Business Intelligence Analyst Developer career plan for 1 year
| Quarter | Goals and Objectives | Actions and Tasks | Skills to Develop/Enhance |
|---|---|---|---|
| Quarter 1 | – Gain a foundational understanding of BI | – Study business intelligence concepts, data warehousing, ETL processes, and data visualization tools | – BI fundamentals, data warehousing |
| – Familiarize with common BI tools and platforms | – Learn about tools like Power BI, Tableau, or QlikView, and understand their capabilities | – BI tools and platforms | |
| – Enhance problem-solving skills | – Practice problem-solving techniques, critical thinking, and deriving insights from BI data | – Problem-solving skills | |
| – Improve communication and data presentation | – Study effective ways to present BI insights through dashboards, reports, and visualizations | – Communication, data presentation | |
| – Attend local or virtual BI-related events | – Connect with BI professionals, share experiences, and learn from industry experts | – Networking with professionals | |
| Quarter 2 | – Dive deeper into advanced BI techniques | – Study advanced data visualization techniques, interactive dashboards, and storytelling | – Advanced data visualization techniques |
| – Learn about data modeling and SQL | – Explore data modeling principles and improve SQL querying skills for data extraction | – Data modeling, SQL querying | |
| – Gain familiarity with scripting languages | – Study scripting languages (e.g., Python) for automating tasks, data processing, and analysis | – Scripting languages (Python) | |
| – Start building a portfolio of BI projects | – Work on small BI projects, create interactive dashboards, and document your analysis | – Portfolio development | |
| – Regularly contribute to personal GitHub repositories | – Contribute to open-source BI projects, personal projects, or BI-related scripts on GitHub | – GitHub collaboration | |
| Quarter 3 | – Focus on advanced data analysis and insights | – Study advanced data analysis techniques, trends analysis, forecasting, and business insights | – Advanced data analysis techniques |
| – Learn about data integration and ETL | – Study ETL processes, data integration strategies, and transforming data from various sources | – Data integration, ETL processes | |
| – Gain familiarity with cloud platforms | – Study cloud platforms for BI (e.g., AWS, Azure) and how to set up environments for BI tasks | – Cloud platform usage | |
| – Explore data storytelling techniques | – Learn how to present data insights in a narrative form, effectively communicating findings | – Data storytelling skills | |
| – Reflect on your BI projects | – Evaluate your portfolio projects, identify areas for improvement, and set new goals | – Self-assessment and goal-setting | |
| Quarter 4 | – Deepen programming and automation skills | – Study advanced programming concepts and techniques for BI tasks, including data automation | – Advanced programming skills |
| – Focus on data security and privacy | – Learn about data security best practices, privacy regulations, and how to handle sensitive data | – Data security, privacy regulations | |
| – Explore big data technologies | – Familiarize with big data technologies (e.g., Hadoop, Spark) and their relevance to BI | – Big data technologies | |
| – Gain familiarity with machine learning | – Explore basic concepts of machine learning and AI, their applications in BI, and predictive analytics | – Machine learning basics | |
| – Reflect on the year’s achievements and set new goals | – Evaluate your progress and set goals for the next year based on your growth | – Self-assessment and goal-setting | |
| – Continuously seek learning opportunities | – Stay updated with the latest BI trends, tools, and industry best practices | – Lifelong learning |