Business Analyst — Business Intelligence & Reporting
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What you'll learn:
Deep dive into modern data warehousing principles and ETL (Extract, Transform, Load) processes. - **Description:** Focus on advanced topics such as data lake integration, ELT (Extract, Load, Transform) strategies, and designing scalable data pipelines for high-volume, real-time data ingestion. Explore various data warehousing architectures like Kimball, Inmon, and Data Vault. Understand different ETL tools and their optimal usage. - **Resources/Activities:** - Read articles and whitepapers on modern data warehousing architectures (Kimball, Inmon, Data Vault 2.0). - Explore advanced ETL tool features (e.g., Apache NiFi, Airflow). - Design a hypothetical data warehouse schema for a complex business scenario (e.g., multi-channel retail). - Evaluate the pros and cons of ELT vs. ETL for specific use cases. - **Expected Outcomes:** Mastery of advanced data warehousing concepts, ETL/ELT pipeline design expertise, ability to choose the appropriate architecture for various business needs.
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What you'll learn:
Crafting and Implementing a BI Strategy that Aligns with Business Goals. - **Description:** Learn how to develop a comprehensive BI strategy aligned with organizational objectives. This includes defining key performance indicators (KPIs), establishing data governance policies, promoting data literacy, and fostering a data-driven culture. Address change management and stakeholder engagement strategies. - **Resources/Activities:** - Analyze industry best practices for BI strategy development and implementation. - Research data governance frameworks (e.g., DAMA-DMBOK). - Develop a BI strategy for a given business case, including a roadmap, key initiatives, and expected outcomes. - Practice stakeholder management and communication techniques. - **Expected Outcomes:** Ability to create and execute a BI strategy, data governance implementation skills, knowledge of how to drive data-driven decision-making within an organization.
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What you'll learn:
Deep Dive into Dimensional Modeling and Optimization - **Description:** Focus on advanced dimensional modeling techniques, including Slowly Changing Dimensions (SCDs), fact table optimization, and handling complex business relationships. Explore data modeling tools, performance optimization techniques, and the impact of data modeling on report performance. - **Resources/Activities:** - Study advanced dimensional modeling concepts like SCD types, degenerate dimensions, and fact constellation models. - Practice building star schemas and snowflake schemas using data modeling tools (e.g., ERwin, Lucidchart, or even draw.io). - Optimize data models for specific reporting requirements. Analyze query performance and apply tuning techniques. - **Expected Outcomes:** Expertise in designing efficient and optimized data models for advanced reporting and analysis, understanding of performance tuning techniques.
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What you'll learn:
Transforming Data into Compelling Insights. - **Description:** Go beyond basic data visualization and explore advanced techniques for creating compelling and insightful dashboards and reports. Focus on effective visual communication, storytelling with data, and selecting the most appropriate chart types for different data sets and audience needs. Practice creating interactive dashboards and leveraging advanced visualization features. - **Resources/Activities:** - Study data visualization best practices (e.g., Edward Tufte's principles). - Explore advanced features of BI tools (e.g., Power BI, Tableau, QlikView). - Create a series of interactive dashboards and reports for a given business scenario, focusing on storytelling and insightful communication. - Analyze and critique existing dashboards for effectiveness. - **Expected Outcomes:** Ability to create compelling and insightful data visualizations, mastery of data storytelling techniques, and proficiency in advanced features of BI tools.
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What you'll learn:
Mastering Sophisticated Reporting Methods. - **Description:** Learn complex reporting techniques, including advanced calculations, report automation, and the integration of predictive analytics into reports. Focus on building dynamic reports and optimizing report performance. Learn about report design principles and best practices. - **Resources/Activities:** - Study advanced reporting functions and features (e.g., custom calculations, parameters, calculated columns/measures). - Practice report automation using scripting or built-in scheduling features of your BI tool. - Integrate predictive analytics models (e.g., time series forecasting) into reports. - Design and optimize report layouts for different device types. - **Expected Outcomes:** Expertise in advanced reporting techniques, ability to build dynamic and interactive reports, and knowledge of report performance optimization.
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What you'll learn:
Ensuring Data Integrity and Confidentiality. - **Description:** Focus on data security best practices, data privacy regulations (e.g., GDPR, CCPA), and compliance requirements within the context of BI. Learn how to implement data masking, access controls, and auditing mechanisms to protect sensitive data. Understand ethical considerations in data usage. - **Resources/Activities:** - Research data security and privacy regulations relevant to your industry. - Explore data security features within your chosen BI tools. - Design and implement data access controls and security policies for a hypothetical BI environment. - Study ethical considerations of data use and bias in reporting. - **Expected Outcomes:** Understanding of data security and privacy principles, proficiency in implementing security measures in BI systems, and knowledge of compliance requirements.
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What you'll learn:
Applying Knowledge and Skills. - **Description:** Hands-on exercises and case studies focusing on real-world business scenarios. Work with various BI tools and technologies to apply the knowledge gained throughout the week. This includes choosing the right tool for the job, comparing different tool's capabilities, and understanding their integration. - **Resources/Activities:** - Work on case studies that require the application of all skills learned throughout the week. - Hands-on exercises using various BI tools (e.g., Power BI, Tableau, Looker, Qlik). - Compare and contrast different BI tools based on their features, strengths, and weaknesses. - Present findings and insights to a virtual "client" (a peer or mentor) using the created reports. - **Expected Outcomes:** Ability to apply all learned skills to solve real-world business problems, experience with a variety of BI tools, and the ability to articulate findings and recommendations effectively.
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