analytics tools that weren’t built in the cloud and don’t offer a single data repository for personalized analytics.
Vertical SaaS Raises New Challenges
While most SaaS solutions are horizontally oriented, carving out their niche across many different industries, vertical SaaS solutions are also gaining in popularity and come with their own analytics challenges.
Vertical solutions offer more value to the companies that use them and in turn, those solutions must be designed to meet higher industry standards.
The requirements for operations, performance and compliance, coupled with the need for pre-built metrics, KPIs and analytics of all types, demand an all-in-one analytics solution that can manage entire data pipelines, from data collection to transformation, analysis and automation.
Qrvey’s All-in-One Analytics Solution
Qrvey is an all-in-one, cloud-native analytics solution that simplifies analytics on AWS to give the SaaS industry all of the tools they need to meet their biggest analytics challenges.
Built For The Modern Age
Qrvey was built for the next generation of analytics applications and fits perfectly with the needs of next-generation SaaS products. Qrvey embraces analytics, automation, big data, and machine learning to provide the speed, automation and personalization the SaaS industry needs with the data security they demand.
Qrvey is a 100% cloud-native platform that assembles over 26 AWS microservices to provide all-in-one analytics solutions spanning data collection, transformation, visualization, automation and ultimately, data-driven actions and decision making. Unlike traditional analytics solutions, Qrvey adopts an “All Data Accepted” philosophy and works even with semi- and unstructured data no matter where it lives.
Automation runs throughout the platform, allowing for all-new data pipelines to be created.
SaaS applications are built on big data. That’s why Qrvey was built to perform in even the most demanding of environments. Even hundreds of millions of rows can now be analyzed in seconds and with machine learning to aid with data augmentation, analysis, predictions and more.
Finally, Qrvey provides the utmost in data security and privacy by deploying directly into your existing AWS account, instantly complying with all existing security policies.
As the SaaS industry continues to usher in the age of digital transformation, the need for powerful, flexible and scalable analytics solutions only intensifies.
Only Qrvey offers an all-in-one, cloud-native analytics platform that can deliver self-service, embedded and enterprise-grade analytics applications to meet these new challenges.