Every day, more companies unlock the potential of artificial intelligence (AI) and machine learning. When AI and machine learning are utilized in embedded analytics, the results are impressive. Much of this can be seen in modern solutions that offer advanced predictive analytics.
Together, predictive analytics and AI can help application teams by streamlining processes, generating personalized recommendations, and creating a more intuitive and efficient user experience. By leveraging these technologies, your team can build stronger customer relationships, increase user satisfaction, and ultimately achieve your goals more effectively.
Predictive analytics refers to using historical data, machine learning, and artificial intelligence to predict what will happen in the future. This historical data is fed into a mathematical model that considers key trends and patterns in the data. The model is then applied to current data to predict what will happen next.
Your customers can use predictive analytics to foresee if a change will help them reduce risks, improve operations, and/or increase revenue. At its heart, predictive analytics answers a common user question, “What is most likely to happen based on my current data, and what can I do to change that outcome?”
Resources to Help Your Team Understand Predictive Analytics
These resources will equip your development team with the knowledge to effectively navigate the embedded analytics landscape alongside AI and machine learning, covering issues like predictive-versus-augmented analytics, integrating AI and machine learning with predictive analytics, and much more.
- Predictive vs. Augmented: Analytics Strategies for the Future: In this video, learn how streamlining data analysis with augmented analytics makes it more accessible to a larger audience, enabling more of your users to gain value from the data. Dive deep into augmented analytics, which uses combination of AI and machine learning to automate various stages of the analytics process.
- The Definitive Guide to Predictive Analytics: In this white paper, learn how embedded analytics is boosting user adoption, creating apps people love, and changing the game for software and SaaS providers. Dive into how predictive analytics answers the question of what is most likely to happen based on current data, and what can be done to change that outcome, and how it uses historical data, machine learning, and AI to predict what will happen in the future.
- Harmony in Data: Empowering Embedded BI with Logi Symphony’s AI, Machine Learning and Predictive Analytics: In this video, discover how predictive analytics is like a crystal ball for your customers. Harmony in Data: Empowering Embedded BI with Logi Symphony’s AI, Machine Learning and Predictive Analytics: In this video, discover how predictive analytics is like a crystal ball for your customers. It uses past data, machine learning, and smart AI to forecast what’s coming down the road. In the embedded analytics world, application teams provide their users with software tools that collect data that drives decision-making. Today, your customers need predictive analytics to add more value to their organizations through better use of data.
- The 5 Levels of Analytics Maturity: From Basic BI to Sophisticated Differentiators: Do the analytics in your application make you stand out from the crowd? In this white paper, see where your offerings fall on the analytics maturity scale—and learn how sophisticated capabilities can differentiate your product. The best way to make analytics a natural part of everyday work is to embed it seamlessly into business applications. And the more sophisticated capabilities you can weave into the fabric of your application, the higher your user adoption and satisfaction will be.
- Drive Better Decision-Making With Data Storytelling: As your customers can find out in this white paper, great storytelling should hold your attention. It’s a fundamental human skill, but the concept of utilizing embedded analytics and data to tell stories is still new and evolving. Fully understanding the benefits is essential to making the most of analytics.
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