Data Analytics Initiatives PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analytics Initiatives PDF full book. Access full book title Data Analytics Initiatives by Ondřej Bothe. Download full books in PDF and EPUB format.

Data Analytics Initiatives

Data Analytics Initiatives PDF Author: Ondřej Bothe
Publisher: CRC Press
ISBN: 1000629341
Category : Computers
Languages : en
Pages : 169

Book Description
The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

Data Analytics Initiatives

Data Analytics Initiatives PDF Author: Ondřej Bothe
Publisher: CRC Press
ISBN: 1000629341
Category : Computers
Languages : en
Pages : 169

Book Description
The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

Governance Models for Creating Public Value in Open Data Initiatives

Governance Models for Creating Public Value in Open Data Initiatives PDF Author: Manuel Pedro Rodríguez Bolívar
Publisher: Springer
ISBN: 3030144461
Category : Political Science
Languages : en
Pages : 181

Book Description
This book relies on the conceptual model of Open Government (OG), focusing on transparency and, concretely, in open data initiatives at the local government context with the aim of improving participation and collaboration. Most Open Government models are centered on three pillars: transparency, participation and collaboration. Transparency is a crucial ingredient of OG and, applied to data openness means to ensure that the data are well known, comprehensible, easily accessible and open to all. new governance models based on different open data models have not been proposed up to now. The chapter authors seek to contribute recent research to the discussion on governance models of open data initiatives to support Open Governments with the aim of creating public value. It includes both theoretical and empirical studies on governments models in open data initiatives.

The State of Open Data

The State of Open Data PDF Author: Davies, Tim
Publisher: African Minds
ISBN: 1928331955
Category : Social Science
Languages : en
Pages : 590

Book Description
It’s been ten years since open data first broke onto the global stage. Over the past decade, thousands of programmes and projects around the world have worked to open data and use it to address a myriad of social and economic challenges. Meanwhile, issues related to data rights and privacy have moved to the centre of public and political discourse. As the open data movement enters a new phase in its evolution, shifting to target real-world problems and embed open data thinking into other existing or emerging communities of practice, big questions still remain. How will open data initiatives respond to new concerns about privacy, inclusion, and artificial intelligence? And what can we learn from the last decade in order to deliver impact where it is most needed? The State of Open Data brings together over 60 authors from around the world to address these questions and to take stock of the real progress made to date across sectors and around the world, uncovering the issues that will shape the future of open data in the years to come.

Ninth Review of the International Monetary Fund’s Data Standards Initiatives

Ninth Review of the International Monetary Fund’s Data Standards Initiatives PDF Author: International Monetary Fund
Publisher: International Monetary Fund
ISBN: 1498344771
Category : Computers
Languages : en
Pages : 51

Book Description
The International Monetary Fund’s Executive Board regularly reviews progress and developments under the Data Standards Initiatives. The last review—Eighth Review—undertaken in February 2012 introduced the Special Data Dissemination Standard (SDDS) Plus. In light of the long experience under the Data Standards Initiatives established in the mid-1990s, this review takes a longer term retrospective on what has been achieved so far, and highlights some of the lessons learned. What is evident is the contrast between the progress of countries with more advanced dissemination practices (SDDS and SDDS Plus), and the slow pace of improvement under the General Data Dissemination System (GDDS).

Big Data Meets Survey Science

Big Data Meets Survey Science PDF Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784

Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.

Enhancing Access to and Sharing of Data Reconciling Risks and Benefits for Data Re-use across Societies

Enhancing Access to and Sharing of Data Reconciling Risks and Benefits for Data Re-use across Societies PDF Author: OECD
Publisher: OECD Publishing
ISBN: 9264660658
Category :
Languages : en
Pages : 138

Book Description
This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.

Sharing Clinical Research Data

Sharing Clinical Research Data PDF Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309268745
Category : Medical
Languages : en
Pages : 157

Book Description
Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and "low-hanging fruit" opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances.

Applying Business Intelligence Initiatives in Healthcare and Organizational Settings

Applying Business Intelligence Initiatives in Healthcare and Organizational Settings PDF Author: Miah, Shah J.
Publisher: IGI Global
ISBN: 1522557199
Category : Business & Economics
Languages : en
Pages : 402

Book Description
Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Applying Business Intelligence Initiatives in Healthcare and Organizational Settings incorporates emerging concepts, methods, models, and relevant applications of business intelligence systems within problem contexts of healthcare and other organizational boundaries. Featuring coverage on a broad range of topics such as rise of embedded analytics, competitive advantage, and strategic capability, this book is ideally designed for business analysts, investors, corporate managers, and entrepreneurs seeking to advance their understanding and practice of business intelligence.

Democratizing Our Data

Democratizing Our Data PDF Author: Julia Lane
Publisher: MIT Press
ISBN: 0262542749
Category : Political Science
Languages : en
Pages : 187

Book Description
A wake-up call for America to create a new framework for democratizing data. Public data are foundational to our democratic system. People need consistently high-quality information from trustworthy sources. In the new economy, wealth is generated by access to data; government's job is to democratize the data playing field. Yet data produced by the American government are getting worse and costing more. In Democratizing Our Data, Julia Lane argues that good data are essential for democracy. Her book is a wake-up call to America to fix its broken public data system.

Sixth Review of the Fund's Data Standards Initiatives

Sixth Review of the Fund's Data Standards Initiatives PDF Author: International Monetary Fund. Statistics Dept.
Publisher: International Monetary Fund
ISBN: 1498331459
Category : Computers
Languages : en
Pages : 53

Book Description
The Data Standards Initiatives, the SDDS and the GDDS, have achieved the goals the Executive Board set in its Fifth Review of July 2003. The staff sees the next three years as a period of consolidating these gains by maintaining the credibility of the SDDS through improved monitoring of countries’ observance of its requirements, and further integrating both the SDDS and GDDS under the Fund’s Data Quality Program (DQP) by aligning their structure with the Fund’s Data Quality Assessment Framework (DQAF). The staff proposes to include no new data categories in the SDDS and GDDS. Instead, the staff proposes to deepen descriptive information on how countries cover oil and gas activities and products in selected existing data categories.