I’ve never been a fan of talking about semantic models because most of the workforce probably doesn’t understand what they are, or doesn’t recognize them by name. But the findings in our recent Analytics and Data Benchmark Research have changed my mind. The research shows how important a semantic model can be to the success of data and analytics processes. Organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%) compared with a 33% overall satisfaction rate. Therefore, I owe it to all of you to write about them.
Organizations are constantly trying to streamline and optimize business data to solve complex problems and identify opportunities to increase revenue and accelerate business growth. The data is usually stored in multiple systems with various data governance rules, which makes it complicated to democratize data and analytics within an organization. The most pressing concerns cited by participants in our Analytics and Data Benchmark Research include difficulty integrating with business processes, systems not flexible or adaptable to change and challenges accessing data sources.
Organizations are scaling business intelligence initiatives to gain a competitive advantage and increase revenue as more data is created. Lack of expertise, data governance and slow performance can impact these efforts. Our Analytics and Data Benchmark Research finds some of the most pressing complaints about analytics and BI include difficulty integrating with other business processes and flexibility issues. Kyvos is a BI acceleration platform that enables BI and analytics tools to analyze massive amounts of data. It offers support for online analytical processing-based multidimensional analytics, enabling workers to access large datasets with their analytics tools. It operates with major cloud platforms, including Google Cloud, Amazon Web Services and Microsoft Azure.