Extent: | Online-Ressource (XXIII, 244 p. 23 illus, online resource) |
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Series: | |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Description based upon print version of record Contents; Introduction; Chapter 1: Big Data; Big Data Crosses Over Into the Mainstream; How Google Puts Big Data Initiatives to Work; How Big Data Powers Amazon's Quest to Become the World's Largest Retailer; Big Data Finally Delivers the Information Advantage; What Big Data Is Disrupting; Big Data Applications Changing Your Work Day; Big Data Enables the Move to Real Time; Chapter 2: The Big Data Landscape; Big Data Market Growth; The Role of Open Source; Enter the Cloud; Overcoming the Challenges of the Cloud; Big Data Infrastructure; Big Data Applications; Online Advertising Applications Sales and Marketing ApplicationsVisualization Applications; Business Intelligence Applications; Operational Intelligence; Data as a Service; Data Cleansing; Data Privacy; Landscape Futures; Chapter 3: Your Big Data Roadmap; Goodbye SQL, Hello NoSQL; Compiling and Querying Big Data; Big Data Analysis: Getting What You Want; Big Data Analytics: Interpreting What You Get; Should I Throw Out My RDBMS ?; Big Data Hardware; Data Scientists and Data Admins: Big Data Managers; Chief Data Officer: Big Data Owner; Your Big Data Vision; Chapter 4: Big Data at Work; How Data Informs Design at Facebook Apple Defines DesignBig Data in Game Design; Better Cars with Big Data; Big Data and Music; Big Data and Architecture; Data-Driven Design; Big Data in Better Web Site Design; Chapter 5: Why a Picture is Worth a Thousand Words; Trend Spotting; The Many Types of Visualizations; How to Create Visualizations; Using Visualization to Compress Knowledge; Why Is Visual Information So Powerful?; Images and the Power of Sharing; Putting Public Data Sets to Use; Real-Time Visualization; Why Understanding Images Is Easy for Us and Hard for Computers; The Psychology and Physiology of Visualization The Visualization Multiplier EffectChapter 6: The Intersection of Big Data, Mobile, and Cloud Computing; How to Get Started with Big Data; The Latest Cloud-Based Big Data Technologies; Infrastructure; Platform; Application; Amazon Web Services (AWS); Public and Private Cloud Approaches to Big Data; How Big Data Is Changing Mobile; How to Build Your Own Big Data Applications; Defining the Business Need; Identifying Data Sources; Choosing the Right Infrastructure; Presenting Insights to Customers; Gathering the Engineering Team; Chapter 7: Doing a Big Data Project; Define the Outcome Identify the Questions to AnswerCreate Data Policies; Measure the Value; Identify Resources; Visualize the Results; Case Study: Churn Reduction; Big Data Workflow; Step 1: Create a Hypothesis; Step 2: Set Up the Systems; Step 3: Transform the Data; Step 4: Analyze the Data; Step 5: Act on the Data; Case Study: Marketing Analytics; Big Data Meets the Cloud; Step 1: Gather the Data; Step 2: Analyze the Results; Step 3: Iterate; Case Study: The Connected Car; In Short . . .; Chapter 8: The Next Billion-Dollar IPO: Big Data Entrepreneurship; Why Being Data-Driven Is Hard Hearing the Signal and Ignoring the Noise |
ISBN: | 978-1-4842-0040-7 ; 978-1-4842-0041-4 |
Other identifiers: | 10.1007/978-1-4842-0040-7 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014021193