book

Data Science For Dummies

by Lillian Pierson

March 2015

Beginner

408 pages

10h 4m

English

For Dummies

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About This BookFoolish AssumptionsIcons Used in This BookBeyond the BookWhere to Go from Here
Seeing Who Can Make Use of Data ScienceLooking at the Pieces of the Data Science PuzzleGetting a Basic Lay of the Data Science Landscape
Defining Big Data by Its Four VsIdentifying Big Data SourcesGrasping the Difference between Data Science and Data EngineeringBoiling Down Data with MapReduce and HadoopIdentifying Alternative Big Data SolutionsData Engineering in Action — A Case Study
Incorporating Data-Driven Insights into the Business ProcessDistinguishing Business Intelligence and Data ScienceKnowing Who to Call to Get the Job Done RightExploring Data Science in Business: A Data-Driven Business Success Story
Introducing the Fundamental Concepts of ProbabilityIntroducing Linear RegressionSimulationsIntroducing Time Series Analysis
Introducing the Basics of Clustering and ClassificationIdentifying Clusters in Your Data

Making Sense of Data with Nearest Neighbor AnalysisSeeing the Importance of Clustering and ClassificationClassifying Data with Average Nearest Neighbor AlgorithmsClassifying with K-Nearest Neighbor AlgorithmsUsing Nearest Neighbor Distances to Infer Meaning from Point PatternsSolving Real-World Problems with Nearest Neighbor Algorithms
Introducing Multi-Criteria Decision Making (MCDM)Using Numerical Methods in Data ScienceMathematical Modeling with Markov Chains and Stochastic Methods
Generating Predictive Surfaces from Spatial Point DataUsing Trend Surface Analysis on Spatial Data
Understanding the Types of VisualizationsFocusing on Your AudiencePicking the Most Appropriate Design StyleKnowing When to Add ContextKnowing When to Get PersuasiveChoosing the Most Appropriate Data Graphic TypeChoosing Your Data Graphic
Introducing the D3.js LibraryKnowing When to Use D3.js (and When Not To)Getting Started in D3.jsUnderstanding More Advanced Concepts and Practices in D3.js
Using Collaborative Data Visualization PlatformsVisualizing Spatial Data with Online Geographic ToolsVisualizing with Open Source: Web-Based Data Visualization PlatformsKnowing When to Stick with Infographics
Focusing on the AudienceStarting with the Big PictureGetting the Details RightTesting Your Design
Getting into the Basics of GISAnalyzing Spatial DataGetting Started with Open-Source QGIS
Understanding Basic Concepts in PythonGetting on a First-Name Basis with Some Useful Python LibrariesUsing Python to Analyze Data — An Example Exercise
Introducing the Fundamental ConceptsPreviewing R Packages
Getting Started with SQLUsing SQL and Its Functions in Data Science
Making Life Easier with ExcelUsing KNIME for Advanced Data Analytics
Exploring the Five Ws and an HCollecting Data for Your StoryFinding and Telling Your Data’s StoryBringing Data Journalism to Life: Washington Post’s The Black Budget
Modeling Environmental-Human Interactions with Environmental IntelligenceModeling Natural Resources in the RawUsing Spatial Statistics to Predict for Environmental Variation across Space
Making Sense of Data for E-Commerce GrowthOptimizing E-Commerce Business Systems
Temporal Analysis for Crime Prevention and MonitoringSpatial Crime Prediction and MonitoringProbing the Problems with Data Science for Crime Analysis
Digging through Data.govChecking Out Canada Open DataDiving into data.gov.ukChecking Out U.S. Census Bureau DataKnowing NASA DataWrangling World Bank DataGetting to Know Knoema DataQueuing Up with Quandl DataExploring Exversion DataMapping OpenStreetMap Spatial Data
Making Custom Web-Based Data Visualizations with Free R PackagesChecking Out More Scraping, Collecting, and Handling ToolsChecking Out More Data Exploration ToolsChecking Out More Web-Based Visualization Tools

Overview

Discover how data science can help you gain in-depth insight into your business - the easy way!

Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization.

Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis

Details different data visualization techniques that can be used to showcase and summarize your data

Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques

Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark

It's a big, big data world out there - let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

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Publisher Resources

ISBN: 9781118841525Purchase book

Data Science For Dummies

by Lillian Pierson

Overview

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

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