What is analytics as a service?

Every company wants to access the power of big data, but the costs of building and maintaining in house systems and solutions make it impractical and inefficient for most enterprises. Many businesses can’t justify the costs of in-house development and large data analysis teams, even when the data insight that analysis could drive could make all the difference.

That’s where analytics-as-a-service comes in. Using analytics-as-a-service, companies that can’t justify the expense of funding an in-house data team can access powerful data analysis tools. They can use cloud-based BI tools to analyze big data and drive insight, even without data specialists or expensive server space.

Analytics-as-a-service tools like Domo are designed to be as user-friendly as possible. With user-friendly analytics tools, it’s much easier for the average person to analyze data. Even those with little to no technical experience can, with a little coaching, learn how to run reports, build dashboards, and connect to data sources. This way, everyone in an organization can use data to make timely and accurate business decisions.

With these powerful tools, businesses can also perform more complex analytics, using things like pre-built machine learning applications and artificial intelligence to drive deeper insight from their data. If you do have data science experts in-house, these platforms often offer full-code solutions in common scripting languages like Python, allowing them to build their own data-science models within their BI tool.

Analytics-as-a-service tools differ from regular cloud-based BI solutions in the level of analysis they offer their customers. Some BI tools are very limited in what a user can do; these tools don’t allow users to do much more than create basic visualizations, i.e. chart and graph building. Analytics-as-a-service solutions like Domo allow for far more freedom and functionality in what users can do with the platform. Whether you need to establish new connections to your data, transform existing datasets, or build custom content and applications, choosing a flexible analytics-as-a-service platform allows you to scale beyond your initial use case.

Analytics-as-a-service tools are a valuable option for startups, small businesses, as well as enterprises looking to democratize their data to drive insight throughout the organization.