Best Practices In Data Cleaning

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Best Practices In Data Cleaning

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Author : Jason W. Osborne
language : en
Publisher: SAGE Publications
Release Date : 2012-01-10

Best Practices In Data Cleaning written by Jason W. Osborne and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-10 with Social Science categories.

Many researchers jump from data collection directly into testing hypothesis without realizing these tests can go profoundly wrong without clean data. This book provides a clear, accessible, step-by-step process of important best practices in preparing for data collection, testing assumptions, and examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of the handbook Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are evidence-based and will motivate change in practice by empirically demonstrating—for each topic—the benefits of following best practices and the potential consequences of not following these guidelines.

Python Data Cleaning And Preparation Best Practices

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Author : Maria Zervou
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-27

Python Data Cleaning And Preparation Best Practices written by Maria Zervou and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-27 with Computers categories.

Take your data preparation skills to the next level by converting any type of data asset into a structured, formatted, and readily usable dataset Key Features Maximize the value of your data through effective data cleaning methods Enhance your data skills using strategies for handling structured and unstructured data Elevate the quality of your data products by testing and validating your data pipelines Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionProfessionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone. To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio. By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.What you will learn Ingest data from different sources and write it to the required sinks Profile and validate data pipelines for better quality control Get up to speed with grouping, merging, and joining structured data Handle missing values and outliers in structured datasets Implement techniques to manipulate and transform time series data Apply structure to text, image, voice, and other unstructured data Who this book is for Whether you're a data analyst, data engineer, data scientist, or a data professional responsible for data preparation and cleaning, this book is for you. Working knowledge of Python programming is needed to get the most out of this book.

Best Practices In Quantitative Methods

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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2008

Best Practices In Quantitative Methods written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language Arts & Disciplines categories.

The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Data Cleaning With Power Bi

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Author : Gus Frazer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-02-29

Data Cleaning With Power Bi written by Gus Frazer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Computers categories.

Unlock the full potential of your data by mastering the art of cleaning, preparing, and transforming data with Power BI for smarter insights and data visualizations Key Features Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BI Conduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M language Apply your newfound knowledge to tackle common data challenges for visualizations in Power BI Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMicrosoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization. This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You’ll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you’ll explore Power BI’s data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you’ll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier. By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.What you will learn Connect to data sources using both import and DirectQuery options Use the Query Editor to apply data transformations Transform your data using the M query language Design clean and optimized data models by creating relationships and DAX calculations Perform exploratory data analysis using Power BI Address the most common data challenges with best practices Explore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaning Who this book is for If you’re a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It’s a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.

Exam Ref Dp 100 Designing And Implementing A Data Science Solution On Azure

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Author : Dayne Sorvisto
language : en
Publisher: Microsoft Press
Release Date : 2024-12-06

Exam Ref Dp 100 Designing And Implementing A Data Science Solution On Azure written by Dayne Sorvisto and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Computers categories.

Prepare for Microsoft Exam DP-100 and demonstrate your real-world knowledge of managing data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Python, Azure Machine Learning, and MLflow. Designed for professionals with data science experience, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Scientist Associate level. Focus on the expertise measured by these objectives: Design and prepare a machine learning solution Explore data and train models Prepare a model for deployment Deploy and retrain a model This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you have experience in designing and creating a suitable working environment for data science workloads, training machine learning models, and managing, deploying, and monitoring scalable machine learning solutions About the Exam Exam DP-100 focuses on knowledge needed to design and prepare a machine learning solution, manage an Azure Machine Learning workspace, explore data and train models, create models by using the Azure Machine Learning designer, prepare a model for deployment, manage models in Azure Machine Learning, deploy and retrain a model, and apply machine learning operations (MLOps) practices. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Scientist Associate credential, demonstrating your expertise in applying data science and machine learning to implement and run machine learning workloads on Azure, including knowledge and experience using Azure Machine Learning and MLflow.

Artificial Intelligence Fundamentals Asq S Pocket Guide

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Author : Jayet Moon
language : en
Publisher: Quality Press
Release Date : 2025-04-15

Artificial Intelligence Fundamentals Asq S Pocket Guide written by Jayet Moon and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.

How is understanding artificial intelligence (AI) and machine learning (ML) useful to a quality professional? The answer may surprise you. With Artificial Intelligence Fundamentals, you’ll learn how these new technologies can be integrated into everyday quality management practices to make your work faster, efficient, scalable, and more effective. Author Jayet Moon covers a wide range of topics, including working with ChatGPT, successfully using AI for problem solving, and following best practices.

Data Ai Imperative

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Author : Lillian Pierson
language : en
Publisher: John Wiley & Sons
Release Date : 2024-12-03

Data Ai Imperative written by Lillian Pierson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.

Unlock predictable bottom line growth through tailored data and AI strategies. In The Data & AI Imperative: Designing Strategies for Exponential Growth, celebrated data-driven growth leader, Lillian Pierson, delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth. With over two decades of experience, Pierson unveils her proprietary STAR framework through which you'll learn to survey, take stock of, and assess your company's current state. Finally, you'll be guided on how to recommend strategies that drive growth via the execution of optimally positioned data- and AI- intensive projects or products that directly improve your business bottom line. From conception to execution, learn to: Identify high-impact opportunities for data or AI interventions within your business. Assess your organization's readiness and data literacy to ensure successful outcomes. Implement practical, effective tactics for overseeing your data-intensive projects, from strategic plans to profitable realities. Develop and deploy AI and data strategies that exceed your business goals. While ideal for executives, managers, and other leaders of data- or AI-intensive companies, The Data & AI Imperative is also invaluable to data and technical professionals who aspire to elevate their impact by turning technical expertise into strategic leadership success.

Proceedings Of The International Conference On Computational Innovations And Emerging Trends Icciet 2024

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Author : K. Reddy Madhavi
language : en
Publisher: Springer Nature
Release Date : 2024-07-30

Proceedings Of The International Conference On Computational Innovations And Emerging Trends Icciet 2024 written by K. Reddy Madhavi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Computers categories.

This is an open access book. International Conference on Computational Innovations and Emerging Trends ICCIET- 2K24 ICCIET’24 has emerged as an enduring techno-platform to connect education experts and passionate educators all over the world for improving the potential for excellence in engineering education. It provides a premier interdisciplinary forum for researchers, engineers, academicians to present and discuss the most recent trends, innovations, concerns, practical challenges encountered, solutions adopted in the field of Computational Intelligence with its allied areas. The conference also aims to provide a platform for scientists, scholars, students from universities all around the world and the industry to present ongoing research activities and hence to foster research relations between the universities and the industry. Scope of the Conference The conference focuses on mutually sharing the advances and innovative technologies for the scientists, scholars, engineers and students from different universities and industry practitioners, to present ongoing research activities in the recent trends of Computer Science and Engineering This conference addresses the relevant topics and research issues in the vicinity of Computational Intelligence and hence to foster collaborations among stakeholders and researchers from distinct universities, national laboratories, government funding bodies and the industry.

Python Data Cleaning And Preparation Best Practices

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Author : Maria Zervou
language : en
Publisher:
Release Date : 2024-09-27

Python Data Cleaning And Preparation Best Practices written by Maria Zervou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-27 with categories.

Python Programming Basic To Advanced

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Author : Puja S. Gholap
language : en
Publisher: GRIN Verlag
Release Date : 2025-05-26

Python Programming Basic To Advanced written by Puja S. Gholap and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Computers categories.

Document from the year 2025 in the subject Engineering - Computer Engineering, grade: A, Savitribai Phule Pune University, formerly University of Pune (Savitribai Phule Pune University), course: B.E, language: English, abstract: Welcome to a comprehensive journey through the world of Python programming, a language that has revolutionized the field of computer science and continues to be a vital tool in various professional domains. This book, "Python Programming for All: Basic to Advanced," aims to empower readers like you with the knowledge and skills to harness the full potential of Python, no matter your starting point. Python's simplicity and versatility have made it one of the most beloved programming languages among both beginners and seasoned coders. Whether you are a student, a hobbyist, a professional coder, or even someone from a non-technical background looking to dip your toes into the world of programming, this book is for you. The book is structured to provide a gradual learning experience, starting from the very basics and gradually moving towards advanced concepts. In the early chapters, you will be introduced to the fundamental aspects of Python, such as syntax, data types, and control structures. As you progress, you will explore more complex topics like object-oriented programming, data structures, algorithms, and more. By the end, you will be equipped to use Python for a wide range of applications, from web development and data analysis to artificial intelligence and machine learning. Each chapter is designed with a balance of theory and practical examples, followed by exercises that reinforce learning. The book also includes useful tips and tricks, common pitfalls to avoid, and insights into how Python is used in the real world. The goal of "Python Programming for All: Basic to Advance" is not just to teach you Python, but also to instill a problem-solving mindset and coding best practices. This will enable you to not just understand Python, but also to think like a Python programmer. We hope that this book will ignite your passion for programming and open up new opportunities for you in the digital world. So, get ready to embark on a thrilling adventure into the world of Python programming!