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Johanna Walker,
Tom Wainwright,
and
Dave Whiteland
Topics Covered
- What is Open Data?
- Why is Open Data useful in business?
- How to assess and manage risk when using Open Data
- How Open Data can improve business
- How to create an Open Data business model
- How to use external Open Data
- How to publish Open Data
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Reviews summary
Introductory open data course
This course provides an overview of the management considerations of using open data in business, covering topics such as risk assessment and creating business models. It is suitable for beginners with no prior exposure to open data.
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Using Open Data for Digital Business.
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Learners who complete Using Open Data for Digital Business will develop knowledge and skills
that may be useful to these careers:
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Reading list
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Provides a basic introduction to Open Data. It discusses the different types of Open Data, the benefits of using Open Data, and the challenges of implementing Open Data initiatives.
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Explores the potential of Open Data for research. It discusses the different ways that Open Data can be used to conduct research, and provides case studies on the use of Open Data for research projects.
Explores the potential of Open Data for journalism. It discusses the different ways that Open Data can be used to improve journalism, and provides case studies on the use of Open Data for journalistic investigations.
Explores why successful companies often fail to innovate. Christensen argues that companies must be willing to cannibalize their own products in order to stay ahead of the competition.
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Provides a step-by-step guide to building a successful startup. Ries advocates for using a lean approach, which involves testing ideas quickly and cheaply.
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Provides practical advice on how to build relationships and develop a strong network. Ferrazzi argues that relationships are essential for success in business and in life.
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Provides a sales methodology that is designed to help salespeople close more deals. Rackham argues that salespeople should focus on asking questions and listening to customers.
Challenges the traditional sales model and argues that salespeople should focus on educating customers and helping them solve their problems.
Provides a step-by-step guide to building a high-performing sales team. Roberge is the former CEO of HubSpot and his book is full of insights that can help sales leaders of all levels improve their teams' results.
Provides a comprehensive guide to sales management. Holmes covers everything from hiring and training salespeople to developing sales processes and closing deals.
Explores the psychology of sales and provides tips on how to build rapport, handle objections, and close deals. Tracy world-renowned sales expert and his book must-read for anyone who wants to improve their sales skills.
Collection of Gitomer's best sales tips and advice. Gitomer top sales expert and his book is full of practical advice that can help salespeople of all levels.
Comprehensive guide to sales that covers everything from prospecting to closing deals. Iannarino sales expert and his book is full of practical advice that can help salespeople of all levels improve their results.
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Provides a simple and effective sales process that can help salespeople close more deals. Weinberg sales expert and his book is full of practical advice that can help salespeople of all levels.
Provides 20 essential principles for sales success. Tracy world-renowned sales expert and his book is full of practical advice that can help salespeople of all levels improve their results.
Provides a comprehensive guide to sales management. Elias sales management expert and his book is full of practical advice that can help sales managers improve their teams' performance.
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An excellent overview of Bayesian statistics, this book provides a comprehensive introduction to the theory and practice of Bayesian data analysis. The focus on practical applications and real-life examples makes it a great choice for students and practitioners alike.
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A classic text in the field of data mining, this book provides a comprehensive overview of techniques and algorithms used for extracting knowledge from large datasets. Written by leading experts in the field, it valuable resource for students and researchers.
A hands-on guide to data analysis using Python, this book covers a wide range of topics, including data cleaning, transformation, visualization, and modeling. Written by the creator of Pandas, it practical resource for students and professionals in various fields.
An authoritative text on statistical learning, this book covers a wide range of topics, including linear and nonlinear regression, classification, unsupervised learning, and model selection. It comprehensive resource for students and practitioners in various fields.
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