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Business Intelligence and Big Data

S152 - BUSINESS INTELLIGENCE AND BIG DATA 

COURSE EDUCATIONAL OBJECTIVES:
The course covers Big Data Fundamentals, including the characteristics of Big Data, the sources Big Data (such as social media, sensor data, and geospatial data), as well as the challenges imposed around information management, data analytics, privacy and security, as well as platforms and architectures. Emphasis will be given to non-relational databases by examining techniques for storing and processing large volumes of structured and unstructured data, streaming data as well as complex analytics on them. Data warehouses will also be presented as a solution to handling big data and business intelligence applications. Business Intelligence (BI) systems in terms of its tools, current practices and impacts .The students should acquire knowledge on how to design BI solutions for different BI targets and users.

COURSE OUTCOMES: At the end of this course, you should be able to:

 CO1: Outline basic concepts of Data Science, Data Hand Tools and Data Issues.
CO2: Illustrate the applications of Big Data like Social Media, Academics and Journalism.
CO3: Demonstrate the foundations of Business Intelligence.
CO4: Analyze various Business intelligence technologies and Identify Opportunities in Business Intelligence.
CO5: Examine Business Intelligence solutions with Implementation Strategy and case studies.

 Syllabus: https://drive.google.com/open?id=1u9ifVtjFUIGu9I2naRItcB6aXFoljrKF

 UNIT - I Data Science – Introduction, working with data at scale, data scientist, the SMAQ stack for big data, scraping, cleaning & selling big data
Data Hand Tools- free data tools for journalists.
Data Issues- Introduction, anonymization, risk of de-anonymization, Big data & semantic web,meta data.

UNIT - II Applications of Data: - Product & Process – Twitter archive, data journalism & data tools, newsroom stack, bridging the data divide, data analysis path, Big data in education & academic disciplines, Discussion of Facebook

UNIT - III BI foundations - Understanding BI, Describing BI, Defining BI cycle, Enabling BI, Bridging the Analysis Gap-Multidimensional analysis, Operation Systems, BI Systems. 

UNIT - IV Defining BI Technologies- The High-level view, Reporting & Analysis, the data warehouse and Data warehousing Framework, Identifying BI opportunities. 

UNIT - V Implementing a BI solution- implementation strategy, Fundamental decisions, Case studies- Audi AG, The Frank Russell Company. 

TEXTBOOKS
1. Elizabeth Vitt, Michael Luckevich, StaciaMisner, “Business Intelligence”, Microsoft Press, 2010. 2. “Big Data Now”, O’Reily Radar Team. 

REFERENCES 

1. Rajiv Sabherwal, Irma Becerra- Fernandez, “Business Intelligence-Practices, Technologies and Management”, John Wiley 2011. 

2. Larissa T. Moss, ShakuAtre, “Business Intelligence Roadmap”, Addison –Wesley IT Series. 

3. Yuli Vasiliev, “Oracle Business Intelligence”. 














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