Live online seminar · Databases & Data Integration
ETL processes and data integration
In plain language Combine data from several systems and process it transparently
Design data flows from source systems to reliable use.
ETL means extracting data from sources, transforming it and loading it into a target under defined quality and error rules.

Reliably planned
What is included with this seminar
Current market-standard content is included as a matter of course. CTPM+ makes the transfer to your IT, data and process practice visible.
- 01EntryBuild sound foundations
- 02ApplicationApply methods in practice
- 03SpecialisationDeepen roles and systems
- 04Transfer & coachingImplement a concrete result
Delivery
Choose the right format
Compare delivery, duration, price and configuration. In-person and in-house formats are aligned with your group, location and assignment.
Live online seminar · 2 days
Two working days for data flows, mapping, quality, error handling and operations.
- Duration
- 2 days
- Level
- Professional
- Location
- Online
CTPM+ is included in the seminar price.
Ask about availabilityIn-person seminar · tailored
Content, examples, duration and transfer are tailored to the audience and assignment.
- Duration
- By arrangement
- Level
- Professional
- Location
- Academy venue
Duration, scope and price are proposed after professional scoping.
Ask about availabilityIn-house training · client-specific
Content, examples, systems and priorities are prepared with the client.
- Duration
- By arrangement
- Level
- Professional
- Location
- At the client site
Duration, scope and price are proposed after professional scoping.
Ask about availabilityLearning content
What you will work on in this seminar
The modules make scope, priorities and intentional boundaries transparent.
Planned learning scope: 2 days. The offered format covers 2 days, including breaks, questions and transfer phases.
Review AI output for professional accuracy, completeness, contradictions, source grounding and fitness for purpose. Checklists, challenge questions and human approval points help correct weak results deliberately.
Suggested seminar agendaBuilt from this delivery’s learning modules
- Review & optimise results70 minutes
- Practical examples & exercises100 minutes
- Databases, interfaces, ETL & enterprise software120 minutes
- Quality & control points100 minutes
- Enterprise IT & project cases90 minutes
- Concrete transfer result80 minutes
- Adaptation to audience, knowledge & assignment
- Data modelling, SQL & databases100 minutes
- ETL, interfaces & data integration180 minutes
The sequence may be adapted to the group, prior knowledge and questions; the stated learning outcomes remain binding.
Compare 31 additional modulesThese topics are intentionally not included in this seminar and are shown only for comparison.
Current models, tools & applications
Content and learning objective+
Distinguish language models, AI services, copilots and specialised tools by task, data access and degree of integration. Criteria such as output quality, data protection, cost, currency and integration into existing workplaces make selection transparent.
Capabilities, limits & common failure modes
Content and learning objective+
Learn which tasks generative AI can support reliably and where probabilistic output, hallucinations, bias, context limits or outdated knowledge create risk. Common failure modes are recognised, assessed and connected to appropriate checks.
Systematic prompting
Content and learning objective+
Translate unclear work requests into structured prompts containing context, task, inputs, objective, quality criteria and output format. This makes requirements transparent, results easier to compare and follow-up questions more focused.
Improve & reuse prompts
Content and learning objective+
Improve prompts in controlled steps, compare variants and distinguish professional weaknesses from wording or context problems. Proven patterns are versioned, documented and made reusable for similar tasks.
Text, documents, research & knowledge work
Content and learning objective+
Work on common tasks such as drafting, summarising, comparing, extracting, classifying and preliminary research. Clarify required inputs, result validation and where AI usefully supports the existing workflow.
Confidential information & organisational data
Content and learning objective+
Classify personal, confidential and business-critical information and decide what data an AI service may process. Anonymisation, permissions, provider settings, internal rules and safer alternatives are assessed through practical situations.
Course materials & job aids
Content and learning objective+
Receive and use checklists, structures, examples and concise references that remain useful after the seminar. Materials are not merely distributed; they are explained and related to common application situations.
Workflows & process chains
Content and learning objective+
Map a real workflow with triggers, inputs, roles, decisions, handovers and outputs. Assess where AI can help, which controls are required and how a reliable pilot fits into the process chain.
Use documents & knowledge systematically
Content and learning objective+
Discover existing text, documents and knowledge through source structure, metadata, terminology and suitable search or retrieval approaches. Quality, currency, permissions and the limits of a RAG or knowledge solution are made explicit.
Reusable prompt, analysis & workflow templates
Content and learning objective+
Develop prompt structures, analysis templates and workflow patterns that can be reused with clear inputs, checks and ownership. Versioning and adaptation prevent templates from becoming uncontrolled one-off solutions.
Collaboration with sector experts
Content and learning objective+
For regulated, safety-critical or highly specialised content, the roles and responsibilities of a dual-instructor team are defined. CTPM covers AI, IT, data, architecture and methodology; the sector expert adds processes, terminology and binding requirements.
Requirements engineering & business analysis
Content and learning objective+
Structure stakeholders, objectives, system boundaries and requirements using suitable elicitation, modelling and documentation techniques. Quality criteria, acceptance conditions, reviews and traceability connect business and delivery.
Software architecture & modernisation
Content and learning objective+
Derive architecture goals from business and quality requirements and structure components, interfaces and responsibilities. Architecture decisions, risks, modernisation steps and transparent documentation are assessed together.
Legacy analysis & knowledge retention
Content and learning objective+
Capture functions, data, interfaces, dependencies, documentation and implicit knowledge in an established solution. Risks and unknown areas become visible so modernisation can proceed incrementally without uncontrolled changes to current behaviour.
Understand relational databases
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Select, filter and sort data
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Aggregate and group data
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Join tables safely
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Classify data changes safely
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Distinguish standard SQL, Oracle, MySQL and MariaDB
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Translate business questions into SQL
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Validate results technically and functionally
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Oracle SQL & PL/SQL
Content and learning objective+
Work with Oracle-specific SQL and PL/SQL from data access and transactions to procedures, functions and packages. Exception handling, performance, testing, interfaces and maintainability are connected through realistic database tasks.
Clarify role, assignment and mandate
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Understand stakeholders and interests
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Communicate clearly at eye level
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Prepare and represent decisions
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Address resistance and conflict early
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Create commitment without hierarchy
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Use briefing and debriefing effectively
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
Lead under uncertainty and secure transfer
Content and learning objective+
Practical module with explanation, exercise, reflection and a reusable transfer result.
The complete professional standard
Fundamentals, current tools, prompting, exercises, output review, privacy, security and responsible use are taught clearly and practically.
More transfer through senior practice
CTPM+ connects learning to roles, documents, knowledge, processes, data, interfaces, architecture and a realistic next implementation step.
An academy that enables learning
We do not merely repeat terminology. We make it usable.
More than 25 years of adult education and thousands of participants in IT and Oracle topics shape our approach: explain clearly, practise together, review critically and transfer safely.
We connect new terminology immediately with plain language and a familiar problem.
You apply the method yourself using a clear example and can ask questions at any time.
We compare results, identify errors and develop understandable quality criteria.
You leave with a template, decision aid or a concrete next step for your work.
Two learning samples from this seminar
Technical terms become clear step by step
Open an example to see how we connect terminology with meaning, application and review.
ETL and mappingHow data moves safely from source to target
A mapping defines source, transformation, target and quality rule for each field. Errors are explicitly detected and handled.
Quality gateWhen a result may move forward
A quality gate defines clear review criteria and an approval decision. Only results meeting those criteria proceed.
For seminars with practical transfer
Example transfer result
A practical, reviewed result for applying the seminar content to your own work: Daten aus mehreren Systemen zusammenführen und nachvollziehbar verarbeiten.
The actual result is adapted to the participants’ task, role and permitted data during the seminar.What you will gain
Define mappings and quality rules.
Design error handling and restart.
Assess batch, delta and streaming approaches.
What this live online seminar covers
The seminar covers sources, targets, mapping, loading, delta logic, data quality, metadata, error handling, monitoring and operations. CTPM+ connects ETL to data modelling, interfaces, legacy systems, architecture and concrete decision points.Participants
Data engineers, database developers, architects, interface owners, BI and data warehouse teams and technical project managers.
Included
Two-day seminar, data flow models, mapping exercises, quality checks and transfer design.
Prerequisites
Basic knowledge of databases, data models or integration.
Not included
No implementation in a specific ETL product or production migration.