000			05496nam a2200253 a 4500
003			AR-LpUFIB
005			20250311170443.0
008			230201s2016 xxua r 000 0 eng d
020			_a9780134291079
024	8		_aDIF-M7424 _b7641 _zDIF006791
040			_aAR-LpUFIB _bspa _cAR-LpUFIB
100	1		_aErl, Thomas
245	1	0	_aBig data fundamentals : _bconcepts, drivers & techniques
250			_a1st ed.
260			_aIndiana : _b Prentice Hall, _c2016
300			_axv, 218 p. : _bil.
500			_aIncluye índice
505	0		_a PART I: THE FUNDAMENTALS OF BIG DATA -- CHAPTER 1: Understanding Big Data -- Concepts and Terminology -- Datasets -- Data Analysis -- Data Analytics -- Descriptive Analytics -- Diagnostic Analytics -- Predictive Analytics -- Prescriptive Analytics -- Business Intelligence (BI) -- Key Performance Indicators (KPI) -- Big Data Characteristics -- Volume -- Velocity -- Variety -- Veracity -- Value -- Different Types of Data -- Structured Data -- Unstructured Data -- Semi-structured Data -- Metadata -- Case Study Background -- History Technical -- Infrastructure and Automation Environment -- Business Goals and Obstacles -- Case Study Example -- Identifying Data Characteristics -- Volume Velocity -- Variety -- Veracity -- Value -- Identifying Types of Data -- CHAPTER 2: Business Motivations and Drivers for Big Data Adoption -- Marketplace Dynamics -- Business Architecture -- Business Process Management -- Information and Communications Technology -- Data Analytics and Data Science -- Digitization -- Affordable Technology and Commodity Hardware -- Social Media -- Hyper-Connected Communities and Devices -- Cloud Computing -- Internet of Everything (IoE) -- -- Case Study Example -- CHAPTER 3: Big Data Adoption and Planning Considerations -- Organization Prerequisites -- Data Procurement -- Privacy -- Security -- Provenance -- Limited Realtime Support -- Distinct Performance Challenges -- Distinct Governance Requirements -- Distinct Methodology -- Clouds -- Big Data Analytics Lifecycle -- Business Case Evaluation -- Data Identification -- Data Acquisition and Filtering -- Data Validation and Cleansing -- Data Aggregation and Representation -- Data Analysis Data Visualization -- Utilization of Analysis Results -- Case Study Example -- Big Data Analytics Lifecycle -- Business Case Evaluation -- Data Identification -- Data Acquisition and Filtering -- Data Extraction -- Data Validation and Cleansing -- Data Aggregation and Representation -- Data Analysis -- Data Visualization -- Utilization of Analysis Results. -- CHAPTER 4: Enterprise Technologies and Big Data Business Intelligence -- Online Transaction Processing (OLTP) -- Online Analytical Processing (OLAP) -- Extract Transform Load (ETL) -- Data Warehouses -- Data Marts Traditional BI -- Ad-hoc Reports -- Dashboards -- Big Data BI -- Traditional Data Visualization -- Data Visualization for Big Data -- Case Study Example -- Enterprise Technology -- Big Data Business Intelligence -- PART II: STORING AND ANALYZING BIG DATA -- CHAPTER 5: Big Data Storage Concepts -- Clusters -- File Systems and Distributed File Systems -- NoSQL -- Sharding -- Replication -- Master-Slave -- Peer-to-Peer -- Sharding and Replication -- Combining Sharding and Master-Slave Replication -- Combining Sharding and Peer-to-Peer Replication -- CAP Theore -- ACID -- BASE -- Case Study Example -- CHAPTER 6: Big Data Processing Concepts -- Parallel Data Processing -- Distributed Data Processing -- Hadoop -- Processing Workloads -- Batch -- Transactional -- Cluster -- Processing in Batch Mode -- Batch Processing with -- MapReduce Map and Reduce Tasks -- Map -- Combine -- Partition -- Shuffle and Sort -- Reduce -- A Simple MapReduce Example -- Understanding MapReduce Algorithms -- Processing in Realtime Mode -- Speed Consistency Volume (SCV) -- Event Stream Processing -- Complex Event Processing -- Realtime Big Data Processing and SCV -- Realtime Big Data Processing and MapReduce -- Case Study Example -- Processing Workloads -- Processing in Batch Mode -- Processing in Realtime -- CHAPTER 7: Big Data Storage Technology -- On-Disk Storage Devices -- Distributed File Systems -- RDBMS Databases -- NoSQL Databases -- Characteristics -- Rationale -- Types -- Key-Value -- Document -- Column-Family -- Graph -- NewSQL Databases -- In-Memory Storage Devices -- In-Memory Data Grids -- Read-through -- Write-through -- Write-behind -- Refresh-ahead -- In-Memory Databases -- Case Study Example -- CHAPTER 8: Big Data Analysis Techniques -- Quantitative Analysis -- Qualitative Analysis -- Data Mining -- Statistical Analysis -- A/B Testing -- Correlation -- Regression -- Machine Learning -- Classification (Supervised Machine Learning) -- Clustering (Unsupervised Machine Learning) -- Outlier Detection -- Filtering -- Semantic Analysis -- Natural Language Processing -- Text Analytics -- Sentiment Analysis -- Visual Analysis -- Heat Maps -- Time Series Plots -- Network Graphs -- Spatial Data Mapping -- Case Study Example -- Correlation -- Regression -- Time Series Plot -- Clustering -- Classification -- APPENDIX A: Case Study Conclusion -- About the Authors -- Thomas Erl -- Wajid Khattak -- Paul Buhler -- Index
650		4	_aBIG DATA
650		4	_aPROCESAMIENTO DE DATOS
700	1		_aKhattak, Wajid
700	1		_aBuhler, Paul
942			_cBK
999			_c56567 _d56567