And not only do end users want impressive outcomes, they want to take ownership over the insights they’ve uncovered without needing to ask for help. In 2021, end users have come to expect some sort of reporting and data analysis functionality in their applications. Self-service analytics tools empower your end users.And with increased visibility into the company’s data and a shorter time spent in search of information, better business decisions can be made. With a self-service analytics tool, users are able to drive improvements. In a survey of 500 applications teams, nearly 50 percent reported that with embedded self-service analytics they were able to reduce the number of reporting requests from users-and 67 percent saw an increase in the time spent in their applications. In short, they retrieve information and generate insights faster. Users of a self-service tool no longer have to rely on IT for insights and gain greater access and visibility to the data they need. With self-service analytics tools, many users see an increased visibility into business data. It’s your self-service analytics tool, which assures stronger user adoption and satisfaction.īusiness users know the queries they want to make, so it makes sense to put access to self-service analytics into their core business application’s workflow. End users will never know they are looking at third-party software. This delivers in-context analytics within the business workflow. With seamless integration of an embedded BI solution, end users don’t have to learn a new interface. While traditional Business Intelligence platforms can help organizations gain some into their data, embedded analytics platforms can deliver a more valuable and richer analytics experience by keeping the user in the workflow.Įmbedded self-service analytics tools blend into your application’s interface to match its look, feel, and navigation. Embedded self-service analytics tools put data and decisions in context.With a self-service analytics tool, any user can create rich reports and dashboards with minimal training. But rather than spending time and resources hiring additional help or training your staff, deploying an analytics tool that is truly self-service empowers even the least-technical employee. There’s a belief within some organizations that data can’t be truly understood without a data scientist. How? By making everyone a data scientist. As more and more businesses look to leverage their ever-increasing data into reports and dashboards, self-service analytics tools look to solve this issue. In fact, there’s been a much-talked-about data scientist shortage going on for years. There are two truths about data scientists: they’re in high demand and they’re expensive. Gain business insights without a data scientist.Here are 7 critical reasons to use self-service analytics tools in 2021. By delivering a self-service analytics tool as part of your application, users can examine their data from many angles using many data sources. They start asking questions that only arose when the data exploration began. They can freely explore the data to unearth hidden insights. Users gain a sense of ownership in the data, the analytics solution, and the insight they gain through their analysis. Self-service analytics is a Business Intelligence platform that enables business users with limited or no IT background to perform queries, create reports, design data visualizations, and more without a deep understanding of the underlying data model.įor modern businesses, this helps build a culture of data-driven decision making. Self-service analytics tools remove the burden of report creation from your IT department, empowering end-users to create the reports they need at the time they need them. For larger organizations, report requests can take weeks to fulfill and, by that time, the data used in the report is likely irrelevant. But without access to a robust data analysis tool, many end-users must request reports from IT. Gone are the days of “hunches” and “gut-decisions.” In business, the best decisions are the ones backed by data. 7 Critical Reasons to Use Self-Service Analytics.