Graduate Certificate in BI Analytics
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⢠Data Warehousing Fundamentals: Understanding the concepts, architecture, and design of data warehouses. ETL processes, data modeling, and data governance.
⢠Data Visualization: Designing effective visualizations for data analysis, conveying insights, and storytelling. Utilizing tools like Tableau, PowerBI, or ggplot2.
⢠Statistical Analysis: Applying statistical methods to BI analytics. Descriptive, diagnostic, predictive, and prescriptive analytics. Using tools like R and Python for statistical modeling.
⢠Big Data Analytics: Exploring big data technologies and their applications in BI analytics. Hadoop, Spark, Hive, and Pig.
⢠Machine Learning: Applying machine learning algorithms to BI analytics. Supervised, unsupervised, and reinforcement learning. Using libraries like scikit-learn and TensorFlow.
⢠Data Mining: Discovering patterns and trends in large datasets. Association rules, clustering, and classification techniques. Utilizing tools like Weka and RapidMiner.
⢠Business Intelligence Tools: Hands-on experience with popular BI tools. Microsoft PowerBI, Tableau, Qlik, and IBM Cognos.
⢠Data Storytelling: Communicating data insights effectively to stakeholders. Developing persuasive arguments, visualizing data, and presenting findings.
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