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Author: Tye Rattenbury
Publisher: "O'Reilly Media, Inc."
ISBN: 1491938870
Category : Computers
Languages : en
Pages : 117
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Book Description
A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "What are you trying to do and why?" Wrangling data consumes roughly 50-80% of an analyst’s time before any kind of analysis is possible. Written by key executives at Trifacta, this book walks you through the wrangling process by exploring several factors—time, granularity, scope, and structure—that you need to consider as you begin to work with data. You’ll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of today’s data-driven organizations. Appreciate the importance—and the satisfaction—of wrangling data the right way. Understand what kind of data is available Choose which data to use and at what level of detail Meaningfully combine multiple sources of data Decide how to distill the results to a size and shape that can drive downstream analysis
Author: Tye Rattenbury
Publisher: "O'Reilly Media, Inc."
ISBN: 1491938870
Category : Computers
Languages : en
Pages : 117
Get Book Here
Book Description
A key task that any aspiring data-driven organization needs to learn is data wrangling, the process of converting raw data into something truly useful. This practical guide provides business analysts with an overview of various data wrangling techniques and tools, and puts the practice of data wrangling into context by asking, "What are you trying to do and why?" Wrangling data consumes roughly 50-80% of an analyst’s time before any kind of analysis is possible. Written by key executives at Trifacta, this book walks you through the wrangling process by exploring several factors—time, granularity, scope, and structure—that you need to consider as you begin to work with data. You’ll learn a shared language and a comprehensive understanding of data wrangling, with an emphasis on recent agile analytic processes used by many of today’s data-driven organizations. Appreciate the importance—and the satisfaction—of wrangling data the right way. Understand what kind of data is available Choose which data to use and at what level of detail Meaningfully combine multiple sources of data Decide how to distill the results to a size and shape that can drive downstream analysis
Author: Ziawasch Abedjan
Publisher: Springer Nature
ISBN: 3031018656
Category : Computers
Languages : en
Pages : 136
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Book Description
Data profiling refers to the activity of collecting data about data, {i.e.}, metadata. Most IT professionals and researchers who work with data have engaged in data profiling, at least informally, to understand and explore an unfamiliar dataset or to determine whether a new dataset is appropriate for a particular task at hand. Data profiling results are also important in a variety of other situations, including query optimization, data integration, and data cleaning. Simple metadata are statistics, such as the number of rows and columns, schema and datatype information, the number of distinct values, statistical value distributions, and the number of null or empty values in each column. More complex types of metadata are statements about multiple columns and their correlation, such as candidate keys, functional dependencies, and other types of dependencies. This book provides a classification of the various types of profilable metadata, discusses popular data profiling tasks, and surveys state-of-the-art profiling algorithms. While most of the book focuses on tasks and algorithms for relational data profiling, we also briefly discuss systems and techniques for profiling non-relational data such as graphs and text. We conclude with a discussion of data profiling challenges and directions for future work in this area.
Author: Veronica Barassi
Publisher: MIT Press
ISBN: 0262044714
Category : Computers
Languages : en
Pages : 233
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Book Description
An examination of the datafication of family life--in particular, the construction of our children into data subjects. Our families are being turned into data, as the digital traces we leave are shared, sold, and commodified. Children are datafied even before birth, with pregnancy apps and social media postings, and then tracked through babyhood with learning apps, smart home devices, and medical records. If we want to understand the emergence of the datafied citizen, Veronica Barassi argues, we should look at the first generation of datafied natives: our children. In Child Data Citizen, she examines the construction of children into data subjects, describing how their personal information is collected, archived, sold, and aggregated into unique profiles that can follow them across a lifetime.
Author: Jack E. Olson
Publisher: Morgan Kaufmann
ISBN: 0080884423
Category : Computers
Languages : en
Pages : 310
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Book Description
With the amount of data a business accumulates now doubling every 12 to 18 months, IT professionals need to know how to develop a system for archiving important database data, in a way that both satisfies regulatory requirements and is durable and secure. This important and timely new book explains how to solve these challenges without compromising the operation of current systems. It shows how to do all this as part of a standardized archival process that requires modest contributions from team members throughout an organization, rather than the superhuman effort of a dedicated team. - Exhaustively considers the diverse set of issues—legal, technological, and financial—affecting organizations faced with major database archiving requirements - Shows how to design and implement a database archival process that is integral to existing procedures and systems - Explores the role of players at every level of the organization—in terms of the skills they need and the contributions they can make. - Presents its ideas from a vendor-neutral perspective that can benefit any organization, regardless of its current technological investments - Provides detailed information on building the business case for all types of archiving projects
Author: Brendan McGurk KC
Publisher: Bloomsbury Publishing
ISBN: 1509920633
Category : Law
Languages : en
Pages : 317
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Book Description
The winner of the 2020 British Insurance Law Association Book Prize, this timely, expertly written book looks at the legal impact that the use of 'Big Data' will have on the provision – and substantive law – of insurance. Insurance companies are set to become some of the biggest consumers of big data which will enable them to profile prospective individual insureds at an increasingly granular level. More particularly, the book explores how: (i) insurers gain access to information relevant to assessing risk and/or the pricing of premiums; (ii) the impact which that increased information will have on substantive insurance law (and in particular duties of good faith disclosure and fair presentation of risk); and (iii) the impact that insurers' new knowledge may have on individual and group access to insurance. This raises several consequential legal questions: (i) To what extent is the use of big data analytics to profile risk compatible (at least in the EU) with the General Data Protection Regulation? (ii) Does insurers' ability to parse vast quantities of individual data about insureds invert the information asymmetry that has historically existed between insured and insurer such as to breathe life into insurers' duty of good faith disclosure? And (iii) by what means might legal challenges be brought against insurers both in relation to the use of big data and the consequences it may have on access to cover? Written by a leading expert in the field, this book will both stimulate further debate and operate as a reference text for academics and practitioners who are faced with emerging legal problems arising from the increasing opportunities that big data offers to the insurance industry.
Author: Renato Baruti
Publisher: Packt Publishing Ltd
ISBN: 1788398688
Category : Computers
Languages : en
Pages : 219
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Book Description
Implement your Business Intelligence solutions without any coding - by leveraging the power of the Alteryx platform About This Book Experience the power of codeless analytics using Alteryx, a leading Business Intelligence tool Uncover hidden trends and valuable insights from your data across different sources and make accurate predictions Includes real-world examples to put your understanding of the features in Alteryx to practical use Who This Book Is For This book is for aspiring data professionals who want to learn and implement self-service analytics from scratch, without any coding. Those who have some experience with Alteryx and want to gain more proficiency will also find this book to be useful. A basic understanding of the data science concepts is all you need to get started with this book. What You Will Learn Create efficient workflows with Alteryx to answer complex business questions Learn how to speed up the cleansing, data preparing, and shaping process Blend and join data into a single dataset for self-service analysis Write advanced expressions in Alteryx leading to an optimal workflow for efficient processing of huge data Develop high-quality, data-driven reports to improve consistency in reporting and analysis Explore the flexibility of macros by automating analytic processes Apply predictive analytics from spatial, demographic, and behavioral analysis and quickly publish, schedule Share your workflows and insights with relevant stakeholders In Detail Alteryx, as a leading data blending and advanced data analytics platform, has taken self-service data analytics to the next level. Companies worldwide often find themselves struggling to prepare and blend massive datasets that are time-consuming for analysts. Alteryx solves these problems with a repeatable workflow designed to quickly clean, prepare, blend, and join your data in a seamless manner. This book will set you on a self-service data analytics journey that will help you create efficient workflows using Alteryx, without any coding involved. It will empower you and your organization to take well-informed decisions with the help of deeper business insights from the data.Starting with the fundamentals of using Alteryx such as data preparation and blending, you will delve into the more advanced concepts such as performing predictive analytics. You will also learn how to use Alteryx's features to share the insights gained with the relevant decision makers. To ensure consistency, we will be using data from the Healthcare domain throughout this book. The knowledge you gain from this book will guide you to solve real-life problems related to Business Intelligence confidently. Whether you are a novice with Alteryx or an experienced data analyst keen to explore Alteryx's self-service analytics features, this book will be the perfect companion for you. Style and approach Comprehensive, step by step guide filled with real-world examples to step through the complex business questions using one of the leading data analytics platform.
Author: Devin Knight
Publisher: Packt Publishing Ltd
ISBN: 1789955637
Category : Computers
Languages : en
Pages : 780
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Book Description
Design, develop, and master efficient Power BI solutions for impactful business insights Key FeaturesGet to grips with the fundamentals of Microsoft Power BI Combine data from multiple sources, create visuals, and publish reports across platformsUnderstand Power BI concepts with real-world use casesBook Description Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life. In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes. Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data. By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products: Microsoft Power BI Quick Start Guide by Devin Knight et al. Mastering Microsoft Power BI by Brett PowellWhat you will learnConnect to data sources using both import and DirectQuery optionsLeverage built-in and custom visuals to design effective reportsAdminister a Power BI cloud tenant for your organizationDeploy your Power BI Desktop files into the Power BI Report ServerBuild efficient data retrieval and transformation processesWho this book is for Microsoft Power BI Complete Reference Guide is for those who want to learn and use the Power BI features to extract maximum information and make intelligent decisions that boost their business. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, then Learning Path is for you. It consists of real-world examples on Power BI and goes deep into the technical issues, covers additional protocols, and much more.
Author: Ed Lindsey
Publisher:
ISBN: 9780980083309
Category :
Languages : en
Pages : 240
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Book Description
Author: Pablo Casas
Publisher:
ISBN: 9789874273666
Category :
Languages : en
Pages :
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Book Description
This book is a practical guide to problems that commonly arise when developing a machine learning project. The book's topics are: Exploratory data analysis Data Preparation Selecting best variables Assessing Model Performance More information on predictive modeling will be included soon. This book tries to demonstrate what it says with short and well-explained examples. This is valid for both theoretical and practical aspects (through comments in the code). This book, as well as the development of a data project, is not linear. The chapters are related among them. For example, the missing values chapter can lead to the cardinality reduction in categorical variables. Or you can read the data type chapter and then change the way you deal with missing values. You¿ll find references to other websites so you can expand your study, this book is just another step in the learning journey. It's open-source and can be found at http://livebook.datascienceheroes.com
Author: Neera Bhansali
Publisher: CRC Press
ISBN: 1439879141
Category : Computers
Languages : en
Pages : 257
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Book Description
As organizations deploy business intelligence and analytic systems to harness business value from their data assets, data governance programs are quickly gaining prominence. And, although data management issues have traditionally been addressed by IT departments, organizational issues critical to successful data management require the implementatio
