Now more than ever, businesses are inundated with data, requiring robust tools for analysis, decision-making and driving growth. The landscape of data analytics is dominated by two models: Embedded Analytics and Traditional Business Intelligence (BI).
Each offers distinct benefits and could be pivotal in leveraging data to drive business success.
This whitepaper delves into these approaches, providing a comprehensive comparison to aid in selecting the optimal tool for your analytics needs.
Fill out the form to continue reading.
Casey Ciniello is a data and analytics-focused product leader at Infragistics, where she drives strategy and innovation for the Reveal embedded analytics platform and the Slingshot work management solution. With a BA in mathematics and an MBA, she brings an in-depth analytical foundation and business perspective to building products that help organizations turn complex data into actionable insights.
Casey leads the development of analytics-driven capabilities, shaping product direction through deep market analysis, user behavior insights, and evolving business intelligence trends. She works closely with customers to understand how data is used in real-world decision-making and translates those needs into intuitive, high-impact analytics experiences. Casey also serves as the Survey Lead for the annual Reveal Software Development Challenges survey, where she analyzes industry data to uncover key trends in analytics, AI, and modern development practices. Her insights and thought leadership have been featured in Dataversity, RT Insights, SaaSXtra, SD Times, Solutions Review, TechStrong IT, App Developer Magazine, Beta News, Integration Developer News, and UX Planet. She is a frequent webinar presenter on modern embedded analytics, machine learning, data visualizations, and scaling SaaS analytics. Casey joined Infragistics in 2013.
