Big Data Analytics. Concepts and Tools

Length: 260 pages
Edition: 1
Language: English
Publisher: lulu.com
Publication Date: 2021-03-20
ISBN-10: B093X5SKSM
ISBN-13: 9781008984530
Sales Rank: #0 (See Top 100 Books)

Today’s data analysis requires the use of statistical techniques to learn from data, highlight patterns and anomalies, predictions and professionals who know how to use them. The use of Big Data technologies not only allows us to increase processing capacity, it is also about finding those ideas that allow us to obtain the knowledge embedded in the data, as long as we have the profiles and experience to carry it out.

For this reason, Analytics techniques (essentially Data Mining and Business Intelligence) and Big Data go hand in hand for the optimal exploitation of information. Professionals, with skills in mathematics, statistics and computer engineering, who are able to extract the maximum value from the organisation’s data through Analytics, must work together with optimal Big Data infrastructures. The management and analysis of big data, structured and unstructured, applied in fields such as scientific research, health, security, social networks or media, among others, is a unique tool for companies to gain competitiveness and improve the life of citizens. This tool can only be optimised with the combined application of Analytics and Big Data techniques.

ANALYTICS, DATA MINING, BUSINESS INTELLIGENCE and BIG DATA
1.1 INTRODUCTION
1.2 MODERN DATA PROCESSING TECHNIQUES: ANALYTICS
1.3 ANALYTICS AND DATA MINING TECHNIQUES
1.4 ANALYTICS AND BUSINESS INTELLIGENCE
1.5 BIG DATA AND HADOOP
INTRODUCTION TO SAS VISUAL ANALYTICS. WORKING ENVIRONMENT
2.1 Visual Analytics
2.2 Benefits of SAS Visual Analytics
2.3 The SAS Visual Analytics WORKING ENVIRONMENT
2.4 Access to SAS Visual Analytics
2.4.1 Authenticated Users
2.4.2 Guest access
2.5 About menu availability and menu selections in SAS Visual Analytics
2.6 First look at the SAS Visual Analytics START PAGE
2.7 Content Management on the home page
2.8 Working with the right-hand panel on the homepage
2.8.1 About the Right-hand Panel
2.8.2 Hide Content in the Right-hand Pane
2.8.3 Displaying Content in the Right-hand Pane
2.8.4 Manage Links in the Right Hand Panel
2.9 EXPLORING DATA uSing the Object Inspector on the home page
2.10 Collection management on the home page
2.11 Adding Comments to objects on the home page
2.12 Specifying Your Preferences
2.12.1 Specifying global preferences
2.12.2 Specifying general SAS Visual Analytics preferences
2.12.3 Specifying your preferred home screen
2.13 data access
2.14 Administering Data Access
2.15 SAS VISUAL ANALYTICS EXPLORER
2.15.1 The welcome window
2.15.2 First look at the Browser
VISUALISATIONS IN SAS VISUAL ANALYTICS
3.1 INTRODUCTION TO VISUALISATIONS
3.1.1 About visualisations
3.1.2 Types of visualisations
3.2 WORKING WITH VISUALISATIONS
3.2.1 Creating a new visualisation
3.2.2 Managing visualisations
3.2.3 Arranging visualisations in the workspace
3.2.4 Using the Visualisation Manager window
3.3 MANAGING DATA IN VISUALISATIONS
3.3.1 Adding a data element to the visualisation
3.3.2 Replacing a data element
3.3.3 Removing data elements
3.3.4 Changing roles of data elements
3.4 Ranking OF DATA
3.4.1 Introduction
3.4.2 Creating a new range
3.4.3 Deleting a range
3.5 Managing visualisation axes
3.5.1 Locking an axle
3.5.2 Setting axes
3.5.3 Transferring the Axis Configuration
3.6 Working with data display ranges and Colour gradients
3.6.1 Support for custom data ranges and Colour gradients
3.6.2 Specifying a custom colour gradient
3.6.3 Specifying a custom data range
3.6.4 Sharing a Colour gradient and a range of data between visualisations
3.6.5 Removing personalised or shared data ranges
3.7 WORKING WITH HIGHLIGHTED DATA
3.7.1 Introduction to highlight data
3.7.2 Enable data highlighting
3.7.3 Selecting values in a visualisation
3.8 WORKING WITH AUTOMATIC GRAPHICS
3.9 WORKING WITH BAR CHARTS
3.9.1 About bar charts
3.9.2 Data roles for a bar chart
3.9.3 Specifying the properties of a bar chart
3.9.4 Sorting of data values
3.10 WORKING WITH LINE CHARTS
3.10.1 About line charts
3.10.2 Data roles for a line chart
3.10.3 Specifying Line Chart Properties
3.10.4 Sorting data values
3.11 FORECASTING
3.11.1 On prediction
3.11.2 Enabling prediction
3.12 WORKING WITH TABLES
3.12.1 About the Tables
3.12.2 Data Roles for a Table
3.12.3 Specifying table properties
3.12.4 Column Management
3.13 WORKING WITH CROSS TABLES
3.13.1 About Cross Tables
3.13.2 Data Roles for a cross-reference table
3.13.3 Specifying Properties of a cross-reference table
3.14 WORKING WITH SCATTER PLOTS
3.14.1 About Scatter plots
3.14.2 Data roles for a scatter plot
3.14.3 Specifying the properties of a scatterplot
3.15 APPLYING DATA ANALYSIS
3.15.1 About Data Analysis
3.15.2 Enable Data Analysis
3.16 Working with Bubble GRAPHICS
3.16.1 About Bubble Charts
3.16.2 Data roles for a bubble chart
3.16.3 Specifying the properties of a bubble chart
3.16.4 Using animation in bubble charts
3.17 Working with NETWORK diagrams
3.17.1 About Network Diagrams
3.17.2 Data roles for a network diagram
3.17.3 Specifying the properties of a network diagram
3.17.4 Selecting nodes in a network diagram
3.17.5 Controlling the view of a network diagram
3.18 Working with histograms
3.18.1 About Histograms
3.18.2 Data roles for a histogram
3.18.3 Specifying Properties of a histogram
3.19 Working with BOX CHARTS AND BIGOTS
3.19.1 About box-and-whisker charts
3.19.2 Data roles for a box-and-whisker diagram
3.19.3 Specifying the properties of a box and whisker chart
3.20 Working with HEAT maps
3.20.1 About Heat Maps
3.20.2 Data roles for a heat map
3.20.3 Specifying Heatmap Properties
3.20.4 Applying Data Analysis
3.21 Working with GEOGRAPHIC MAPS (Geo maps)
3.21.1 About Geo Maps
3.21.2 Data roles for a geo map
3.21.3 Specifying the properties of a Geo map
3.21.4 Zooming on a Geo Map
3.21.5 Moving a Geo Map
3.22 Working with MOSAIC GRAPHICS (Treemaps)
3.22.1 About Tile Charts
3.22.2 Roles for data in a mosaic graph
3.22.3 Specifying Properties of a Tile Chart
3.22.4 Creating a tile map hierarchy
3.23 Working with Correlation Matrices
3.23.1 About correlation matrices
3.23.2 Data Roles for a Decorrelation Matrix
3.23.3 Specifying the properties of a correlation matrix
3.23.4 Type of values for a correlation matrix
3.24 Working with decision trees
3.24.1 About Decision Trees
3.24.2 Roles of data in a decision tree
3.24.3 Specifying the properties of a decision tree
3.24.4 Browsing a node as a new view
3.24.5 Calculating a decision tree data element
3.24.6 Displaying a Summary
3.24.7 Zooming in on a tree
3.25 Working with WORD clouds
3.25.1 About word clouds
3.25.2 Data papers for a word cloud
3.25.3 Specifying the properties of a word cloud
DATA ANALYSIS AND REPORTING WITH SAS VISUAL ANALYTICS
3.26 Data analysis overview in SAS Visual Analytics Explorer
3.26.1 Types of data analysis
3.26.2 Correlation
3.26.3 Adjustment Lines
3.26.4 Forecasts
3.26.5 Adding an adjustment line to the current display
3.26.6 Add Forecast for current display
3.26.7 Forecast Measures as a new visualisation
3.26.8 Applying Scenario Analysis for a Forecast
3.27 REPORTS. SAS VISUAL ANALYTICS DESIGNER
3.27.1 SAS Visual Analytics Graph Builder
3.27.2 SAS Visual Analytics Viewer
3.28 Mobile Business Intelligence
SAS VISUAL STATISTICS
4.1 INTRODUCTION
4.2 START-UP AND WORKING ENVIRONMENT
4.3 USER INTERFACE
4.3.1 Menus and toolbars
4.3.2 Data panel
4.3.1 Right-hand panel
4.3.1 Model panel
4.4 LINEAR MULTIPLE REGRESSION MODEL
4.5 LOGISTIC REGRESSION MODEL
4.6 GENERALISED LINEAR MODEL
4.7 DECISION TREES
4.8 CLUSTER ANALYSIS
4.9 COMPARISON OF MODELS
SAS HADOOP SOLUTIONS. SAS HIGH PERFORMANCE ANALYTICS AND SAS IN-MEMORY STATISTICS
5.1 INTRODUCTION
5.2 SAS HIGH-PERFORMANCE ANALYTICS
5.3 SAS High-Performance Statistics
5.3.1 Characteristics
5.4 High-Performance Optimisation
5.4.1 Characteristics
5.5 SAS IN-MEMORY STATISTICS FOR HADOOP
5.5.1 Characteristics
ANALYTICS WITH IBM TOOLS
6.1 INTRODUCTION
6.2 ANALYTICS WITH POWER SYSTEM
6.2.1 IBM Solution for Hadoop Power Systems Edition
6.2.2 IBM Solution for Analytics Power Systems Edition
6.2.3 IBM BLU Acceleration Solution Power Systems Edition
6.2.4 IBM AIX Solution Editions for Cognos and SPSS
6.2.5 IBM PureData System for Operational Analytics
6.2.6 Big Data solution with InfoSphere BigInsights and Streams
6.3 IBM SPSS MODELER
6.4 DATA SOURCE NODES
6.5 RECORD OPERATION NODES
6.6 FIELD OPERATION NODES
6.7 NODES FOR GRAPHS
6.8 NODES FOR MODELLING
6.9 RESULT NODES
6.10 EXPORT NODES
ANALYTICS WITH ORACLE TOOLS
7.1 INTRODUCTION
7.2 Oracle Business Analytics
7.3 Oracle Business Intelligence Foundation Suite
7.4 Enterprise Performance Management
7.5 Analytical applications
7.5.1 Analytical applications by commercial role
7.5.2 Analytical applications by sector
7.5.3 Analytical Applications by Product Line
7.6 Information Discovery
7.7 Advanced Analytics
7.8 Cloud