TDWI Analytics Fundamentals, Germany

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Analytics is a hot topic, but also a complex topic. This continuously growing field now includes descriptive, diagnostic, predictive, and prescriptive analytics. Applied analytics including optimization, simulation, and automation expand the scope. Data growth also fuels the complexity – unstructured data, big data, social data, data streams, and more. Advanced analytics continues to expand with complex event processing, machine learning, cognitive computing, etc.

In the growing and evolving world of analytics we’re also experiencing a shift of roles and responsibilities. The “data things” that were once seen as IT responsibilities have become critical business skills. Analytics spans a continuum that encompasses IT departments, data scientists, data analysts, business analysts, business managers, and business leadership. It seems that everyone has a stake in analytics. Coordination, cross-functional analysis, data sharing, and governance all become important skills.

There are no prerequisites for this course.

Business leaders and managers seeking to understand business dynamics through analytics
IT leaders and managers responsible to deliver and to support analytics initiatives
BI and analytics architects guiding the design, development, and deployment of analytics
BI and analytics designers and developers
Business analysts, data analysts, data scientists and those who aspire to these roles

The concepts and practices of analytic modeling
An analytics topology to make sense of the variety of analytic types and techniques
The data side of analytics including data sourcing, data discovery, data cleansing, and data preparation
Analytic techniques for exploration, experimentation, and discovery
The human side of analytics: communication, conversation, and collaboration
The organizational side of analytics: self-service, central services, governance, etc.
A bit about emerging techniques and technologies shaping the future of analytics

Module One: Concepts of Analytics

Analytics Defined
Data Analytics and Business Analytics
- Variations of Purpose
- Variations of Skills
Why Analytics
- Cause and Effect
- Strategy and Analytics
- Tactics and Analytics
- Operations and Analytics
- Systemic Analytics
Analytics Processes
- Problem Framing
- Problem Modeling
- Solution Modeling
- Visualization and Presentation
- Understanding and Action
Analytics Foundations
Data
- Scope of Data
- Finding Data
- Observations and Populations
- Raw Data vs. Summary Data
- Data Preparation
Statistics
- Histograms
- Distribution and Deviation
- Correlation
- Regression
Visualization
- Visual Design
- Choosing Charts and Graphs
Business Impact
- Simulation
- Optimization
- Automation

Module Two: The Analytics Environment

Analytics Stakeholders
The Participants
- Business Stakeholders
- Analytic Modelers and Data Scientists
- IT and Data Organizations
Analytic Culture
Values, Beliefs, and Competencies
- Numeracy
- Collaboration
- Conversation
- Decision Styles
Analytics Organizations
Organization Models
- Self Service
- Shared Services
- Central Services
- Hybrid Organizations
Analytics and Governance
Analytics Capabilities
Business Capabilities
- Planning
- Executing
- Adapting
- Innovating
Analysis Capabilities
- Evaluating
- Detecting
- Predicting
- Classifying
- Recommending
- Monitoring
Data Capabilities
- Measuring
- Searching and Acquiring
- Blending and Integrating
- Securing
- Provisioning
A Capability-Based Framework
- Discovery Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics

Module Three: Analytics Architecture

The Big Picture
Data Architecture
- Data Sources and Types
- Data Acquisition
- Data Ingestion
- Persistence
- Data Management Topology
- Data Quality and Utility
- Data Usage / Information Delivery
Process Architecture
Next Generation BI
- Extending BI
Basic Data Analysis
- Statistical Analysis
- Time-Series Analysis
Discovery and Prediction
- Data Mining
- Predictive Modeling
- Ensemble Modeling
Text and Language Analysis
- Natural Language Processing
- Text Mining o People and Behaviors
- Sentiment Analysis
- Behavioral Analytics
People and Social Media
- Social Network Analysis
- Social Media Analytics
Events and Data Streams
- Stream Processing
- Complex Event Processing
Smart Machines
- Machine Learning
- Cognitive Computing
Technology Architecture
Connectivity
- SQL
- Messaging
- Services
- Replication
- Virtualization
Data Stores
- RDBMS
- Columnar
- MPP
- MDDB
- NoSQL
- In Memory
Data Analysis
- Data Mining
- Analytic Modeling
- Big Data Analytics
- Streaming Analytics
- Event Processing
- Machine Learning etc.
Data Flow
- Batch
- Real-time
- Streams
Management
- Workflow
- Service Levels
Platforms
- Servers
- Appliances
- Cloud

Module Four: Analytic Modeling

The Roles of Models
- Understanding the Problem Space
- Understanding the Data
- Understanding the Language
- Understanding the Business Dynamics
Kinds of Models
- Framing Models
- Questioning
- Kernel Seeking
Cause-Effect Models
- Influence Models
- Causal Loop Models
Data Models
- Physical Models
- Logical Models
- Conceptual Models
Language Models
- Ontology
- Taxonomy
- Lexicon
- Semantics
Solution Models
- Formula Based
- Algorithm Based
Problem Modeling
- Framing the Problem
- Influence Diagramming
- Causal Modeling
Solution Modeling
Formula Based Modeling
- Structuring
- Defining
- Documenting
- Developing
- Parameterizing
- Visualizing
Algorithm Based Modeling
- Business Understanding
- Data Understanding
- Data Preparation
- Model Building
- Evaluation
- Deployment

Module Five: Applied Analytics

Discovery Analytics
Description
Techniques
- Experimental Design
- Rule Discovery
- Data Mining
- Regression Models
Enabled Business Capabilities
Examples
Descriptive Analytics
- Description
- Techniques
- Statistical Models
- Probability Distribution Models
- Monte Carlo Models
Enabled Business Capabilities
Examples
Diagnostic Analytics
Description
Techniques
- Control Charts
- Classification Models
- Abnormal Condition Models
Enabled Business Capabilities
Examples
Predictive Analytics
Description
Techniques
- Regression Models
- Neural Network Models
- Time Series Forecasting Models
- Bayes Theorem Models
Enabled Business Capabilities
Examples
Prescriptive Analytics
Description
Techniques
- Discrete Event Models
- Continuous Simulation Models
- Optimization Models
- Linear Programming Models
Enabled Business Capabilities
Examples

Module Six: Summary and Conclusion

Summary of Key Points
References and Resources

TDWI Analytics Fundamentals Training Course in Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

TDWI Analytics Fundamentals Training in Germany

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TDWI Analytics Fundamentals Training in Germany

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