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Certificates: Certificate "Big Data Analyst"
Original SAP Consultant Certificate -
Additional Certificates: Data Engineer" certificate
Data Analyst" certificate
Certificate "Big Data Specialist" -
Examination: Praxisbezogene Projektarbeiten/Fallstudie
SAP-Beraterzertifizierung Reporting, Modeling and Data Acquisition mit SAP BW/4HANA C_BW4H -
Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 28 Weeks
Data Engineer
Fundamentals of Data Engineering and Data Architectures (approx. 2 days)
Tasks and Application Areas in Data Engineering
Fundamentals of Modern Data Architectures and Data Platforms
Fundamentals and Comparison of Cloud-Based Data Architectures
OLTP and OLAP
Processing Structured, Semi-Structured, and Unstructured Data
Requirements Management and Data Modeling (approx. 1 day)
Requirements for Data and Data Sources
Conceptual Data Modeling
Modeling Data Structures and Data Flows
Data Contracts, Data Governance, and Data Lineage
Databases and Data Processing (approx. 1 day)
Database System Architecture
SQL vs. NoSQL vs. NewSQL: A Comparison
Relational Data Modeling
SQL for Querying and Processing Data
Data Warehousing and Modern Data Architectures (approx. 2 days)
Fundamentals and Architecture of Data Warehouse Systems
Dimensional Data Modeling and Schema Design
Facts, Dimensions, and Historical Data Storage
Comparing Data Warehouses, Data Lakes, and Lakehouses
Introduction to dbt
Practical Implementation of Data Models
Data Integration and Data Pipelines (approx. 5 days)
Data Integration and Data Provisioning
ETL and ELT Processes
Design and Orchestration of Data Pipelines
Data Cleaning, Validation, and Data Quality
Batch and Streaming Processing
Practical Application of Airflow and Spark
Programming and Automated Data Processing (approx. 4 days)
Python Environments and Package Management
Data Processing and Transformation with Python
Automation of data processing workflows
Connecting to Different Data Sources and Interfaces
Development of data engineering workflows
Containerization with Docker
AI-powered support in the development and data processing process
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
Data analytics
Introduction to Data Analytics (approx. 1 day)
Tasks, Areas of Application, and Typical Use Cases of Data Analytics
Data Analytics Processes and CRISP-DM
The Role of the Data Analyst and How It Differs from Data Science, Data Engineering, and Business Intelligence
Classification of Artificial Intelligence and Machine Learning
Python for Data Analytics (approx. 1 day)
Working with Jupyter Notebooks
NumPy and Pandas for Data Analysis
Importing and Exporting Data from Various Sources, e.g., Excel and CSV
Selecting and transforming data
Data Preparation and Exploratory Data Analysis (approx. 3 days)
Data cleaning and transformation with Pandas
Handling missing, incorrect, and outlier data
Merging, grouping, and aggregating data
Exploratory data analysis and deriving initial insights
Fundamentals of statistical analysis
SQL and Data Management (approx. 2 days)
Relational Databases and Data Models
Data Queries and Processing with SQL
Joins, aggregations, and analytical queries
Interaction Between SQL and Python in Data Analysis
Data Quality and Data Protection
Connecting to and Using Different Data Sources and Database Systems
Data Visualization and Data Storytelling (approx. 2 days)
Visualization with Matplotlib, Seaborn, and Plotly
Selecting Appropriate Charts and Visualization Methods
Preparing and interpreting analysis results
Data Storytelling and Communication Tailored to the Audience
Power BI and Interactive Dashboards (approx. 2 days)
Data Import and Preparation with Power Query
Data modeling and relationships
Basics of DAX and metrics
Creating interactive reports and dashboards
Visualization and Communication of Business KPIs
Overview of Alternative Business Intelligence and Visualization Solutions
AI-powered data analysis (approx. 2 days)
Use of generative AI in the data analytics workflow
AI-powered data preparation, analysis, and visualization
Support with Python and SQL queries
Prompting for data analysis and interpretation of results
Critical evaluation of data sources and detection of synthetic and implausible data
Quality assurance, data protection, and responsible use of AI
Business Analytics and Statistical Fundamentals (approx. 2 days)
Key Metrics and KPIs in a Business Context
Descriptive Statistics and Statistical Relationships
Correlation, Causality, and Simple Regression Analyses
Fundamentals of confidence intervals and hypothesis testing
Interpreting Analysis Results and Deriving Data-Driven Recommendations
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
Big Data Specialist
What is Big Data? (approx. 1 day)
Volume, Velocity, Variety, Value, Veracity
Opportunities and risks of large amounts of data
Differentiation: business intelligence, data analytics, data science
Introduction to data mining
Role of AI and data-driven systems in the big data environment
Introduction to big data frameworks (approx. 2 days)
Big data solutions in the cloud (overview of AWS, Azure, GCP)
Data access patterns
Data storage
Introduction to data lakes and data warehouses
Overview of Apache Hadoop and Spark
Distributed data processing with Spark (approx. 3 days)
Basics of distributed systems
Apache Spark (Core and SQL)
Comparison of different approaches to data processing
Processing large amounts of data
Introduction to simple ML workflows with Spark
Data pipelines and data integration (approx. 2 days)
ETL and ELT processes
Batch vs. streaming processing
Basics of data pipelines
Introduction to orchestration (e.g. Airflow overview)
Data quality and preparation
Components (approx. 2 days)
Brief presentation of various tools
Data transfer
Overview of resource management in big data systems
Hadoop ecosystem
Apache Spark deepening
Introduction to streaming technologies
NoSQL and data storage (approx. 2 days)
CAP theorem
ACID and BASE
Types of databases
HBase
Introduction to document-oriented databases
Introduction to storage formats
Overview of data lakehouse approaches
Big Data Visualization (approx. 2 days)
Theories of visualization
Diagram selection
New types of diagrams
Tools for data visualization
Introduction to BI tools (e.g. Power BI, Tableau)
Basics of data-driven decision making
Data governance and data protection (approx. 1 day)
Basics of the GDPR in the data context
Data ethics and responsible handling of data
Data quality and governance concepts
Access controls and security
Fundamentals of responsible AI use
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
SAP Consultant BW/4HANA - Reporting, Modeling and Data Acquisition
Introduction (approx. 20 days)
First, you will get to know the SAP system landscape by choosing one of the following topics:
either:
Elective topic 1: SAP Financial Accounting (FI) and Controlling (CO)
S4H00 Overview of SAP S/4HANA
S4F10 Business processes in financial accounting
S4F20 Business processes in internal accounting (Controlling)
or:
Elective topic 2: SAP Materials Management (MM) and Sales and Distribution (SD)
S4H00 Overview of SAP S/4HANA
S4500 Sourcing and procurement business processes
S4600 Business processes in Sales
Your chosen topic is followed by the BW-specific SAP topics:
BW405 - Query Design and Analysis (approx. 10 days)
Introduction to SAP HANA and SAP BW/4HANA
Starting reports and navigating in reports
Simple queries
Key figures in queries
Structures in queries
Characteristics, attributes and hierarchies
Variables in queries
Exceptions and conditions in queries
Report-report interface
Query performance optimization
Query administration
Overview of authorizations
Overview of SAP Analytics
BW410 - Data Warehousing (approx. 10 days)
Introduction to SAP HANA
Master data in SAP Business Warehouse BW/4HANA
Transaction data in SAP BW/4HANA
Native modeling in SAP HANA
Open ODS Views
Advanced SAP BW/4HANA topics
BW430 - Data Modeling (approx. 15 days)
Challenges in data modeling
Overview: The business case
Modeling approaches in SAP BW/4HANA
Best practice standards in SAP BW/4HANA modeling
Modeling process
SAP BW/4HANA content add-on
Implementing field-based rapid prototyping for SAP BW/4HANA
Implementing models in SAP BW/4HANA
Implement native SAP HANA views
Implement agile data marts
Implementing SAP BW/4HANA Workspaces
Advanced Modeling in SAP BW/4HANA
BW450 - Data provision (approx. 10 days)
Data provision in SAP HANA
Overview of SAP BW/4HANA
Data provisioning in SAP BW/4HANA via the SAP HANA source system
Data provisioning in SAP BW/4HANA via Operational Data Provisioning (ODP_SAP)
Delta management in Operational Data Provisioning (ODP_SAP)
Data extraction from SAP S/4HANA in SAP BW/4HANA
Other types of operational data provisioning in SAP BW/4HANA
Manage and optimize data flow components in SAP BW/4HANA
Big data provisioning in SAP BW/4HANA and SAP Data Hub
SAP BW465 Authorizations (approx. 5 days)
Authorization concepts
Standard authorization objects for reporting users
Analysis authorizations
Standard authorizations for modelers and administrators
Security of system communication
Introduction to SAP HANA authorizations
Authorizations in mixed scenarios
Additional topics in SAP Business Warehouse
Case study, certification preparation and SAP consultant certification BW/4HANA (approx. 10 days)
Changes are possible, the course content is updated regularly.
You are proficient in the processes involved in merging, preparing, enriching and forwarding data and understand big data analysis using basic Python programming, SQL and NoSQL database concepts. Knowledge of industry-specific software for processing and structuring large, unstructured data and visualizing it rounds off your knowledge.
You will also have the necessary qualifications to provide your clients with comprehensive and competent support as an SAP BW/4HANA consultant. The course will enable you to use the SAP BW/4HANA technology platform to automate, evaluate and present company statistics in electronic form. Your professional profile will be enhanced by the SAP Consultant certification.
The course is aimed at people with a degree in computer science, business informatics, business administration, mathematics or comparable qualifications.
A systematic evaluation of data volumes is essential for companies in order to generate information about their own products and customer behavior. Against this backdrop, big data analysts are increasingly in demand across all industries.
You will also acquire the globally standardized and recognized SAP certificate. It is considered one of the most important manufacturer certifications in the IT sector and will improve your career prospects on the job market across all industries. Managers in the field of Business Warehouse are in demand from both large and medium-sized companies in industry, trade, services and finance. Your potential fields of activity lie in business and software consulting, development and business analysis and reporting
Training partner of SAP® Germany
In cooperation with the SAP training partner alfatraining Bildungszentrum GmbH, we will qualify you for a job in industry and business.
You are directly connected to the SAP® Germany servers and learn on the original SAP® training system (IDES) in the latest version. This gives you the necessary practical experience during the course.
All SAP consultant courses also conclude with the original SAP certification. Our SAP instructors are qualified SAP consultants who will provide you with intensive support and prepare you optimally for the certification exam.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face teaching via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).