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How to Chunk Documents for RAG Our latest blog article provides a comprehensive guide on how to divide documents into manageable chunks while preserving context and improving response accuracy. - Improved Contextual Understanding: Learn how dividing documents into smaller segments helps in maintaining contextual integrity and reduces information overload. - Efficient Retrieval: Discover various chunking strategies like fixed-size, sentence-based, paragraph-based, and semantic-based chunks to ensure optimal performance. - Enhanced Metadata Usage: Understand how enriching each chunk with metadata and converting them into numerical representations (embeddings) boosts semantic understanding. - Sustained Context Between Chunks: Explore the importance of overlapping segments to maintain continuity and improve system performance. This article is part of our series on making your data AI-ready. Don't miss out on these valuable insights that could transform your data processing approach! https://lnkd.in/dggZRree #TextGeneration #RAGSystems #DocumentChunking #DataProcessing #AIReadyData #MetadataManagement #SemanticUnderstanding #MultimodalAI

Recommended by an off-LinkedIn colleague, this book was described to me as the “holy grail of data visualization strategy.” Only halfway through but I’ll already echo that sentiment. Tufte does a fantastic job of describing the ethics and psychology of visualization techniques in a way that isn’t overwhelmingly technical. Great read for anyone with an interest in the history, art, and science of responsibly transforming data from numbers into graphical representations. #analytics #data

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

I am excited about our new tools and how they will give time back to our valuable #marketresearchers! I have a demo recording I am happy to share or just give me a nudge and I’d be happy to take you through it, together. #qualresearch #mrx #onlinequal

Are we accurately using visualization in our research papers? I recently read the book "How to Lie with Statistics" and among many other things, it talked about how data visualization can be used to deceive. One example the book discusses is how advertisers can use maps to misrepresent information - the #data may be accurate, but the visualization distorts the true picture. This struck a chord with me when I was reading a review paper that presented global research output using a world map. The numbers and statistics were all there, but the visual representation was quite misleading. Most research activity is concentrated in countries with larger economies and land areas. So even with a relatively small range of publication counts (e.g. 1 to 15 papers), the map visualization can make it seem like there is a huge disparity in research output globally. Rather than using an area-based map, I think a better approach would be to present the data in a simple table format. This would allow readers to clearly see the actual publication counts for each country, without the distortion introduced by the map visualization. A sorted table, a simple bar chart may provide a more accurate and transparent way to communicate the research landscape. I believe, the key is to choose a #visualization that accurately represents the underlying data, rather than one that creates a misleading impression. Well that's what I think. Let me know what you think in the comments.