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Tryggvi Bjorgvinsson

The Art of Data Usability

Edition 1

The Art of Data Usability

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Best.Nr.
978-1-6172-9471-6
Erschienen am
28.09.2019
Sprache
Englisch
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Versandkostenfrei nach Deutschland und in die Schweiz
€ 41,72
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Data is only valuable if it's useful. If you're responsible for making meaningful data available to business stakeholders, researchers, or even the general public, you need a predictable process for discerning the users' needs and delivering the right data in the right way. So how do you establish the correct priorities and measures of relevance? How do you continuously improve your data projects? This is the essential art of data usability.

 

The Art of Data Usability teaches you to think about data quality in context, presenting a methodology to maximize the usefulness of data for its intended consumers. In this practical guide, you'll master an iterative process for identifying and refining user data needs and reflecting those requirements in your data projects.

 

Key Features

·   Attributes of quality data

·   Identifying user needs and requirements

·   Using Python for data quality monitoring

·   Best practices and methods to improve data usability

 

Audience

Written for readers comfortable with data management and common data formats such CSV and JSON.

 

Tryggvi Björgvinsson is the head of IT and dissemination at Statistics Iceland. He holds a Ph.D. in software engineering.



Data is only valuable if it's useful. If you're responsible for making meaningful data available to business stakeholders, researchers, or even the general public, you need a predictable process for discerning the users' needs and delivering the right data in the right way. So how do you establish the correct priorities and measures of relevance? How do you continuously improve your data projects? This is the essential art of data usability.

 

The Art of Data Usability teaches you to think about data quality in context, presenting a methodology to maximize the usefulness of data for its intended consumers. In this practical guide, you'll master an iterative process for identifying and refining user data needs and reflecting those requirements in your data projects.

 

Key Features

·   Attributes of quality data

·   Identifying user needs and requirements

·   Using Python for data quality monitoring

·   Best practices and methods to improve data usability

 

Audience

Written for readers comfortable with data management and common data formats such CSV and JSON.

 

Tryggvi Björgvinsson is the head of IT and dissemination at Statistics Iceland. He holds a Ph.D. in software engineering.

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