(1) Data: where does it come from and how is it managed?
(2) Analytics: what types of models can we build and who builds them?
(3) Organizational context: how do we strategize and organize the business analytics function?

Learning Outcomes
Explain how business analytics is changing organizations, governments, and the lives of citizens
Describe the sources of big data and the types of data used in business analytics
Explain the different types of analytics models that are produced by data scientists and how they can be deployed to create value
Describe the characteristics of a data scientist and their role in an organization
Explain why business analytics is a strategic and cultural issue for organizations.


data sources

internal----enterprise systems and e-commerce applications
external-----third parties, for example credit scores, and from the Internet via social media platforms
open platforms- - - - -data made freely available by other organizations, such as governments (e.g., Census data)

data generators
InternetofThings(IoT)
ubiquitous computing
social media
big data- -- -4V   volume velocity variety veracity  the implied fifth v--- value

data management
SaaS PaaS IaaS

big data technologies
operational big data
analytical big data

data quality

analytics
models- - - --descriptive/prescriptive/predictive

data scientists

the organizational context

business analytics strategy

business analytics applications

the business analytics function----data science, business analysis, IT operations, and data management

business analytics changes
1.Dealing with data growth
2.Generating insights in a timely manner
3.Recruiting and retaining big data talent
4.Integrating disparate data sources
5.Validating data
6.Securing data
7.Organizational resistance