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Data Literacy in Practice

Data Literacy in Practice

By : Angelika Klidas, Kevin Hanegan
4.5 (10)
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Data Literacy in Practice

Data Literacy in Practice

4.5 (10)
By: Angelika Klidas, Kevin Hanegan

Overview of this book

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.
Table of Contents (21 chapters)
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1
Part 1: Understanding the Data Literacy Concepts
7
Part 2: Understanding How to Measure the Why, What, and How
12
Part 3: Understanding the Change and How to Assess Activities

Questioning the Data

There is an old saying: Curiosity killed the cat. This is often mentioned as a way to highlight to individuals who ask too many questions that they may not like the answers they get. People tend to hear this quote and think that curiosity is seen as a bad thing, because it may have unintended consequences. However, did you know this is not the full saying? The saying goes on: but satisfaction brought it back. This highlights that people should embrace curiosity, even if it does have some unintended consequences.

This saying highlights the critical data literacy skill of questioning. The most important part of the process of working with data is ensuring you understand what is being asked. There’s no such thing as asking too many questions when making decisions using data.

In this chapter, we’re going to cover the following main topics:

  • Being curious and critical by asking questions
  • Questioning based on the decision-making stage
  • ...
CONTINUE READING
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Data Literacy in Practice
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