What are some issues in data analysis?

Data Science, AI and ML
#1
A few of the inherent issues in data analysis relate to policy concerns; while others are related to the technical side of things. Data privacy is a major policy concern which businesses need to be cognizant of while extracting & processing sensitive data. Other than that, processing large sets of unstructured data into a relational format is extremely challenging as well. Also, the cost factor in large-scale data science projects often acts as a bottleneck as well for businesses.
#2

Presenting a very high level view at these issues.

Privacy: One of the important issues raised by data mining is that of individual data privacy.This is clearly a policy issue and not a technical one. Data mining/analysis is empowering us to analyze business transactions/online transactions and infer important information about individuals browsing patterns/spending behaviour.

Data Integrity: Data analysis can only be as good as the data that is being analyzed. An important challenge is integrating the various different data sources, and ensuring data cleanliness. 90% of time goes in cleaning, managing this data, before the actual analysis kicks in.

Relational Data v.s MultiDimensional Data: Whether to have data in a relational format or multidimensional. Relational is good for the client-server type of applications, multi dimensional makes the analysis part easier.