CIS 9002 Kannan Mohan Department of CIS Zicklin School of Business, Baruch College
Articulate the role of business intelligence in organizations Explain the use of Data warehouses, Data mining, and Artificial Intelligence in helping business decision making
Predicting Flu outbreaks What drives the price of Bitcoins? Target’s foray into analytics Watson and Jeopardy
Unstructured Massive amounts Not amenable for easy processing using conventional databases
Reporting, data exploration, ad-hoc queries, sophisticated data modeling and analysis Analytics Extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions
Information technology Statistics Business knowledge
Collection: What kind of data? How much data? Storage: Structure, access, security Analysis: Structure or not? Algorithms, Assumptions Interpretation: Correlation vs. Causation, Type I/II errors, Outliers
Data: Raw facts and figures Information: Data presented in a context so that it can answer a question or support decision making Knowledge: Insight derived from experience, expertise, and ability to interpret
Database: A single table or a collection of related tables Database management systems (DBMS): Software for creating, maintaining, and manipulating data (Eg. MS Access, MS SQL Server, MySQL) Structured query language (SQL): A language used to create and manipulate databases
How do you organize data? How do you connect different pieces of data? How do you answer questions that are important for you? Tables and relationships Avoiding data integrity problems
Data warehouses Data marts Data mining Artificial Intelligence
(Laudon and Laudon, 2009)
Provide regular summaries of information in a predetermined format Canned reports Create custom reports on an as-needed basis by selecting fields, ranges, summary conditions, and other parameters Ad hoc reporting tools Display of critical indicators that allow managers to get a graphical glance at key performance metrics Dashboards Takes data from standard relational databases, calculates and summarizes the data, and then stores the data in a special database called a data cube Data cube: Stores data in OLAP report Online analytical processing (OLAP)
Identifying hidden patterns in large datasets Areas of application: Customer churn Fraud detection Financial modeling Hiring and promotion Customer segmentation Marketing and promotion targeting Market basket analysis Collaborative filtering
(Laudon and Laudon, 2009)
How do you arrive at interpretations? Role of theory Large enough data set to find anything? Security and privacy issues - Who has control over the data? Analyzing Big Data Size and speed of analytics Distributing over commodity hardware
Information Retrieval Natural Language Processing Machine Learning Cognitive Technologies Deep Learning Data Science
What is business intelligence? How do we organize data in databases? What is the role of data warehousing, data mining, and artificial intelligence in business decision making?