Objective of this training
Developing the skills of participants in the field of big data, dealing with it and analyzing it by providing them with knowledge, experiences, trends and skills that raise the level of their performance through the development of efficiency and production effectiveness in this field.

Targets of this training
 Changing the cultures of employees in institutions towards the importance of this data and that it is a source of support and strength for the institution towards excellence and increasing loyalty and satisfaction for customers
 Understand this big data, its generators, how to deal with it, its benefits and limitations
 Tracking what serves the institution and adds value to it and how to build work teams in this field
 Working to find means of analysis for this growing accumulated amount of data to serve the rationalization of the administrative decision
 How to use it in strategic planning and organizational excellence
 Practical applications on how to link and infer relationships and how to build analytical models
 Using free apps and getting to know Hadoop
 Transforming thinking from traditional to creative by finding relationships and causes between these data to provide information that serves the organization towards excellence
 Shifting from short-term, limited thinking to long-term strategic thinking
 Making institutional excellence a value and a culture that lives inside us and we strive for it with all our work

 Directors of senior departments, executives, managers and heads of departments concerned with making decisions
 Supervisors and employees responsible for handling and analyzing data
 Participants who work in dealing with data
 Managers and employees of the technical offices of the leaders of companies and institutions
 Working groups for decision-making and technical studies
 Lecturers or trainers who wish to develop their skills in this field
 Workers in the field of information technology
 All those interested and willing to develop the skills of dealing with big data

Course outline
Big data
• Data
• Measuring the volume of data
• Evolution of data volume
• Big data
(ISO definition - ITU definition - IBM definition - General definition - Big Data science)
• Big data sources
• Types of Big Data
(Structured - Unstructured - Semi-structured)
• Characteristics of Big Data
(3V's – 4V's – 5V's – 10V's)
• Data processing systems
(Sequential - parallel - distributed)
• Big data processing mechanism
• Benefits of Big Data
• The importance of big data
• Big data users
• Big Data Science Applications
• Big Data Challenges
Big data analytics tools
• Big data analysis
• Hadoop
• HPCC
• Storm
• Tableau
• KNIME
• RapidMiner
Hadoop Big Data Platform
• Introduction to Hadoop
• Hadoop's goals
• Advantages of Hadoop
• Hadoop's style of work
• Hadoop Framework Tools
• Hadoop style
• The main components of Hadoop
• Uses of Hadoop
• Hadoop Apps
Pivot tables
• Practical steps for creating and using pivot tables
• Applications to the uses of pivot tables
• Dealing with data through pivot tables
• Pivot table capabilities
• Graphic Display Dash Board
• Display pivot table data through graphical display
Tableau introduction
• Data visualization
• Charts types
(Comparison – Composition – Distribution - Relationship)
• What is Tableau
• Tableau visualization examples
• Tableau introduction
Practical sessions
• Building and using Pivot tables using big data files
• Extracting results and analysis using pivot tables
• Visualizing pivot tables data
• Using Tableau Software
• Introducing Tableau features
• Extracting results and analysis using Tableau
• Training course attendees on using Tableau (Hands on training)
• Discussing use cases for course attendees

Pre and Port Exams are included