Tasks and Duties
Objective
The goal for Week 1 is to build a foundational understanding of SAP HANA data modeling. You will design both logical and physical data models suitable for analytical processing. The task emphasizes practical work, requiring you to create a detailed document in a DOC file format.
Expected Deliverables
- A DOC file containing a complete data modeling strategy for a hypothetical business scenario.
- Diagrams detailing the logical and physical data models, clearly outlining entities, relationships, and key attributes.
- A comprehensive explanation of your data model design choices.
Key Steps
- Research and Analysis: Study the fundamentals of SAP HANA data modeling and note best practices.
- Scenario Development: Develop a realistic business scenario using publicly available data sources.
- Model Design: Create logical and physical diagrams, detailing the structure and relationships of data elements. Tools such as Visio or draw.io can be used.
- Documentation: Prepare a detailed explanation of your design, addressing scalability, performance, and security considerations.
- Review and Revise: Check your work for clarity, ensuring information is well-organized and accurate.
Evaluation Criteria
- Clarity and completeness of the data models
- The logical flow and organization of the documentation
- Depth of analysis and justification of design decisions
- Correct use of diagrams and technical accuracy
- Overall presentation, readability, and adherence to DOC file submission requirements
This task is designed to take between 30 to 35 hours and simulate a real-life scenario where you are required to quickly adapt and devise excellent data models under time constraints.
Objective
The objective for Week 2 is to gain hands-on experience with data extraction and transformation processes in SAP HANA. You will develop a comprehensive DOC file report that outlines your approach to extracting data from a public source, transforming it for analysis, and loading it into a SAP HANA environment.
Expected Deliverables
- A DOC file report detailing the end-to-end process of data extraction, transformation, and loading (ETL).
- Step-by-step accounts of data preparation, including code snippets, if applicable.
- Diagrams or flowcharts illustrating the ETL process.
- Analysis of challenges encountered and strategies used to overcome them.
Key Steps
- Source Identification: Choose a publicly available dataset relevant to analytics.
- Data Extraction: Describe the methods and tools utilized to extract data from the chosen source.
- Data Transformation: Demonstrate cleaning, refining, and integration steps needed to prepare the data for SAP HANA.
- Data Loading: Provide a process explanation on how to load data into SAP HANA, including code examples or pseudo-code if applicable.
- Documentation: Compile all findings, challenges, and solutions into a structured DOC file report.
Evaluation Criteria
- Completeness and depth of the ETL process described
- Clarity of code snippets and flowcharts provided
- Logical organization and narrative quality of the documentation
- Evidence of problem-solving and critical thinking during transformation
- Overall presentation and adherence to the weekly task requirements
This exercise is expected to take approximately 30 to 35 hours and is designed to simulate real-world data integration scenarios encountered by SAP HANA data analysts.
Objective
Week 3 focuses on optimizing query performance in SAP HANA. You will conduct a benchmark analysis on various SQL queries, explore methods to optimize them, and document your findings. This task emphasizes practical experience and the development of a comprehensive analysis report in a DOC file format.
Expected Deliverables
- A DOC file report that details your analysis of SQL query performance, including before and after optimization metrics.
- Descriptions of queries tested along with their optimization strategies.
- Tables, graphs, or charts that highlight performance improvements.
- A summary of challenges encountered and solutions implemented.
Key Steps
- Initial Benchmarking: Identify and execute a set of baseline queries using SAP HANA SQLScript, recording their performance metrics.
- Identify Bottlenecks: Analyze query execution plans to pinpoint performance issues.
- Optimization Process: Implement optimization strategies such as indexing, partitioning, or rewriting queries. Document each step and change.
- Post-Optimization Benchmarking: Re-run the queries to capture improvements, tabulating and comparing results.
- Report Writing: Create a detailed DOC file report that incorporates methodology, results, visual aids, and final insights.
Evaluation Criteria
- Accuracy and depth of performance analysis
- Effectiveness and practicality of optimization strategies employed
- Clarity in presentation of data, supported by visual aids
- Insightfulness of conclusions drawn from performance metrics
- Overall organization and structure of the report document
This task will require approximately 30 to 35 hours of work and is intended to give you in-depth knowledge of query performance tuning – a vital skill in the SAP HANA data analysis toolkit.
Objective
For Week 4, you are tasked with creating a comprehensive dashboard that visualizes key performance indicators (KPIs) using SAP HANA. This practical exercise will help you understand the process of turning raw data into actionable insights through the effective use of data visualization techniques.
Expected Deliverables
- A DOC file that details the dashboard development process, including conceptualization, design, and the technical steps taken.
- Screenshots or mock-ups of the final dashboard design.
- Explanation of tool selection, data sources used, and visualization rationale.
- A section covering potential improvements and future enhancements.
Key Steps
- Conceptualization: Define the business scenario by choosing relevant KPIs and data sources.
- Tool Selection: Select an appropriate data visualization tool that integrates with SAP HANA. Justify your choice.
- Dashboard Design: Develop an initial layout using wireframes or sketches, detailing the placement and design of charts, tables, and filters.
- Implementation Steps: Describe the integration and data linking process, providing code snippets, if relevant.
- Documentation: Craft a comprehensive DOC file that captures the entire process, supporting diagrams, screenshots, and incremental improvements.
Evaluation Criteria
- Quality and clarity of the dashboard layout
- Effectiveness in communicating insights through visual aids
- Depth of explanation regarding tool and design choices
- Thoroughness in documenting the entire process
- Overall presentation and adherence to the task guidelines
You are expected to spend approximately 30 to 35 hours on this task, which simulates a typical project phase where data analysts create visual representations for strategic decision-making.
Objective
This week’s assignment focuses on integrating advanced analytics within the SAP HANA environment. You will apply predictive analytics techniques to a dataset (using publicly available data), document the integration method, and evaluate the impact of your analytics on decision making. The final deliverable must be captured in a comprehensive DOC file.
Expected Deliverables
- A DOC file report detailing the integration of advanced analytics into an SAP HANA project.
- Step-by-step implementation details, including data preprocessing, model selection, and validation metrics.
- Diagrams or flowcharts that represent the analytical process.
- A discussion on the impact of advanced analytics in providing strategic business insights.
Key Steps
- Dataset Selection: Identify a publicly available dataset suitable for predictive analysis.
- Analytical Framework: Outline and justify the predictive model(s) selected for the analysis.
- Implementation: Document your steps in preprocessing data, implementing predictive analytics in SAP HANA (via SQLScript or other analytics tools), and validating model performance.
- Integration Approach: Explain how the insights from your analytics can be integrated into broader business strategies.
- Report Preparation: Compile your work into a detailed DOC file including process diagrams, code examples, and outcome analysis.
Evaluation Criteria
- Depth and accuracy of predictive analytics implementation
- Clarity in explaining model selection and validation
- Quality and relevance of diagrams or flowcharts
- Overall integration of analytics insights into business decision making
- Adherence to the DOC file submission format and task guidelines
This task is expected to take about 30 to 35 hours and will enhance your practical skills in embedding advanced analytics within SAP HANA projects.
Objective
The final week’s task centers around project evaluation and the development of a future roadmap for continuous improvement in SAP HANA data analysis operations. In this task, you will critically analyze a pseudo-project, identify strengths and weaknesses, and propose innovative enhancements for the project lifecycle. The final deliverable is a comprehensive DOC file document.
Expected Deliverables
- A DOC file that provides a detailed evaluation of a simulated SAP HANA project.
- A SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) related to the project execution.
- An actionable roadmap outlining proposed strategies for improvement, including technological and process enhancements.
- Visual aids like Gantt charts or flow diagrams to highlight phases and planning timelines.
Key Steps
- Project Overview: Provide an overview of the simulated project, including objectives, methodologies, and outcomes.
- Critical Evaluation: Conduct a detailed evaluation assessing project performance using a SWOT framework. Identify what worked well and areas needing improvement.
- Roadmap Development: Based on your evaluation, develop a forward-looking roadmap with suggested improvements, advanced techniques, and strategies for future projects.
- Documentation: Organize your findings and proposed strategies into a comprehensive DOC file. Integrate diagrams and charts to illustrate key points.
- Conclusion: Summarize your insights and recommendations, emphasizing the anticipated impact on operational efficiency and data-driven decision-making.
Evaluation Criteria
- Depth and clarity of the project evaluation
- Relevance and feasibility of proposed improvement strategies
- Quality of visual aids and diagrams used in the documentation
- Overall structural organization and clarity of the DOC file
- Ability to integrate analytical insights into strategic planning
This capstone task is designed to take approximately 30 to 35 hours and challenges you to use a holistic approach to review and enhance SAP HANA implementation practices, preparing you for real-world challenges in data analysis and strategic planning.