ACC 271 Exam #1

Best practices in dashboard design

-Data is the most important attribute -Benchmark KPIs with industry standards -Wrap the dashboard metrics with contextual metadata -Validate the dashboard design by a usability specialist -Prioritize and rank alerts/exceptions streamed to the dashboard -Enrich the dashboard with business-user comments -Present information in three different levels -Pick the right visual construct using dashboard design principles -Provide for guided analytics

Characteristics that define the readiness of data for an analytics study

-Data source reliability -Data content accuracy -Data accessibility -Data security and privacy -Data richness -Data consistency -Data currency/timeliness -Data granularity -Data validity -Data relevancy

What has contributed to the growth of decision support and analytics?

-Group communication and collaboration -Improved data management -Managing giant data warehouses and big data -Analytical support -Overcoming cognitive limits in processing and storing information -Knowledge management -Anywhere, anytime support

What is true about metadata?

-Helps to describe the meaning and structure of data -Gives context to reported data -There may be ethical issues involved in the creation of metadata NOT TRUE: For most organizations, data warehouse metadata are an unnecessary expense

What are the three categories of business analytics?

-Predictive -Prescriptive -Descriptive

Anatomy of the analytics ecosystem

-The outer six petals are technology providers -The inner petals are analytics accelerators -The core is the analytics users organizations

Functions of business reports

-To ensure that all departments are functioning properly -To provide information -To provide the results of an analysis -To persuade others to act -To create an organizational memory (as part of a knowledge management team)

Four major components of BI

1. DW, with its source data 2. Business analytics 3. BPM, for monitoring and analyzing performance 4. A user interface (such as a dashboard)

Assumptions in linear regression

1. Linearity - linear, straight-line function 2. Independence - errors of the response variable are uncorrelated with each other 3. Normality - errors of the response variable are normally distributed 4. Constant variance - response variables have same variance in their error regardless of the values of the explanatory variables 5. Multicollinearity - Explanatory variables are not correlated

Major categories of business reports

1. Metric Management Reports 2. Dashboard-Type Reports 3. Balanced Scorecard-Type Reports

Three layers of information on a dashboard:

1. Monitoring - Graphical, abstracted data to monitor key performance metrics 2. Analysis - Summarized dimensional data to analyze the root cause of problems 3. Management - Detailed operational data that identify what actions to take to resolve a problem

Common dashboard design characeristics

1. They all fit within the larger BI and/or performance measurement system 2. They use visual components to highlight, at a glance, the data and exceptions that require action 3. They are transparent to the user, meaning they require minimal training and are extremely easy to use 4. They combine data from a variety of systems into a single, summarized, unified view of the business 5. They enable drill-down or drill-through to underlying data sources or reports, providing more detail about the underlying comparative and evaluative context 6. They present a dynamic, real-world view with timely data refreshes, enabling the end user to stay up to date with any recent changes in the business 7. They require little, if any, customized coding to implement, deploy, and maintain

Predictive Analysis

Aims to determine what is likely to happen in the future (foreseeing the future events) -Looking at the past data to predict the future -Data mining -Text mining/web mining -Forecasting (time series)

Online Analytical Processing (OLAP)

An information system that enables the user, while at a PC, to query the system, conduct an analysis, and son on. The result is generated in seconds

Business Intelligence

An umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologies; Descriptive analytics tools and techniques -Major objective is to enable interactive access (sometimes in real time) to data, enable manipulation of data, and give business managers and analysts the ability to conduct appropriate analyses

T/F: Business intelligence (BI) is a specific term that describes architectures and tools only

False

T/F: Successful BI is a tool for the information systems department, but is not exposed to the larger organization

False

T/F: The growth in hardware, software, and network capacities has had little impact on modern BI innocations

False

T/F: When telling a story during a presentation, it is best to avoid describing hurdles that your character must overcome, to avoid souring the mood

False

Which data warehouse architecture uses metadata from existing data warehouses to create a hybrid logical data warehouse comprised of data from the other warehouses?

Federated Architecture

In answering the question "Which customers are likely to be using fake credit cards?" you are most likely to use which of the following analytic applications?

Fraud Detection

Which type of visualization tool can be very helpful when a data set contains location data?

Geographic map

Prescriptive Analytics

Goal is to recognize what is going on as well as the likely forecast and make decisions to achieve the best performance possible -Uses both descriptive and predictive to create the alternatives, and then determines the best one -Optimization -Stimulation -Multi-Criteria Decision Modeling -Heuristic Programming

What are the uses of pivot tables?

Helps to summarize, analyze, explore, and present your data to help make better business decisions

Data warehouses provide direct and indirect benefits to using organizations. Which of the following is an indirect benefit of data warehouses?

Improved customer service

Which kind of data warehouse is created separately from the enterprise data warehouse by a department and not reliant on it for updates?

Independent Data Marts

Key performance indicators (KPIs) are metrics typically used to measure what?

Internal results

If a company's strategy is properly aligned with DW and BI initiatives, and the company's IS organization can be made capable of playing its role in such a project, and if the requisite user community is in place and has the proper motivation, then...

It is wise to start BI and establish a BI Competency Center (BICC) within the company

Descriptive Analytics

Knowing what is happening in the organization and understanding some underlying trends and causes of such occurrences -Answering the question of what happened -Retrospective analysis of historical data -Visualization -OLAP/DW

Which of the following developments is NOT contributing to facilitating growth of decision support and analytics?

Locally concentrated workforces

In the Magpie Sensing case study, the automated collection of temperature and humidity data on shipped goods helped with various types of analytics. Which of the following is an example of prescriptive analytics?

Optimal temperature setting

What type of analytics seeks to determine what is likely to happen in the future?

Predictive

Dashboards

Provide visual displays of important information that is consolidated and arranged on a single screen so that information can be digested at a single glance and easily drilled in and further explored

What is the role of a BICC center?

Responsible for ensuring the successful creation, rollout, and use of BI and PM systems throughout an enterprise 1. Program Management 2. Consistency and Standards 3. Delivery 4. Training 5. Support 6. Vendor Management 7. Data Stewardship 8. Governance

The competitive imperatives for BI include all of the following except...

Right user

Which of the following is not an example of transaction processing?

Sales report

Difference between OLTP and OLAP

The goal of OLTP is to capture data and the goal of OLAP is decision support

Analytics

The process of developing actionable decisions or recommendations for actions based on insights generated from historical data

Big Data often involves a form of distribution storage and processing using Hadoop and MapReduce. One reason for this is what?

The processing power needed for the centralized model would overload a single computer

Data visualization

The use of visual representations to explore, make sense of, and communicate data

Dashboards can be presented at all of the following levels except

The visual cube level -Can be presented at the visual dashboard, static report, and self-service cube levels

How are descriptive analytics methods different from the other two types?

They answer "what is?" queries, not "what will be?" queries

Online Transaction Processing (OLTP)

Transaction system that is primarily responsible for capturing and storing data related to day-to-day business functions

T/F: Data is the main ingredient for any BI, data science, and business analytics initiative

True

T/F: Descriptive statistics is all about describing the sample data on hand

True

T/F: During the early days of analytics, data was often obtained from the domain experts using manual processes to build mathematical or knowledge-based models

True

T/F: The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball case study, is an example of the effectiveness of prescriptive analytics

True

Time Series Forecasting

Use of mathematical modeling to predict future values of the variable of interest based on previously observed values

Structured Data

What data mining algorithms use and can be classified as categorical or numeric

Which kind of chart is described as an enhanced version of a scatter plot?

Bubble chart

What are the uses of the PMT function?

Calculates the payment for a loan based on constant payments and a constant interest rate PMT(rate, nper, pv, [fv], [type])

Visual analytics

Combination of visualization and predictive analytics; aimed at answering "why is this happening?" and "what is more likely to happen?"

Unstructured Data

Composed of any combination of textual, imagery, voice, and web content

Data preprocessing

Converts the raw real-world data into a well-refined form for analytics algorithms

Analytics Ecosystem

A classification of sectors, technology/solution providers, and industry participants for analytics

Data

A collection of facts usually obtained as the result of experiments, observations, transactions, or experiences

Regression

A data mining method for real-world prediction problems where the predicted values are numeric; can be used for two purposes: 1. Hypothesis testing - investigating potential relationships between different variables 2. Prediction/forecasting - estimating values of a response variable based on one or more explanatory variables

Data mining

A process that uses statistical, mathematical, artificial intelligence, and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases

Linear Regression

A relatively simple statistical technique to model the linear relationship between a response variable and one or more explanatory/input variables

Dashboard

A visual representation of critical data for executives to view. It allows executives to see hot spots in seconds and explore the situation

When you tell a story in a presentation, all of the following are true except

A well-told story should have no need for subsequent discussion

DW

Data Warehouse - A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format

What is the difference between a data analyst and a data scientist?

Data scientists have a higher degree of technical knowledge and skill sets

Big Data

Data that cannot be stored or processed easily using traditional tools/means; typically refers to data that comes in many different forms -Worthless if it does not provide business value, and for it to provide value, it has to be analyzed

Cornerstones of today's modern management

Data warehousing, data mining, OLAP, dashboards, and the use of cloud-based systems

DSS

Decision Support System - Interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems; DSSs couple the intellectual resources of individuals and with the capabilities of the computer to improve the quality of decisions

BI applications must be integrated with...

Enterprise systems, databases, and legacy systems (all of these)

Descriptive Statistics

Describes the basic characteristics of the data at hand, often one variable at a time; summarizes data in such a way that often meaningful and easily understandable patterns emerge from the study -Does not allow making conclusions beyond the sample being analyzed -Helps convert numbers and symbols into meaningful representations for anyone to understand and use

When querying a dimensional database, a user went from summarized data to its underlying details. The function that served this purpose is...

Drill down

What is the fundamental challenge of dashboard design?

Ensuring that the required information is shown clearly on a single screen