Business Intelligence Exam 1 with complete solutions

What is Business Intelligence? - Answer- a set of methodologies, processes, architectures, and technologies that transform raw data (both internal and external to the organization) into meaningful and useful information. What is the objective of Business Intelligence? - Answer- to support better business decision- making by exploiting relevant and timely information What are the major factors driving BI adoption? - Answer- -dramatic increase in quantity of available data -increasingly complicated decisions and decision environments -need for quick reflexes -technological process Dramatic increase in quantity of available data - Answer- -Cheaper storage -More electronic connections -Regulatory changes Increasingly complicated decisions and decision environments - Answer- -Multi-industry, global competition -Decisions from structured and unstructured data Need for quick reflexes - Answer- -Faster pace of change (volatility) -Windows of opportunity close rapidly Technological Progress - Answer- -Processing speeds and data capacity -Enterprise Resource Planning systems (ERP) -Data warehousing -Accessible Data mining models -Accessible Text Data mining models Descriptive Analytics - Answer- refers to knowing what is happening in the organization and understanding some underlying trends and causes of such occurrences Predictive Analytics - Answer- aims to determine what is likely to happen in the future. This analysis is based on statistical techniques as well as other more recently developed techniques that fall under the general category of data mining Prescriptive Analytics - Answer- The goal of this is to recognize what is going on as well as the likely forecast and make decisions to achieve the best performance possible. The goal is also to provide a decision or a recommendation for a specific action Comparing descriptive, predictive and prescriptive analytics - Answer- Descriptive: What happened? What is happening? Predictive: What will happen? When will it happen? Prescriptive: What should I do? Why should I do it? Business Driven Goals of DW and DW requirements - Answer- -DW not about tools -DW not about technology -"first and foremost, the DW/BI system must consider the needs of the business" -Successful DW implementations demand end user involvement Dimensional Modeling - Answer- -preferred method for presenting BI data -resilient to change -(often) instantiated in RDBMS -designs use traditional modeling representations (ERD, UML) Differences of the needs of data capture from the needs of data analysis - Answer- Needs of data capture: -"Users of operational systems turn the wheels of the organization" -Interactions are usually record oriented -Used for Order entry, customer services, etc. Needs of data analysis: -"Users of DW/BI systems watch the wheels of the organization turn to evaluate performance" -usually NEVER deal with a single record - Used for "what" things happened and "why" things happened and are such things "likely" to happen again RDBMS - Answer- Relational Database Management System "star schema" - Answer- the most commonly used way to represent data, containing a central fact table surrounded by and connected to several dimensional tables A constellation or galaxy of stars - Answer- When a dimensional model contains more than one fact table Dimensional Modeling Misconceptions (Myths) - Answer- -DMs are only for summary data -DMs are departmental, not enterprise -DMs are not scalable -DMs are only useful for predicable usage patterns -DMs cannot be integrated Requirements of a DW - Answer- -must make information easily accessible -must present information consistently -system must be able to adapt to change -system must present information in a timely way -system must be a secure bastion that protects the information -system must serve as the authoritative and trustworthy foundation for improved decision making -business community must accept the DW/BI system to deem it successful Two general table types that comprise a Dimensional Model - Answer- 1) Fact Table 2) Decision Table Fact Table - Answer- -Fact Tables store performance measurements resulting from business process measurement events -Each FT row corresponds to a measurement event -FT are LARGE -Business process measurement events have a 1-to-1 relationship with FT rows -Most useful Facts are numeric (continuously valued) and additive Characteristics of Fact Tables - Answer- -Sparse in the sense FTs only capture events that happen -Deep in terms of rows and narrow in terms of attributes -All FT have 2 or more foreign keys to connect to dimension tables -FT primary key is a composite key composed of subset of available attributes -Fact tables express many-to-many relationships among dimensions -Two of the most common additional attributes that can appear in the fact table are: -Transaction identifiers • Transaction time Dimension Table Characteristics - Answer- -Shallow in terms of rows and wide in terms of attributes -Surrogate primary key Dimension Model Characteristics - Answer- -Simplicity -Recognizable to business users -Extensible Design -The most granular data has the most dimensionality Dimension Table - Answer- -Contains the context associated with a business process measurement event Describe the "who, what, when, where, how and why" associated with the event -DT attribute values are the principal source of DW usability -often represent existing hierarchical relationships -DTs are (almost) always in 1NF dashboard - Answer- visual representation of critical data for executives to view. It allows executives to see hot spots in seconds and explore the situation analytics ecosystem - Answer- classification of sectors, technology/solution providers, and industry participants for analytics Big Data - Answer- -Data that is characterized by its volume, variety, and velocity that exceeds the reach of commonly used hardware environments and/or capabilities of software tools to process -data that cannot be stored or processed easily using traditional tools/means owing to its sheer volume Big Data Analytics - Answer- Applications of analytics methods and tools to Big Data What are the 3 "V"s of Big Data? - Answer- Volume, Variety, Velocity Analytics Ready Data - Answer- A state of preparedness for analytics projects, especially as it relates to data acquisition and preparedness Metrics that make for analytics-ready data - Answer- -Data source reliability -Data content accuracy -Data accessibility -Data security and data privacy -Data richness -Data consistency -Data currency/data timeliness -Data granularity -Data validity -Data relevancy data taxonomy - Answer- a structured representation of the sub-groups/subtypes of data Categorical data is: - Answer- -represents the labels of multiple classes used to divide a variable into specific groups. -can be divided into nominal or ordinal data Nominal Data - Answer- contains measurements of simple codes assigned to objects as labels, which are not measurements