The course first introduces the business aspects of big data analytics. This includes a discussion on market dynamics as well as key managerial issues (i.e., organizational alignment, integration strategies and data governance issues. It further analyzes the big data application high-performance aspects related to architectural choices in software and hardware. The last part covers an introductory technical discussion on tools and algorithms used in big data analytics. Emphasis is given on Spark 2.0 framework (via Python – PySpark) through real case applications related to data exploration, regression, k-means, neural networks etc.
Course ID: MIS-612
| Credit hours | Theory | Practical | Laboratory | Lecture | Studio | Contact hours | Pre-requisite | 3 | - | MIS-602 & 604 |
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