Management Information Systems
MISM 3405: Data Wrangling for Business Analytics
Lecture - 4 credits
ND
EI
IC
FQ
SI
AD
DD
ER
WF
WD
WI
EX
CE
- Covers data wrangling principles and novel techniques for business analytics.
- Key topics include data profiling, data retrieval, data cleansing, and data integration, as well as data extraction and exploration via APIs.
- Applies the principles of data wrangling for structured and unstructured data using industry tools such as Oracle, SQL, statistical programming languages (R/Python), and visualization tools (Tableau).
- Offers students an opportunity to learn data wrangling techniques to identify and solve real-world data challenges, creating business value from the vast amount and types of traditional and big data.
Covers data wrangling principles and novel techniques for business analytics. Show more.