Enroll in the program and start a new professional path studying the Analytical Techniques used in the Technology Sector” 

Nowadays there is no doubt that the IT Project Management and Control is a complex process that involves Measurements, Parameters and Analytical Techniques that will guarantee decisions taken are correctly grounded. Thanks to this, not only the performance of the company will be improved, but possible problems will also be anticipated.  

For this reason, this Postgraduate Diploma will instruct students in the world of project management and control, using business intelligence techniques. Thus, a vision of industry applications will be developed to elaborate Promotions, Planning, Financial Controls, Cost Optimization and Sales Trend Analysis.

In another sense, Strategic Decision Making must be based on the use of tools, technologies and methods that allow for well-founded actions.  In view of this need, the program includes a module focused on Data and Information Analysis, where Data Life Cycle will be examined within the scope of Business Intelligence, from its origins to its transformation as a valuable asset for a company. 

Finally, digital analytics will be addressed, a discipline that studies marketing actions in detail to interpret results in order to make the best decisions for the business. In this way, data related to users visiting a website or digital platform will be collected and then processed for analysis using Google Analytics as a central tool.  

With all this knowledge, students will be able to manage with greater skill any kind of IT Project, knowing which work methodology to use at any given moment and being able to solve internal work team problems.

Develop change strategies and practices for digital business transformation through the advanced application of Analytical Techniques”

This Postgraduate diploma in IT Project Control Using Analytical Techniques contains the most complete and updated educational program on the market. Its most notable features are:

• Analysis of everything involved in the Management and Direction of an IT Project, both in a productive and human sense 
• Specific knowledge in the field of Team Management, with Innovative Methodologies adapted to New Technological Realities 
• Extensive audiovisual content throughout the learning process, which makes study work easier and more enjoyable 
• Content that is accessible from any fixed or portable device with an Internet connection 

Analyze the differences between different data warehousing paradigms: Data Lake,  Data Warehouse and Data Mart”

The program’s teaching staff includes professionals in the sector who contribute their work experience to this training program, as well as renowned specialists from leading societies and prestigious universities.  

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive training programmed to train in real situations.  

This program is designed around Problem Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts. 

Take the challenge, enroll in this Postgraduate diploma and learn how to generate reports using Google Analytics"

In this program you will understand how to perform an intelligent business assessment, taking your skills to the next level"

The content structure of this program will help students to use the methodologies and tools to develop specialized knowledge in the application of Business Intelligence Techniques for Project Management and Control. They will be able to lead a team effectively, as well as communicate the analysis results to company managers. Thanks to all this, they will be able to opt for new job offers both nationally and internationally.   

Find out everything that awaits you in this Postgraduate diploma by enrolling now. Don't miss the opportunity to grow in the professional world” 

Module 1. IT Project Management and Control Using Business Intelligence 

1.1. Business Intelligence 

1.1.1. Business Intelligence 
1.1.2. Data Management 
1.1.3. Data Life Cycle 
1.1.4. Architecture 
1.1.5. Applications  

1.2. IT Projects Management Using Analytical Techniques

1.2.1. Business Intelligence Selection 
1.2.2. Benefits of Business Intelligence for Projects 
1.2.3. Examples and Applications

1.3. Harvesting and Storage

1.3.1. Business Models and Data Models 
1.3.2. Types of Storage 
1.3.3. Storing Big Data in the Cloud 

1.4. Massive Data and Information Processing 

1.4.1. Types of Database Processing 
1.4.2. Techniques to Simplify Massive Processing 
1.4.3. Cloud Processing 

1.5. Analytical Techniques 

1.5.1. Analytical Techniques 
1.5.2. Predictive Analyses 
1.5.3. Pattern Analysis and Recommendation 
1.5.4. Scalable Machine Learning 

1.6. Visualization for Decision-Making 

1.6.1. Visualization and Data Analysis 
1.6.2. Tools 
1.6.3. Data Analysis Visualization 
1.6.4. Reports Design 

1.7. Business Information Consumption 

1.7.1. Control Panel 
1.7.2. KPI Design and Extraction 
1.7.3. Geographic Information 

1.8. Security and Governance 

1.8.1. Security/safety 
1.8.2. Governance 

1.9. Real Applications to IT Projects 

1.9.1. From Harvesting to Processing 
1.9.2. From Analysis to Visualization 

1.10. Project Management 

1.10.1. Project 
1.10.2. Requirements and Objectives 
1.10.3. Start-up and Implementation

Module 2. Strategic Monitoring and Control of IT Projects  

2.1. Data and Information in Decision-Making and Project Management 

2.1.1. Business Intelligence 
2.1.2. Business Intelligence Concept Evolution 
2.1.3. Data Life Cycle 

2.2. Information Analysis Techniques 

2.2.1. Descriptive Analytics 
2.2.2. Prescriptive Analytics 
2.2.3. Predivtive Analytics 
2.2.4. Pattern Analysis and Recommendation 
2.2.5. Benefits of Computer Projects Analysis 

2.3. Types of Data 

2.3.1. Structured Data 
2.3.2. Semi-Structured Data 
2.3.3. Unstructured Data 

2.4. Storage and Management 

2.4.1. Data Lake,  Data Warehouse and Data Mart 
2.4.2. Stages in Data Management: Extraction, Transformation and Loading 
2.4.3. ETL and ELT Paradigm 

2.5. Data Management for Project Implementation 

2.5.1. Data Use in Project Design 
2.5.2. Decision Making 
2.5.3. Benefits 

2.6. Business Intelligence Solutions: Power BI 

2.6.1. Ecosystem 
2.6.2. Potential Strengths and Weaknesses 

2.7. Business Intelligence Solutions: Tableau 

2.7.1. Ecosystem 
2.7.2. Strengths and Weaknesses 

2.8. Business Intelligence Solutions: Qlik 

2.8.1. Ecosystem 
2.8.2. Potential Strengths and Weaknesses 

2.9. Business Intelligence Solutions: Prometeus 

2.9.1. Ecosystem 
2.9.2. Potential Strengths and Weaknesses 

2.10.     Future of Business Intelligence 

2.10.1. Cloud Applications 
2.10.2. Self-consumption Business Intelligence 
2.10.3. Integration with Data Science: Value Creation 

Module 3. Digital Analytics for Decision Making in Technology Projects 

3.1. Digital Analytics 

3.1.1. Digital Analytics 
3.1.2. Modus Operandi 

3.2. Google Analytics: Analysis Tools 

3.2.1. Google Analytics 
3.2.2. Quantifying and Qualifying: Metrics and Dimensions 
3.2.3. Analysis Objectives 

3.3. Metrics 

3.3.1. Basic Metrics 
3.3.2. KPI (Key Performance Indicators) or Advanced Metrics 
3.3.3. Objetive: Conversion 

3.4. Dimensions 

3.4.1. Campaign/Keyword 
3.4.2. Source/Media 
3.4.3. Contents 

3.5. Google Analytics 

3.5.1. Tool Set-up and Configuration 
3.5.2. Current Versions: UA/GA4 
3.5.3. Conversion Objectives: Conversion Funnels 

3.6. Google Analytics Structure: Work Areas 

3.6.1. Accounts 
3.6.2. Properties 
3.6.3. Views 

3.7. Google Analytics Reports 

3.7.1. In Real Time 
3.7.2. Audience 
3.7.3. Acquisition 
3.7.4. Behaviour 
3.7.5. Conversions 

3.8. Advanced Reports Using Google Analytics 

3.8.1. Personalized Reports 
3.8.2. Panels 
3.8.3. API 

3.9. Filtering 

3.9.1. Filtering and Segmentation: Usability 
3.9.2. Predefined Segments and Personalized Segments 
3.9.3. Remarketing Lists 

3.10. Digital Analytics Plan 

3.10.1. Measurement 
3.10.2. Implementation in the Technological Environment 
3.10.3. Conclusions 

Do not stop advancing in your projects. Communicate and elaborate business models that generate a positive change in the company”