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[null,"1.","Record Nr.",null,"UNINA9911008443803321"]
[null,null,"Autore",null,"Klidas Angelika"]
[null,null,"Titolo",null,"Data Literacy in Practice : A Complete Guide to Data Literacy and Making Smarter Decisions with Data Through Intelligent Actions"]
[null,null,"Pubbl/distr/stampa",null,"Birmingham : , : Packt Publishing, Limited, , 2022"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"9781803232355"]
[{"$nulls":4},"1803232358"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (396 pages)"]
[null,null,"Disciplina",null,"006.312"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Information literacy"]
[{"$nulls":4},"Decision making"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[{"$nulls":4},"Applying Goodhart's law to KPIs"]
[null,null,"Nota di contenuto",null,"Cover -- Copyright -- Contributors -- Table of Contents -- Preface -- Part 1:  Understanding the Data Literacy Conceptss -- Chapter 1: The Beginning - The Flow  of Data -- Understanding data in our daily lives -- Analyzing data -- Searching and finding information -- An introduction to data literacy -- The COVID-19 pandemic -- The organizational data flow -- The DIDM journey -- The success story of The Oakland A's -- Summary -- Chapter 2: Unfolding Your Data Journey -- Growing toward data and analytics maturity -- Descriptive analyses and the data path to maturity -- Understanding descriptive analysis -- Identifying qualitative or quantitative data -- Understanding diagnostic analysis -- Understanding predictive analytics -- Understanding prescriptive analytics -- AI -- Can data save lives? A success story -- Summary -- Chapter 3: Understanding the  Four-Pillar Model -- Gaining an understanding of the various aspects of data literacy -- Introducing the four fundamental pillars -- Becoming acquainted with organizational data literacy -- Discussing the significance of data management -- Defining a data and analytics approach -- The rapid growth of our data world -- Tools -- The rise of ML and AI -- Moving to the cloud -- Data literacy is a key aspect of data and analytics -- Understanding the education pillar -- Mixing the pillars -- Summary -- Chapter 4: Implementing Organizational Data "]
[{"$nulls":4},"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 -- Managing the organization's skills and knowledge -- Creating a data literacy educational program -- Identifying employee roles."]
[{"$nulls":4},"Learning levels -- Covering all moments of need -- Learning methodologies -- Including all knowledge types -- Learning elements -- Organizing content -- Searching for content -- Measuring success -- Celebrating successes -- Summary -- Further reading -- Chapter 5: Managing Your Data Environment -- Introducing data management -- Understanding your data quality -- Intermezzo - Starting to improve data quality in a small-scaled healthcare environment -- Delivering a data management future -- Data strategy -- Taking care of your data strategy -- Creating a data vision -- Identifying your data -- Discovering where your data is stored -- Retrieving your data -- Combining and enriching data -- Setting the standard -- Processes -- Control -- IT -- Summary -- Part 2:  Understanding How to Measure the Why, What, and How -- Chapter 6: Aligning with  Organizational Goals -- Understanding the types of indicators -- Identifying KPIs -- Characteristics of KPIs -- Leading and lagging indicators -- Reviewing for unintended consequences -- Applying Goodhart's law to KPIs -- Defining what to track -- Activity system maps -- Logic models -- Summary -- References -- Chapter 7: Designing Dashboards  and Reports -- The importance of visualizing data -- Deceiving with bad visualizations -- Using our eyes and the usage of colors -- Introducing the DAR(S) principle -- Defining your dashboard -- Choosing the right visualization -- Understanding some basic visualizations -- Bar chart (or column chart or bar graph) -- Line chart -- Pie chart -- Heatmap -- Radar chart -- Geospatial charts -- KPIs in various ways -- Tables -- Presenting some advanced visualizations -- Bullet charts -- Addressing contextual analysis -- Summary -- Chapter 8: Questioning the Data -- Being curious and critical by asking questions -- Starting with the problem - not the data."]
[{"$nulls":4},"Identifying the right key performance indicators (KPIs) ahead of time -- Questioning not just the data, but also assumptions -- Using a questioning framework -- Questioning based on the decision-making stage -- Questioning data and information -- Questioning analytic interpretations and insights -- Summary -- References -- Chapter 9: Handling Data Responsibly -- Introducing the potential risks of data and analytics -- Identifying data security concerns -- Intermezzo - a data leak at an airplane carrier -- Identifying data privacy concerns -- Identifying data ethical concerns -- Intermezzo - tax office profiles ethnically -- Summary -- Part 3:  Understanding the  Change and How to Assess Activities -- Chapter 10: Turning Insights into Decisions -- Data-informed decision-making process -- Ask - Identifying problems and interpreting requirements -- Acquire - Understanding, acquiring, and preparing relevant data -- Analyze - Transforming data into insights -- Apply - Validating the insights -- Act - Transforming insights into decisions -- Announce - Communicating decisions with data -- Assess - Evaluating outcomes of a decision -- Making a data-Informed decision in action -- Using a data-informed decision checklist -- Why data-informed over data-driven? -- Storytelling -- Why is communicating with data so hard? -- Three key elements of communication -- Why include a narrative? -- The process -- Summary -- Further reading -- Chapter 11: Defining a Data Literacy Competency Framework -- Data literacy competency framework -- Identifying "]
[{"$nulls":4},"problems and interpreting requirements -- Understanding, acquiring, and preparing relevant data -- Turning data into insights -- Validating the insights -- Transforming insights into decisions -- Communicating decisions with data -- Evaluating the outcome of a decision -- Understanding data -- Data literacy skills."]
[{"$nulls":4},"Identifying data literacy technical skills -- Data literacy soft skills -- Data literacy mindsets -- Summary -- References -- Chapter 12: Assessing Your Data  Literacy Maturity -- Assessing individual data literacy -- Assessing organizational data literacy -- Basic organizational data literacy assessment -- Robust organizational data literacy maturity assessment -- Summary -- Chapter 13: Managing Data and  Analytics Projects -- Discovering why data and analytics projects fail -- Understanding four typical data and analytics project characteristics -- Understanding data and analytics project blockers -- Pitfalls in data and analytics projects -- Lack of expertise -- The technical architecture -- Time and money -- Unfolding the data and analytics project approach -- Unfolding the data and analytics project framework -- Intermezzo 2 - successfully managing a data and analytics project -- Mitigating typical data and analytics project risks -- Project risks -- Technical risks -- Cultural risks -- Content risks -- Determining roles in data and analytics projects  (and teams) -- Managing data and analytics projects -- Writing a successful data and analytics business case -- A chapter layout for  your business case -- Finding financial justification for your project -- Argumentation for one-time project costs -- Annual recurring costs -- Argumentation for annual recurring costs -- The quantitative benefits -- ROI -- Conclusion and advice -- Summary -- Chapter 14: Appendix A - Templates -- Project intake form -- STARR TEMPLATE -- Layout for a business case -- Layout for a business case scenario description -- A business case financial analysis -- Layout for a risk assessment -- Layout for a summary business case -- Layout information and measure plan -- Layout for a KPI description -- Table with the Inmon groups and a description of their roles."]
[{"$nulls":4},"Chapter 15: Appendix B - References -- Inspirational books -- Online articles and blogs -- Dutch articles and blogs -- Online tools -- Online sites -- Index -- Other Books You May Enjoy."]
[null,null,null,"Sommario/riassunto","Understanding data is a powerful skill. This book will help you build a sound understanding of data literacy basics and build your confidence to work with data every day. Guided by best practices and real-world examples, you'll master the skills to make smarter decisions with data, fast."]