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The Open Data Foundation
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دانلود کتاب Big Data For Dummies
BIG Data مهم ترین روند تکنولوژی که دارای پتانسیل بالایی به منظور نمایش داده های بزرگ برای Dummies است. BIG Data در حال تبدیل شدن به یکی از عواملی است که سازمان ها از اطلاعات استفاده می کنند تا تجربه مشتری را بهبود بخشند و مدل های کسب و کار خود را تغییر دهند. چگونه است که یک شرکت در مورد استفاده از داده ها به بهترین وجه ممکن عمل می کند و از اطلاعات بهترین استفاده را می کند؟
خب، هر آنچیزی که باید ...
هم چنین در این آموزش می توانید پاسخ پرسشهای زیر را نیز ببینید :
Standards OrganizationsHurwitz & Associates
Study Best Practices and Leverage Patterns
Continually Test Your Assumptions
Plan for Data Stewardship
Plan a Data Governance Strategy
Plan for Security in Context with Big Data
Understand the Technology Options
Figure Out What Data You Don’t Have
Preventing Fraud with Big Data Analytics The Business Beneft of Integrating
Using Big Data Analytics to Determine Next Best Action
The business value to the big data analytics implementation
Improving the Customer Experience with Text Analytics
Understanding Companies’ Needs for Big Data Analytics
alternative sources of energy Connecting Streaming Data to Historical and Other
Using streaming data to increase energy efficiency Using streaming data to advance the production of
Streaming Data in the Energy Industry
Streaming Data in the Healthcare Industry
Capturing the data stream
Streaming Data with a Public Policy Impact
The benefts of real-time data
Streaming Data with an Environmental Impact Using sensors to provide real-time information about
The value of streaming data
he value of streaming data
Understanding Companies’ Needs for Data in Motion
Transforming Business Processes with Big Data
Planning for Big Data
Getting your big data strategy started
Getting Started with the Right Foundation
Big Data as a Business Planning Tool
Developing a Well-Governed and Secure Big Data Environment
Setting the right governance and quality policies
Preparing for stewardship and management of risk
Putting the Right Organizational Structure in Place
Identifying the key stakeholders
Auditing your big data process
The Data Governance Challenge
Understanding Data Protection Options
Risks lurking inside big data
Assessing the risk for the business
Security in Context with Big Data
Starting Your Big Data Road Map
Selecting the right software development methodology
Determining your appetite for risk
Balancing budgets and skill sets
Projecting the right amount of capacity
Understanding business urgency
Creating a Big Data Implementation Road Map
Defning Enterprise Data Management
Enterprise Data Management and Big Data
Calculating the return on investment (ROI) from big data investments
Finding the talent to support big data projects
Business process modifcations or new process creation
The technology impact of big data workflows
Identifcation of data types and sources
Figuring the Economics of Big Data
The Cloud Security Alliance
National Institute of Standards and Technology
Apache Software Foundation
OASIS
Online Collaborative Sites
Big Data Conferences
Do Involve All Business Units in Your Big Data Strategy
Do Evaluate All Delivery Models for Big Data
Do Think about Your Traditional Data Sources as Part of Your Big Data Strategy
Do Plan for Consistent Metadata
Do Distribute Your Data
Don’t Rely on a Single Approach to Big Data Analytics
Don’t Go Big Before You Are Ready
Don’t Overlook the Need to Integrate Data
Don’t Forget to Manage Data Securely
Don’t Overlook the Need to Manage the Performance of Your Data
Making Big Data a Part of Your Operational Process
Integrating big data
Incorporating big data into the diagnosis of diseases
Understanding Big Data Workflows
Workload in context to the business problem
Ensuring the Validity, Veracity, and Volatility of Big Data
Data validity
Data volatility
Understanding the Impact of Streaming Data and CEP on Business
Differentiating CEP from Streams
Using Complex Event Processing
The need for metadata in stream
s
Data streaming
Explaining Streaming Data and Complex Event Processing
Using Streaming Data
Best Practices for Data Integration in a Big Data World
Using Hadoop as ETL
Prioritizing Big Data Quality
Data transformation
Understanding the Fundamentals of Big Data Integration
Defning Traditional ETL
Understanding ELT — Extract, Load, and Transform
Integration and incorporation stage
Codifying stage
Exploratory stage
Identifying the Data You Need
Big to Small: A Big Data Paradox
Characteristics of a Big Data Analysis Framework
Semi-custom applications for big data analysis
Custom applications for big data analysis
Understanding Different Approaches to Big Data Analysis
Characteristics of big data analysis
Building New Models and Approaches to Support Big Data
Clarabridge
Attensity
Text Analytics Tools for Big Data
Social media analytics
Voice of the customer
Putting Big Data to Use
Putting Your Results Together with Structured Data
Taxonomies
Understanding the extracted information
Analysis and Extraction Techniques
The difference between text analytics and search
Understanding Text Analytics
Exploring Unstructured Data
Operationalized analytics
Monetizing analytics
Advanced analytics
Basic analytics
sing Big Data to Get Results
Monetizing analytics
Operationalized analytics
Advanced analytics
Basic analytics
sing Big Data to Get Results
Examining the Future of Data Warehouses
The cloud model
The appliance model
Changing Deployment Models in the Big Data Era
Changing the Role of the Data Warehouse
Rethinking extraction, transformation, and loading
The integration lynchpin
Big Data Analysis and the Data Warehouse
Examining a hybrid process case study
Differentiating big data structures from data warehouse data
Optimizing the data warehouse
Integrating Big Data with the Traditional Data Warehouse
Zookeeper
Sqoop
Pig and Pig Latin
Interacting with the Hadoop Ecosystem
Mining Big Data with Hive
Storing Big Data with HBase
Managing Resources and Applications with Hadoop YARN
Building a Big Data Foundation with the Hadoop Ecosystem
Reduce and combine
Let the mapping begin
Getting the data ready
Hadoop MapReduce
Under the covers of HDFS
Data nodes
NameNodes
Understanding the Hadoop Distributed File System (HDFS)
Explaining Hadoop
Synchronization
Hardware/network topology
Optimizing MapReduce Tasks
Putting map and reduce Together
Adding the reduce Function
Understanding the map Function
Tracing the Origins of MapReduce
Polyglot Persistence
PostGIS/OpenGEO Suite
Spatial Databases
Neo4J graph database
Graph Databases
HBase columnar database
Columnar Databases
CouchDB
MongoDB
Document Databases
Riak key-value database
Key-Value Pair Databases
Nonrelational Databases
PostgreSQL relational database
RDBMSs Are Important in a Big Data Environment
Where to be careful when using cloud services
OpenStack
Microsoft Azure
Google big data services
Amazon’s Public Elastic Compute Cloud
Providers in the Big Data Cloud Market
Making Use of the Cloud for Big Data
The Cloud as an Imperative for Big Data
Cloud delivery models
Cloud deployment models
Understanding Cloud Deployment and Delivery Models
Defning the Cloud in the Context of Big Data
Implementing Virtualization to Work with Big Data
Abstraction and Virtualization
Managing Virtualization with the Hypervisor
Data and storage virtualization
Processor and memory virtualization
Network virtualization
Application virtualization
Server virtualization
The importance of virtualization to big data
Understanding the Basics of Virtualization
Big Data Applications
Big Data Analytics
Layer 4: Analytical Data Warehouses
Layer 3: Organizing Data Services and Tools
Layer 2: Operational Databases
Interfaces and Feeds to and from Applications and the Internet
Layer 1: Security Infrastructure
Infrastructure operations
Managing hardware: Storage and servers
Physical redundant networks
Layer 0: Redundant Physical Infrastructure
Exploring the Big Data Stack
Getting Performance Right
Demand meets solutions
The problem with latency
The changing economics of computing
Why we need distributed computing for big data
Understanding the Basics of Distributed Computing
The value of a consistent model
Giving thanks to DARPA
A Brief History of Distributed Computing
Integrating data types into a big data environment
Managing different data types
Putting Big Data Together
Looking at Real-Time and Non-Real-Time Requirements
Understanding the role of a CMS in big data management
Exploring sources of unstructured data
Defning Unstructured Data
Understanding the role of relational databases in big data
Understanding the role of relational databases in big data
Exploring sources of big structured data
Defning Structured Data
The Big Data Journey
Traditional and advanced analytics
Performance matters
Setting the architectural foundation
Beginning with capture, organize, integrate, analyze, and act
Building a Successful Big Data Management Architecture
Defning Big Data
Managing big data
Web and content management
Creating manageable data structures
Understanding the Waves of Managing Data
The Evolution of Data Management
The Part of Tens
The Evolution of Data Management
Big Data Solutions in the Real World
Big Data Implementation
Analytics and Big Data
Big Data Management
Technology Foundations for Big Data
Getting Started with Big Data
Ten Great Big Data Resources
Improving Business Processes with Big Data Analytics
Ten Big Data Do’s and Don’ts
Ten Big Data Best Practices
Analyzing Data in Motion: A Real-World View
The Importance of Big Data to Business
Big Data Solutions in the Real World
Security and Governance for Big Data Environments
Applying Big Data within Your Organization
Operationalizing Big Data
Dealing with Real-Time Data Streams and Complex
Event Processing
Integrating Data Sources
Big Data Implementation
Customized Approaches for Analysis of Big Data
Understanding Text Analytics and Big Data
Defning Big Data Analytics
Appliances and Big Data Warehouses
Analytics and Big Data
The Hadoop Foundation and Ecosystem
Exploring the World of Hadoop
Map Reduce Fundamentals
Operational Databases
Big Data Management
Examining the Cloud and Big Data
Virtualization and How It Supports Distributed Computing
Digging into Big Data Technology Components
Technology Foundations for Big Data
Distributed Computing
Examining Big Data Types
Grasping the Fundamentals of Big Data
Getting Started with Big Data
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