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address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap;
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Science is increasingly driven by data, and spatial data underpin the science directions laid out in the 2007 U.S. Geological Survey (USGS;
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data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers;
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--is revolutionizing business. Offering real-world insight and explanations, this book provides a roadmap for organizations looking to develop a profitable big;
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describes the agility that comes from collaborative commerce, and provides key decision makers the implementation roadmap they need to build a;
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simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the;
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expensive data warehouse—solve the basic problem of bad data quality practices. Journey to Data Quality offers a roadmap that can be used by;
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together in order to reduce data storage size, package transfer size and response time to driver's queries; and finally to control the exchange;
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are remote and potentially dangerous to access. One promising new technology for data collection is unmanned aircraft systems (UAS), which may;
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insight into the mathematical techniques used to describe and model geometrical elements. The book then explores the link between the demands;
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accurate and confident decision making that is based on insight. For companies to thrive in the global post-recession marketplace, their management;
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where they fit into the analytical ecosystem Look at the Internet of your things and find ways to discover and draw on the insights your data;
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warehouse - solve the basic problem of bad data quality practices. Journey to Data Quality offers a roadmap that can be used by practitioners;
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with the Import Wizard and external file interface, and using access methods to read data. Let these examples save you time when reading;
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need has led to the development of many different time series causality approaches and tools including transfer entropy, convergent cross;
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architecture framework * Roadmap to introduce big data as a service for potential clients * Presents a thorough description of each component in the;
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Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments;
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Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and;
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, Athena, and SalesForce and visualize using QuickSight * Understand how to prepare data using QuickSight without the need of an IT developer;
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manager. This work addresses these challenges and provides a roadmap to managing every aspect of data warehouse design, development, and;
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Use Big Data and technology to uncover real-world insights You don't need a time machine to predict the future. All it takes is a little;
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practitioners have to address for effective big data innovation. The book proposes a process-based model to identify and implement big data innovation;
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Time is a decisive factor in the processing of big data. Tuning these processes can dramatically reduce the time required. Traditional;
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which determines what data to collect, how to collect these data, and how to reduce the noise in the data based on smartphone sensors;
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. But how do you embed the use of data and analytics across your organisation so they truly support every process end-to-end? Becoming data;
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that they need to go back to the drawing board and produce a brand new BIdata warehousing roadmap to help move their enterprises from their;
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