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Data Literacy in Practice A Complete Guide to Data Literacy and Making Smarter Decisions with Data Through Intelligent Actions /
Accelerate your journey to smarter decision making by mastering the fundamentals of data literacy and developing the mindset to work confidently with data Key Features Get a solid grasp of data literacy fundamentals to support your next steps in your career Learn how to work with data and extract me...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2022.
|
| Edición: | 1st edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 049 | |a UAMI | ||
| 100 | 1 | |a Klidas, Angelika, |e author. | |
| 245 | 1 | 0 | |a Data Literacy in Practice |h [electronic resource] : |b A Complete Guide to Data Literacy and Making Smarter Decisions with Data Through Intelligent Actions / |c Angelika Klidas, Kevin Hanegan. |
| 250 | |a 1st edition. | ||
| 260 | |a Birmingham : |b Packt Publishing, Limited, |c 2022. | ||
| 300 | |a 1 online resource (396 p.) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a computer |2 rdamedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 500 | |a Description based upon print version of record. | ||
| 505 | 0 | |a Cover -- Copyright -- Contributors -- Table of Contents -- Preface -- Part 1: Understanding the Data Literacy Conceptss -- Chapter 1: The Beginning -- The Flow of Data -- Understanding data in our daily lives -- Analyzing data -- Searching and finding information -- An introduction to data literacy -- The COVID-19 pandemic -- The organizational data flow -- The DIDM journey -- The success story of The Oakland A's -- Summary -- Chapter 2: Unfolding Your Data Journey -- Growing toward data and analytics maturity -- Descriptive analyses and the data path to maturity | |
| 505 | 8 | |a Understanding descriptive analysis -- Identifying qualitative or quantitative data -- Understanding diagnostic analysis -- Understanding predictive analytics -- Understanding prescriptive analytics -- AI -- Can data save lives? A success story -- Summary -- Chapter 3: Understanding the Four-Pillar Model -- Gaining an understanding of the various aspects of data literacy -- Introducing the four fundamental pillars -- Becoming acquainted with organizational data literacy -- Discussing the significance of data management -- Defining a data and analytics approach | |
| 505 | 8 | |a The rapid growth of our data world -- Tools -- The rise of ML and AI -- Moving to the cloud -- Data literacy is a key aspect of data and analytics -- Understanding the education pillar -- Mixing the pillars -- Summary -- Chapter 4: Implementing Organizational Data Literacy -- Implementing organizational data literacy -- Planning the data literacy vision -- Communicating the data literacy vision -- Focusing on desired outcomes -- Adopting a systemic perspective -- Getting everyone involved in the whole process -- Developing a data-literate culture -- Managing change -- Driving resilience | |
| 505 | 8 | |a Managing the organization's skills and knowledge -- Creating a data literacy educational program -- Identifying employee roles -- Learning levels -- Covering all moments of need -- Learning methodologies -- Including all knowledge types -- Learning elements -- Organizing content -- Searching for content -- Measuring success -- Celebrating successes -- Summary -- Further reading -- Chapter 5: Managing Your Data Environment -- Introducing data management -- Understanding your data quality -- Intermezzo -- Starting to improve data quality in a small-scaled healthcare environment | |
| 505 | 8 | |a Delivering a data management future -- Data strategy -- Taking care of your data strategy -- Creating a data vision -- Identifying your data -- Discovering where your data is stored -- Retrieving your data -- Combining and enriching data -- Setting the standard -- Processes -- Control -- IT -- Summary -- Part 2: Understanding How to Measure the Why, What, and How -- Chapter 6: Aligning with Organizational Goals -- Understanding the types of indicators -- Identifying KPIs -- Characteristics of KPIs -- Leading and lagging indicators -- Reviewing for unintended consequences | |
| 500 | |a Applying Goodhart's law to KPIs | ||
| 520 | |a Accelerate your journey to smarter decision making by mastering the fundamentals of data literacy and developing the mindset to work confidently with data Key Features Get a solid grasp of data literacy fundamentals to support your next steps in your career Learn how to work with data and extract meaningful insights to take the right actions Apply your knowledge to real-world business intelligence projects Book Description Data is more than a mere commodity in our digital world. It is the ebb and flow of our modern existence. Individuals, teams, and enterprises working with data can unlock a new realm of possibilities. And the resultant agility, growth, and inevitable success have one origin--data literacy. This comprehensive guide is written by two data literacy pioneers, each with a thorough footprint within the data and analytics commercial world and lectures at top universities in the US and the Netherlands. Complete with best practices, practical models, and real-world examples, Data Literacy in Practice will help you start making your data work for you by building your understanding of data literacy basics and accelerating your journey to independently uncovering insights. You'll learn the four-pillar model that underpins all data and analytics and explore concepts such as measuring data quality, setting up a pragmatic data management environment, choosing the right graphs for your readers, and questioning your insights. By the end of the book, you'll be equipped with a combination of skills and mindset as well as with tools and frameworks that will allow you to find insights and meaning within your data for data-informed decision making. What you will learn Start your data literacy journey with simple and actionable steps Apply the four-pillar model for organizations to transform data into insights Discover which skills you need to work confidently with data Visualize data and create compelling visual data stories Measure, improve, and leverage your data to meet organizational goals Master the process of drawing insights, ask critical questions and action your insights Discover the right steps to take when you analyze insights Who this book is for This book is for data analysts, data professionals, and data teams starting or wanting to accelerate their data literacy journey. If you're looking to develop the skills and mindset you need to work independently with data, as well as a solid knowledge base of the tools and frameworks, you'll find this book useful. | ||
| 504 | |a Includes bibliographical references (pages 355-359) and index. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Information literacy. | |
| 650 | 0 | |a Decision making. | |
| 650 | 7 | |a Data mining. |2 fast |0 (OCoLC)fst00887946 | |
| 650 | 7 | |a Decision making. |2 fast |0 (OCoLC)fst00889035 | |
| 650 | 7 | |a Information literacy. |2 fast |0 (OCoLC)fst00972560 | |
| 700 | 1 | |a Hanegan, Kevin, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Klidas, Angelika |t Data Literacy in Practice |d Birmingham : Packt Publishing, Limited,c2022 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781803246758/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH40491796 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL30279148 | ||
| 938 | |a YBP Library Services |b YANK |n 303296601 | ||
| 938 | |a EBSCOhost |b EBSC |n 3469529 | ||
| 994 | |a 92 |b IZTAP | ||