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Discussion: Please refer to the attachment Discussion#2_Question.pdf file for the question. The discussion should be a minimum of 300 words and should meet all the requirements given by the professor.

Paper:  Please refer to the attachment paper#2_Question.pdf file for the question. The paper should be a minimum of 4 pages excluding references and should meet all the requirements given by the professor. Especially in the conclusion section, I got the below comments from the professor please try to follow the guidelines and make sure to rectify the comments below.

Comments:  Thank you for taking the time to complete your assignment and based on my review, you did a good job on this assignment.  For example, you used multiple sources of research to support your case analysis and your conclusions were also good; however, do not forget to visually represent your ideas through the use of created diagrams which may represent any process or operation to support a potential solution to the cases.  As a suggestion, use the “Smart Art” tools in Microsoft Word and if you have never used these tools, you can find demonstrations at www.youtube.com using a keyword search “Microsoft Word Smart Art Tools.” 

9/1/2020 Graded Assignment: Knowledge and Skills Paper – Fall …

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Graded Assignment: Knowledge and Skills Paper

Fall 2020 – Business Intelligence (ITS-531-A05) – First Bi-Term Content Week 2: 08/31/2020 – 09/06/2020

Graded Assignment: Knowledge and Skills Paper

W2: Paper (Click Here to Submit)

1. Research some data warehouse vendors and obtain information about their products. Give special attention to vendors that provide tools for multiple purposes, such as Cognos, Software A&G, SAS Institute, and Oracle. Free online demos are available from some of these vendors. Download a demo or two and try them and describe your learning experience and review of this products.

2. Download an information visualization tool, such as Tableau, QlikView, or Spotfire. If your school does not have an educational agreement with these companies, then a trial version would be sufficient for this exercise. Use your own data (if you have any) or use one of the data sets that comes with the tool (they usually have one or more data sets for demonstration purposes). Study the data, come up with a couple of business problems, and use data and visualization to analyze, visualize, and potentially solve those problems.

3. Important Note:  With limited time for a college class, perfection is not expected but effort to be exposed to various tools with attempts to learn about them is critical when considering a career in information technology associated disciplines.

W2: Paper

Graded Assignment:  Knowledge and Skills Paper

Paper Section 1: Reflection and Literature Review

Using Microsoft Word and Professional APA format, prepare a professional written paper supported with three sources of research that details what you have learned from chapters 3 and 4.  This section of the paper should be a minimum of two pages. 

Paper Section 2:  Applied Learning Exercises

In this section of the professional paper, apply what you have learned from chapters 3 and 4 to descriptively address and answer the problems below.  Important Note:  Dot not type the actual written problems within the paper itself.

Important Note:  There is no specific page requirement for this section of the paper but make sure any content provided fully addresses each problem.

Paper Section 3:  Conclusions

After addressing the problems, conclude your paper with details on how you will use this knowledge and skills to support your professional and or academic goals. This section of the paper should be around one page including a custom and original process flow or flow diagram to visually represent how you will apply this knowledgehttps://ucumberlands.blackboard.com/webapps/blackboard/execute/courseMain?course_id=_131833_1https://ucumberlands.blackboard.com/webapps/blackboard/content/listContent.jsp?course_id=_131833_1&content_id=_2473515_1&mode=resethttps://ucumberlands.blackboard.com/webapps/blackboard/content/listContent.jsp?course_id=_131833_1&content_id=_2609948_1&mode=resethttps://ucumberlands.blackboard.com/webapps/assignment/uploadAssignment?content_id=_2609962_1&course_id=_131833_1&group_id=&mode=view

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going forward.  This customized and original flow process flow or flow diagram can be created using the “Smart Art” tools in Microsoft Word.

Paper Section 4:  APA Reference Page

The three or more sources of research used to support this overall paper should be included in proper APA format in the final section of the paper.

Paper Review and Preparation to submit for Grading

Please make sure to proof read your post prior to submission. This professional paper should be well written and free of grammatical or typographical errors. Also remember not to plagiarize!!!!!!!!!!!!

Important Reminder:  Assessment of discussion boards and other writing assignments account for 75% of overall grading and below are how grades will be assessed for this assignment:

Assessment Criteria Possible Points

Points Earned

Student included a minimum of “2” body pages of written content supported with “3” academic sources of research offering a detailed reflection and literature review of learning from chapters 3 and 4

18.75  

Student in scholarly detail addressed and answered all exercises or problems demonstrating application of knowledge and skills learned from chapters 3 and 4.

12.5  

Student in scholarly detail offered conclusions detailing how knowledge and skills learned from chapters 3 and 4 will support continued professional and academic growth.  Student also prepared process flow or flow diagrams to visualize these conclusions.

12.5  

Student included a paper professionally formatted using APA and free of grammar and spelling issues

6.25  

Student successfully completed and successfully submitted this paper by the Sunday due date.

12.5  

Total Earned points 62.5   Comments:   

9/1/2020 Graded Discussion: Chapter 1, 2, 3, and 4 Case Studies –…

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Graded Discussion: Chapter 1, 2, 3, and 4 Case Studies

Fall 2020 – Business Intelligence (ITS-531-A05) – First Bi-Term Content Week 2: 08/31/2020 – 09/06/2020

Graded Discussion: Chapter 1, 2, 3, and 4 Case Studies

W2: Discussion (Click Here To Post)

)

W2: Discussion Case Studies

Graded Assignment:  Case Studies – (Follow all steps below)

For students having last names beginning with A through M carefully review and read both end of chapter application cases from chapters 1 and 2 from the following required book for this class.

For students having last names beginning with N through Z carefully review and read both end of chapter application cases from chapters 3 and 4 from the following required book for this class.

Sharda, R., Delen, D., & Turban, E. (2015) Business intelligence and analytics: Systems for decision support (10th ed.). Boston: Pearson.

Digital: ISBN-13: 978-0-13-340193-6 or Print: ISBN-13: 978-0-13-305090-5

(

After reading and analyzing both case studies, address all case study questions found within the case studies in scholarly detail.  In addition to answering all case study questions, put yourself in these situational cases and what ideas would you have to make any operational processes or process flows better where associated in the decision-making process?

Discussion Expectations

Please make sure to proof read your post prior to submission. They should be well written and free of grammatical or typographical errors.

Initial postings are due by Wednesday. You are encouraged to post your follow-up comments to different students, and you can do more than two if you want and thesehttps://ucumberlands.blackboard.com/webapps/blackboard/execute/courseMain?course_id=_131833_1https://ucumberlands.blackboard.com/webapps/blackboard/content/listContent.jsp?course_id=_131833_1&content_id=_2473515_1&mode=resethttps://ucumberlands.blackboard.com/webapps/blackboard/content/listContent.jsp?course_id=_131833_1&content_id=_2609948_1&mode=resethttps://ucumberlands.blackboard.com/webapps/blackboard/content/launchLink.jsp?course_id=_131833_1&content_id=_2609959_1&mode=view

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peer replies are due by Saturday.  Postings should include scholarly detail with research support where appropriate

Important Reminder:  Assessment of discussion boards and other writing assignments account for 75% of overall grading and below are how grades will be assessed for this discussion board:

Assessment Criteria Possible Points

Points Earned

Student included an initial posting 18.75   Student included at least two peer replies. 12.5   Content in student postings is of rich descriptive details supported with research to support and move discussion topics forward in a collaborative environment.

18.75  

Student posted an initial posting by the Wednesday due date.

6.25  

Student posted at least two peer replies by the Saturday date.

6.25  

Total Earned points 62.5   Comments:   

hapter 3:

Data Warehousing

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

Copyright © 2014 Pearson Education, Inc.

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Learning Objectives

(Continued…)

Understand the basic definitions and concepts of data warehouses

Learn different types of data warehousing architectures; their comparative advantages and disadvantages

Describe the processes used in developing and managing data warehouses

Explain data warehousing operations

Copyright © 2014 Pearson Education, Inc.

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Learning Objectives

Explain the role of data warehouses in decision support

Explain data integration and the extraction, transformation, and load (ETL) processes

Describe real-time (a.k.a. right-time and/or active) data warehousing

Understand data warehouse administration and security issues

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Opening Vignette…

“Isle of Capri Casinos Is Winning with Enterprise Data Warehouse”

Company background

Problem description

Proposed solution

Results

Answer & discuss the case questions.

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Questions for the Opening Vignette

Why is it important for Isle to have an EDW?

What were the business challenges or opportunities that Isle was facing?

What was the process Isle followed to realize EDW? Comment on the potential challenges Isle might have had going through the process of EDW development.

What were the benefits of implementing an EDW at Isle? Can you think of other potential benefits that were not listed in the case?

Why do you think large enterprises like Isle in the gaming industry can succeed without having a capable data warehouse/business intelligence infrastructure?

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Main Data Warehousing Topics

DW definition

Characteristics of DW

Data Marts

ODS, EDW, Metadata

DW Framework

DW Architecture & ETL Process

DW Development

DW Issues

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What is a Data Warehouse?

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

“The data warehouse is a collection of integrated, subject-oriented databases designed to support DSS functions, where each unit of data is non-volatile and relevant to some moment in time”

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A Historical Perspective to Data Warehousing

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Characteristics of DWs

Subject oriented

Integrated

Time-variant (time series)

Nonvolatile

Summarized

Not normalized

Metadata

Web based, relational/multi-dimensional

Client/server, real-time/right-time/active

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Data Mart

A departmental small-scale “DW” that stores only limited/relevant data

Dependent data mart

A subset that is created directly from a data warehouse

Independent data mart

A small data warehouse designed for a strategic business unit or a department

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Other DW Components

Operational data stores (ODS)

A type of database often used as an interim area for a data warehouse

Oper marts – an operational data mart.

Enterprise data warehouse (EDW)

A data warehouse for the enterprise.

Metadata: Data about data.

In a data warehouse, metadata describe the contents of a data warehouse and the manner of its acquisition and use

Copyright © 2014 Pearson Education, Inc.

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Application Case 3.1

A Better Data Plan: Well-Established TELCOs Leverage Data Warehousing and Analytics to Stay on Top in a Competitive Industry

Questions for Discussion

What are the main challenges for TELCOs?

How can data warehousing and data analytics help TELCOs in overcoming their challenges?

Why do you think TELCOs are well suited to take full advantage of data analytics?

Copyright © 2014 Pearson Education, Inc.

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A Generic DW Framework

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13

Application Case 3.2

Data Warehousing Helps MultiCare Save More Lives

Questions for Discussion

What do you think is the role of data warehousing in healthcare systems?

How did MultiCare use data warehousing to improve health outcomes?

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DW Architecture

Three-tier architecture

Data acquisition software (back-end)

The data warehouse that contains the data & software

Client (front-end) software that allows users to access and analyze data from the warehouse

Two-tier architecture

First two tiers in three-tier architecture is combined into one

… sometimes there is only one tier?

Copyright © 2014 Pearson Education, Inc.

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15

DW Architectures

3-tier

architecture

2-tier

architecture

1-tier

Architecture

?

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16

Data Warehousing Architectures

Issues to consider when deciding which architecture to use:

Which database management system (DBMS) should be used?

Will parallel processing and/or partitioning be used?

Will data migration tools be used to load the data warehouse?

What tools will be used to support data retrieval and analysis?

Copyright © 2014 Pearson Education, Inc.

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A Web-Based DW Architecture

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18

Alternative DW Architectures

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19

Alternative DW Architectures

Each architecture has advantages and disadvantages!

Which architecture is the best?

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20

Ten factors that potentially affect the architecture selection decision

Information interdependence between organizational units

Upper management’s information needs

Urgency of need for a data warehouse

Nature of end-user tasks

Constraints on resources

Strategic view of the data warehouse prior to implementation

Compatibility with existing systems

Perceived ability of the in-house IT staff

Technical issues

Social/political factors

Copyright © 2014 Pearson Education, Inc.

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21

Teradata Corp. DW Architecture

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Data Integration and the Extraction, Transformation, and Load Process

ETL = Extract Transform Load

Data integration

Integration that comprises three major processes: data access, data federation, and change capture.

Enterprise application integration (EAI)

A technology that provides a vehicle for pushing data from source systems into a data warehouse

Enterprise information integration (EII)

An evolving tool space that promises real-time data integration from a variety of sources, such as relational or multidimensional databases, Web services, etc.

Copyright © 2014 Pearson Education, Inc.

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Data Integration and the Extraction, Transformation, and Load Process

Copyright © 2014 Pearson Education, Inc.

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ETL (Extract, Transform, Load)

Issues affecting the purchase of an ETL tool

Data transformation tools are expensive

Data transformation tools may have a long learning curve

Important criteria in selecting an ETL tool

Ability to read from and write to an unlimited number of data sources/architectures

Automatic capturing and delivery of metadata

A history of conforming to open standards

An easy-to-use interface for the developer and the functional user

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25

Data Warehouse Development

Data warehouse development approaches

Inmon Model: EDW approach (top-down)

Kimball Model: Data mart approach (bottom-up)

Which model is best?

Table 3.3 provides a comparative analysis between EDW and Data Mart approach

One alternative is the hosted warehouse

Copyright © 2014 Pearson Education, Inc.

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Application Case 3.5

Starwood Hotels & Resorts Manages Hotel Profitability with Data Warehousing

Questions for Discussion

How big and complex are the business operations of Starwood Hotels & Resorts?

How did Starwood Hotels & Resorts use data warehousing for better profitability?

What were the challenges, the proposed solution, and the obtained results?

Copyright © 2014 Pearson Education, Inc.

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Additional DW Considerations Hosted Data Warehouses

Benefits:

Requires minimal investment in infrastructure

Frees up capacity on in-house systems

Frees up cash flow

Makes powerful solutions affordable

Enables solutions that provide for growth

Offers better quality equipment and software

Provides faster connections

… more in the book

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Representation of Data in DW

Dimensional Modeling

A retrieval-based system that supports high-volume query access

Star schema

The most commonly used and the simplest style of dimensional modeling

Contain a fact table surrounded by and connected to several dimension tables

Snowflakes schema

An extension of star schema where the diagram resembles a snowflake in shape

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The ability to organize, present, and analyze data by several dimensions, such as sales by region, by product, by salesperson, and by time (four dimensions)

Multidimensional presentation

Dimensions: products, salespeople, market segments, business units, geographical locations, distribution channels, country, or industry

Measures: money, sales volume, head count, inventory profit, actual versus forecast

Time: daily, weekly, monthly, quarterly, or yearly

Multidimensionality

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30

Star versus Snowflake Schema

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Analysis of Data in DW

OLTP vs. OLAP…

OLTP (online transaction processing)

Capturing and storing data from ERP, CRM, POS, …

The main focus is on efficiency of routine tasks

OLAP (Online analytical processing)

Converting data into information for decision support

Data cubes, drill-down / rollup, slice & dice, …

Requesting ad hoc reports

Conducting statistical and other analyses

Developing multimedia-based applications

…more in the book

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OLAP vs. OLTP

Copyright © 2014 Pearson Education, Inc.

3-‹#›

OLAP Operations

Slice – a subset of a multidimensional array

Dice – a slice on more than two dimensions

Drill Down/Up – navigating among levels of data ranging from the most summarized (up) to the most detailed (down)

Roll Up – computing all of the data relationships for one or more dimensions

Pivot – used to change the dimensional orientation of a report or an ad hoc query-page display

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OLAP

Slicing Operations on a Simple Tree-Dimensional

Data Cube

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Variations of OLAP

Multidimensional OLAP (MOLAP)

OLAP implemented via a specialized multidimensional database (or data store) that summarizes transactions into multidimensional views ahead of time

Relational OLAP (ROLAP)

The implementation of an OLAP database on top of an existing relational database

Database OLAP and Web OLAP (DOLAP and WOLAP); Desktop OLAP,…

Copyright © 2014 Pearson Education, Inc.

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36

Technology Insights 3.2 Hands-On DW with MicroStrategy

A wealth of teaching and learning resources can be found at TUN portal

www.teradatauniversitynetwork.com

The available resource includes scripted demonstrations, assignments, white papers, etc…

Copyright © 2014 Pearson Education, Inc.

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DW Implementation Issues

Identification of data sources and governance

Data quality planning, data model design

ETL tool selection

Establishment of service-level agreements

Data transport, data conversion

Reconciliation process

End-user support

Political issues

… more in the book

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Successful DW Implementation Things to Avoid

Starting with the wrong sponsorship chain

Setting expectations that you cannot meet

Engaging in politically naive behavior

Loading the data warehouse with information just because it is available

Believing that data warehousing database design is the same as transactional database design

Choosing a data warehouse manager who is technology oriented rather than user oriented

… more in the book

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Failure Factors in DW Projects

Lack of executive sponsorship

Unclear business objectives

Cultural issues being ignored

Change management

Unrealistic expectations

Inappropriate architecture

Low data quality / missing information

Loading data just because it is available

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Massive DW and Scalability

Scalability

The main issues pertaining to scalability:

The amount of data in the warehouse

How quickly the warehouse is expected to grow

The number of concurrent users

The complexity of user queries

Good scalability means that queries and other data-access functions will grow linearly with the size of the warehouse

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41

Real-Time/Active DW/BI

Enabling real-time data updates for real-time analysis and real-time decision making is growing rapidly

Push vs. Pull (of data)

Concerns about real-time BI

Not all data should be updated continuously

Mismatch of reports generated minutes apart

May be cost prohibitive

May also be infeasible

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42

Enterprise Decision Evolution and Data Warehousing

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43

Real-Time/Active DW at Teradata

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Traditional versus Active DW

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DW Administration and Security

Data warehouse administrator (DWA)

DWA should…

have the knowledge of high-performance software, hardware and networking technologies

possess solid business knowledge and insight

be familiar with the decision-making processes so as to suitably design/maintain the data warehouse structure

possess excellent communications skills

Security and privacy is a pressing issue in DW

Safeguarding the most valuable assets

Government regulations (HIPAA, etc.)

Must be explicitly planned and executed

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The Future of DW

Sourcing…

Web, social media, and Big Data

Open source software

SaaS (software as a service)

Cloud computing

Infrastructure…

Columnar

Real-time DW

Data warehouse appliances

Data management practices/technologies

In-database & In-memory processing New DBMS

Advanced analytics

Copyright © 2014 Pearson Education, Inc.

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Free of Charge DW Portal for Teaching & Learning

www.TeradataStudentNetwork.com

Password to signup: <check with your instructor>

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48

End of the Chapter

Questions, comments

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49

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.

Copyright © 2014 Pearson Education, Inc.

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50

1970s1980s1990s2000s2010s

üMainframe computers

üSimple data entry

üRoutine reporting

üPrimitive database structures

üTeradata incorporated

üMini/personal computers (PCs)

üBusiness applications for PCs

üDistributer DBMS

üRelational DBMS

üTeradata ships commercial DBs

üBusiness Data Warehousecoined

üCentralized data storage

üData warehousing was born

üInmon, Building the Data Warehouse

üKimball, The Data Warehouse Toolkit

üEDW architecture design

üExponentially growing data Web data

üConsolidation of DW/BI industry

üData warehouse appliances emerged

üBusiness intelligence popularized

üData mining and predictive modeling

üOpen source software

üSaaS, PaaS, Cloud Computing

üBig Data analytics

üSocial media analytics

üText and Web Analytics

üHadoop, MapReduce, NoSQL

üIn-memory, in-database

Data

Sources

ERP

Legacy

POS

Other

OLTP/wEB

External

data

Select

Transform

Extract

Integrate

Load

ETL

Process

Enterprise

Data warehouse

Metadata

Replication

A

P

I

/

M

i

d

d

l

e

w

a

r

e

Data/text

mining

Custom built

applications

OLAP,

Dashboard,

Web

Routine

Business

Reporting

Applications

(Visualization)

Data mart

(Engineering)

Data mart

(Marketing)

Data mart

(Finance)

Data mart

(…)

Access

No data marts option

Tier 2:

Application server

Tier 1:

Client workstation

Tier 3:

Database server

Tier 1:

Client workstation

Tier 2:

Application & database server

Web

Server

Client

(Web browser)

Application

Server

Data

warehouse

Web pages

Internet/

Intranet/

Extranet

Source

Systems

Staging

Area

Independent data marts

(atomic/summarized data)

End user

access and

applications

ETL

Source

Systems

Staging

Area

End user

access and

applications

ETL

Dimensionalized data marts

linked by conformed dimensions

(atomic/summarized data)

Source

Systems

Staging

Area

End user

access and

applications

ETL

Normalized relational

warehouse (atomic data)

Dependent data marts

(summarized/some atomic data)

(a) Independent Data Marts Architecture

(b) Data Mart Bus Architecture with Linked Dimensional Datamarts

(c) Hub and Spoke Architecture (Corporate Information Factory)

Source

Systems

Staging

Area

Normalized relational

warehouse (atomic/some

summarized data)

End user

access and

applications

End user

access and

applications

Logical/physical integration of

common data elements

Existing data warehouses

Data marts and legacy systems

ETL

Data mapping / metadata

(d) Centralized Data Warehouse Architecture

(e) Federated Architecture

Packaged

application

Legacy

system

Other internal

applications

Transient

data source

ExtractTransformCleanseLoad

Data

warehouse

Data mart

Fact Table

SALES

UnitsSold

Dimension

TIME

Quarter

Dimension

PEOPLE

Division

Dimension

PRODUCT

Brand

Dimension

GEOGRAPHY

Country

Fact Table

SALES

UnitsSold

Dimension

DATE

Date

Dimension

PEOPLE

Division

Dimension

PRODUCT

LineItem

Dimension

STORE

LocID

Dimension

BRAND

Brand

Dimension

CATEGORY

Category

Dimension

LOCATION

State

Dimension

MONTH

M_Name

Dimension

QUARTER

Q_Name

Star SchemaSnowflake Schema

Product

T

i

m

e

G

e

o

g

r

a

p

h

y

Sales volumes of

a specific Product

on variable Time

and Region

Sales volumes of

a specific Region

on variable Time

and Products

Sales volumes of

a specific Time on

variable Region

and Products

Cells are filled

with numbers

representing

sales volumes

A 3-dimensional

OLAP cube with

slicing

operations

Chapter 4:

Business Reporting,

Visual Analytics, and Business

Performance Management

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

Copyright © 2014 Pearson Education, Inc.

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Learning Objectives

Define business reporting and understand its historical evolution

Recognize the need for and the power of business reporting

Understand the importance of data/information visualization

Learn different types of visualization techniques

Appreciate the value that visual analytics brings to BI/BA

(Continued…)

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Learning Objectives

Know the capabilities and limitations of dashboards

Understand the nature of business performance management (BPM)

Learn the closed-loop BPM methodology

Describe the basic elements of balanced scorecards

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Opening Vignette…

Self-Service Reporting Environment Saves Millions For Corporate Customers

Background

Business Challenge

Solution

Results

Answer & discuss the case questions.

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4

Questions for the Opening Vignette

What does Travel and Transport, Inc., do?

Describe the complexity and the competitive nature of the business environment in which Travel and Transport, Inc., functions.

What were the main business challenges?

What was the solution? Implementation?

Why do you think a multi-vendor, multi-tool solution was implemented?

List and comment on three main benefits of the implemented system.

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Business Reporting Definitions and Concepts

Report = Information  Decision

Report?

Any communication artifact prepared to convey specific information

A report can fulfill many functions

To ensure proper departmental functioning

To provide information

To provide the results of an analysis

To persuade others to act

To create an organizational memory…

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6

What is a Business Report?

A written document that contains information regarding business matters.

Purpose: to improve managerial decisions

Source: data from inside and outside the organization (via the use of ETL)

Format: text + tables + graphs/charts

Distribution: in-print, email, portal/intranet

Data acquisition  Information generation  Decision making  Process management

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Business Reporting

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Key to Any Successful Report

Clarity …

Brevity …

Completeness …

Correctness …

Report types (in terms of content and format)

Informal – a single letter or a memo

Formal – 10-100 pages; cover + summary + text

Short report – periodic, informative, investigative

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Application Case 4.1

Delta Lloyd Group Ensures Accuracy and Efficiency in Financial Reporting

Questions for Discussion

How did Delta Lloyd Group improve accuracy and efficiency in financial reporting?

What were the challenges, the proposed solution, and the obtained results?

Why is it important for Delta Lloyd Group to comply with industry regulations?

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Types of Business Reports

Metric Management Reports

Help manage business performance through metrics (SLAs for externals; KPIs for internals)

Can be used as part of Six Sigma and/or TQM

Dashboard-Type Reports

Graphical presentation of several performance indicators in a single page using dials/gauges

Balanced Scorecard-Type Reports

Include financial, customer, business process, and learning & growth indicators

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Components of Business Reporting Systems

Common characteristics

OLTP (online transaction processing)

ERP, POS, SCM, RFID, Sensors, Web, …

Data supply (volume, variety, velocity, …)

ETL

Data storage

Business logic

Publication medium

Assurance

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Application Case 4.2

Flood of Paper Ends at FEMA

Questions for Discussion

What is FEMA and what does it do?

What are the main challenges that FEMA faces in delivering its services?

How did FEMA improve its inefficient reporting practices?

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Data and Information Visualization

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

Data visualization vs. Information visualization

Information = aggregation, summarization, and contextualization of data

Related to information graphics, scientific visualization, and statistical graphics

Often includes charts, graphs, illustrations, …

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Application Case 4.3

Tableau Saves Blastrac

Thousands of Dollars with

Simplified Information Sharing

Questions for Discussion

How did Blastrac achieve significant cost saving in reporting and information sharing?

What were the challenge, the proposed solution, and the obtained results?

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A Brief History of Data Visualization

Data visualization can date back to the second century AD

Most developments have occurred in the last two and a half centuries

Until recently it was not recognized as a discipline

Today’s most popular visual forms date back a few centuries

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The First Pie Chart Created by William Playfair in 1801

William Playfair is widely credited as the inventor of the modern chart, having created the first line and pie charts.

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Decimation of Napoleon’s Army During the 1812 Russian Campaign

Arguably the most popular multi-dimensional chart

By Charles Joseph Minard

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A Brief History of Data Visualization

1900s –

more formal attitude toward visualization

focus on color, value scales, and labeling

Publication of the book Semiologie Graphique

2000s –

Emergence of Internet as the medium for information visualization  raising visual literacy

Incorporate interaction, animation, 3D graphics-rendering, virtual worlds, real-time data feed

2010s and beyond – ?

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Application Case 4.4

TIBCO Spotfire Provides Dana-Farber Cancer Institute with Unprecedented Insight into Cancer Vaccine Clinical Trials

Questions for Discussion

How did Dana-Farber Cancer Institute use TIBCO Spotfire to enhance information reporting and visualization?

What were the challenges, the proposed solution, and the obtained results?

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Different Types of Charts and Graphs

Which one to use? Where and when?

Specialized Charts and Graphs

Histogram

Gantt Chart

PERT Chart

Geographic Map

Bullet Graph

Heat Map / Tree Map

Highlight Table

Basic Charts and Graphs

Line Chart

Bar Chart

Pie Chart

Scatter Plot

Bubble Chart

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A Gapminder Chart Wealth and Health of Nations

See gapminder.org for

interesting animated examples

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The Emergence of Data Visualization And Visual Analytics

Magic Quadrant for Business Intelligence and Analytics Platforms (Source: Gartner.com)

Many data visualization companies are in the 4th quadrant

There is a move toward visualization

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The Emergence of Data Visualization And Visual Analytics

Emergence of new companies

Tableau, Spotfire, QlikView, …

Increased focus by the big players

MicroStrategy improved Visual Insight

SAP launched Visual Intelligence

SAS launched Visual Analytics

Microsoft bolstered PowerPivot with Power View

IBM launched Cognos Insight

Oracle acquired Endeca

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Visual Analytics

A recently coined term

Information visualization + predictive analytics

Information visualization

Descriptive, backward focused

“what happened” “what is happening”

Predictive analytics

Predictive, future focused

“what will happen” “why will it happen”

There is a strong move toward visual analytics

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Visual Analytics by SAS Institute

SAS Visual Analytics Architecture

Big data + In memory + Massively parallel processing + ..

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Visual Analytics by SAS Institute

At teradatauniversitynetwork.com, you can learn more about SAS VA, experiment with the tool

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Performance Dashboards

Performance dashboards are commonly used in BPM software suites and BI platforms

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

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Performance Dashboards

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Performance Dashboards

Dashboard design

The fundamental challenge of dashboard design is to display all the required information on a single screen, clearly and without distraction, in a manner that can be assimilated quickly

Three layer of information

Monitoring

Analysis

Management

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Application Case 4.6

Saudi Telecom Company Excels with Information Visualization

Questions for Discussion

Why do you think telecommunication companies are among the prime users of information visualization tools?

How did Saudi Telecom use information visualization?

What were their challenges, the proposed solution, and the obtained results?

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Application Case 4.6

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Performance Dashboards

What to look for in a dashboard

Use of visual components to highlight data and exceptions that require action.

Transparent to the user, meaning that they require minimal training and are extremely easy to use

Combine data from a variety of systems into a single, summarized, unified view of the business

Enable drill-down or drill-through to underlying data sources or reports

Present a dynamic, real-world view with timely data

Require little coding to implement/deploy/maintain

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Best Practices in Dashboard Design

Benchmark KPIs with Industry Standards

Wrap the Metrics with Contextual Metadata

Validate the Design by a Usability Specialist

Prioritize and Rank Alerts and Exceptions

Enrich Dashboard with Business-User Comments

Present Information in Three Different Levels

Pick the Right Visual Constructs

Provide for Guided Analytics

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Business Performance Management (BPM)

Business Performance Management (BPM) is…

A real-time system that alerts managers to potential opportunities, impending problems and threats, and then empowers them to react through models and collaboration.

Also called corporate performance management (CPM by Gartner Group), enterprise performance management (EPM by Oracle), strategic enterprise management (SEM by SAP)

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Business Performance Management (BPM)

BPM refers to the business processes, methodologies, metrics, and technologies used by enterprises to measure, monitor, and manage business performance.

BPM encompasses three key components

A set of integrated, closed-loop management and analytic processes, supported by technology …

Tools for businesses to define strategic goals and then measure/manage performance against them

Methods and tools for monitoring key performance indicators (KPIs), linked to organizational strategy

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A Closed-Loop Process to Optimize Business Performance

Process Steps

Strategize

Plan

Monitor/analyze

Act/adjust

Each with its own process steps

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Strategize: Where Do We Want to Go?

Strategic planning

Common tasks for the strategic planning process:

Conduct a current situation analysis

Determine the planning horizon

Conduct an environment scan

Identify critical success factors

Complete a gap analysis

Create a strategic vision

Develop a business strategy

Identify strategic objectives and goals

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Plan: How Do We Get There?

Operational planning

Operational plan: plan that translates an organization’s strategic objectives and goals into a set of well-defined tactics and initiatives, resources requirements, and expected results for some future time period (usually a year).

Operational planning can be

Tactic-centric (operationally focused)

Budget-centric plan (financially focused)

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Monitor/Analyze: How Are We Doing?

A comprehensive framework for monitoring performance should address two key issues:

What to monitor?

Critical success factors

Strategic goals and targets

How to monitor?

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Success (or mere survival) depends on new projects: creating new products, entering new markets, acquiring new customers (or businesses), or streamlining some process.

Many new projects and ventures fail!

What is the chance of failure?

60% of Hollywood movies fail

70% of large IT projects fail, …

Act and Adjust: What Do We Need to Do Differently?

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Application Case 4.7

IBM Cognos Express Helps Mace for Faster and Better Business Reporting

Questions for Discussion

What was the reporting challenge Mace was facing? Do you think this is an unusual challenge specific to Mace?

What was the approach for a potential solution?

What were the results obtained in the short term, and what were the future plans?

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Performance measurement system

A system that assists managers in tracking the implementations of business strategy by comparing actual results against strategic goals and objectives

Comprises systematic comparative methods that indicate progress (or lack thereof) against goals

Performance Measurement

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Key performance indicator (KPI)

A KPI represents a strategic objective and metrics that measure performance against a goal

Distinguishing features of KPIs

KPIs and Operational Metrics

Strategy

Targets

Ranges

Encodings

Time frames

Benchmarks

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Key performance indicator (KBI)

Outcome KPIs vs. Driver KPIs

(lagging indicators (leading indicators

e.g., revenues) e.g., sales leads)

Operational areas covered by driver KPIs

Customer performance

Service performance

Sales operations

Sales plan/forecast

Performance Measurement

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Balanced Scorecard (BSC)

A performance measurement and management methodology that helps translate an organization’s financial, customer, internal process, and learning and growth objectives and targets into a set of actionable initiatives

“The Balanced Scorecard: Measures That Drive Performance” (HBR, 1992)

Performance Measurement System

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Balanced Scorecard

The meaning of “balance” ?

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Six Sigma

A performance management methodology aimed at reducing the number of defects in a business process to as close to zero defects per million opportunities (DPMO) as possible

Six Sigma as a Performance Measurement System

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The DMAIC performance model

A closed-loop business improvement model that encompasses the steps of defining, measuring, analyzing, improving, and controlling a process

Lean Six Sigma

Lean manufacturing / lean production

Lean production versus six sigma?

Six Sigma as a Performance Measurement System

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Comparison of Balanced Scorecard and Six Sigma

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Application Case 4.8

Expedia.com’s Customer Satisfaction Scorecard

Questions for Discussion

Who are the customers for Expedia.com? Why is customer satisfaction a very important part of their business?

How did Expedia.com improve customer satisfaction with scorecards?

What were the challenges, the proposed solution, and the obtained results?

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End of the Chapter

Questions, comments

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All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.

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Data

Repositories

Business Functions

UOB 1.0X

UOB 2.2

UOB 2.1XUOB 3.0

1

Machine

Failure

SymbolCountDescription

Exception Event

Transactional Records

PHASE 5

DEPT 4

DEPT 3

DEPT 2

DEPT 1

PHASE 4PHASE 3PHASE 2PHASE 1

DEPLOYMENT CHART

1

2

3

4

5

Information

(reporting)

Decision

Maker

Action

(decision)

Data

ITS 531: Business Intelligence

Week 2: Video Lecture

Lecture Objectives

During this lecture, we will:

Go over concepts of data warehouses, business reporting, visual analytics, and performance management.

Go over and review discussion expectations for week 2.

ITS 531: Data Warehouses

Data Warehouses (Part 1)

In the realm of business intelligence, it is always good to understand the fundamental concepts of data warehouses. For example:

One characteristic of a data warehouse is that these systems are subject oriented where data is organized by detailed subject, such as sales, products, or customers, containing only information relevant for decision support.

Another characteristic of a data warehouse is that these systems are integrated. For example, data warehouses must place data from dissimilar sources into a reliable format. Furthermore, data warehouses must deal issues associated with naming conflicts and discrepancies among units of measure in essence to be totally integrated.

Data warehouses are also based on time variances. For example, the data in a data warehouse does not necessarily provide a current status unless the technology driven system is real-time. Data warehouses also detect trends, deviations, and long-term relationships for forecasting and comparisons, leading to decision making which is the very foundation of the most important benefit of business intelligence. Even more, every data warehouse has a time-based quality which is a dimension where data for analysis from multiple sources contains multiple time points.

Another characteristic of a data warehouse is that these technology driven information systems are nonvolatile meaning that after data is entered, users of the system cannot change or update the data.

An important benefit of today’s data warehouses is that many are based on web-based technology which creates efficient computing environment.

The design of data warehouses is based on either the relational or the multidimensional model and structure. In addition, the architecture of these technology driven data warehouses have focus on client/server uses which promote efficiency and good productivity for end users.

In addition, data warehouses of today’s technology advancements support real time activities for data access and data analysis.

Data warehouses of today technology era also includes a data form known as meta data which is data about data. In other words, a user would understand how the data is organized and how to best use the data for data analysis to support the decision making process.

Data Warehouses (Part 2 – Processing)

To continue with our foundations of data warehousing, it is good to understand some of the processes used by data warehouses. For example:

Data warehouses must deal with data sources where data is sourced from multiple independent and operational systems and some of these systems could be from external data providers. Data may also come from online transaction processing (OLTP) and Enterprise Resource Planning (ERP) systems.

When data is extracted from a data warehouse for the intentions of transformation into usable business intelligence, the transformation process happens with the support ETL software which is based on three database functions including extraction, transformation, and lading.

Another important processing feature of a data warehouse is data loading. In this process, data is loaded into a staging area, where the data is converted and cleansed. After this process is complete, the data would be ready to load into the data warehouse and in some cases a data mart.

Once a data warehouse is in is comprehensive state, this would be the processing capability as a EDW or an enterprise data warehouse where the technology driven information system, in this case, supports all decision analysis by providing relevant summarized and detailed information originating from many different sources.

In addition, a data warehouse will support processing from many software programs to support the process of metadata for organizing data summaries which are easy to index and search, especially with Web tools.

As with any major database architecture, the internal structure of these systems will be protected and middleware tools will be used to allow or enable access. There are many front-end applications that business users can use to interact with data stored in the data repositories, including data mining, OLAP, reporting tools, and data visualization tools.

Data Warehouses (Part 3– The Future)

To continue with our foundations of data warehousing, it is good to see what the future holds for data warehousing. For example below are areas of research everyone may find interesting to explore:

Data Warehouse sourcing using the following technology:

Web, social media, and Big Data

Open source software

SaaS (software as a service)

Cloud computing

Data Warehouse infrastructures base on:

Columnar (Based on storage and access)

Real-time data warehousing

Data warehouse appliances

Data management technologies and practices

In-database processing technology

In-memory storage technology

New database management systems

Advanced analytics

ITS 531: Data Warehouses (SQL Server)

Data Warehouses (SQL Server Demonstration)

For anyone that plans to focus in a career of business intelligence and data analytics may find it very beneficial to explore the SQL language. Below are free learning resources found over the internet:

SQL Server Courses, (2018). Microsoft’s Virtual Academy. Retrieved from https://mva.microsoft.com/product-training/sql-server#!lang=1033

SQL Tutorial, (1999 – 2018). W3schools.com. Retrieved from https://www.w3schools.com/sql/

SQL Tutorial, (2018). Tutorials Point: Simply Easy Learning. Retrieved from https://www.tutorialspoint.com/sql/

SQL Tutorial, (2004 – 2015). Art Branch Inc. Retrieved from http://www.sql-tutorial.net/

SQL Tutorial, (2018). Geeks for Geeks. Retrieved from https://www.geeksforgeeks.org/sql-tutorial/

SQL Tutorial (2018). Mode. Retrieved from https://community.modeanalytics.com/sql/tutorial/introduction-to-sql/

For video demonstrations, everyone might be amazed at what can be located at www.youtube.com using the following keyword searches.

SQL and SQL Server Tutorials

SQL and MySQL Tutorials

SQL and Oracle Tutorials

SQL and Microsoft Access Tutorials

ITS 531: Business Reporting

Business Reporting (Part 1 – Report Types)

In the realm of business intelligence, there are several ways businesses and organization use reports and below are some major uses. For example:

One type of report used in these cases is a metric management report. For example, an organization that use this type of report will accomplish business performance through outcome-oriented metrics. For external groups, these are service-level agreements (SLAs). For internal management, they are key performance indicators (KPIs).

Important Note: All students should conduct further research to see uses and application of service-level agreements (SLAs) and key performance indicators (KPIs) as used by any organization or business.

Another type of report an organization will use is reports in the dashboard format. These types of reports will offer a wide assortment of diverse performance indicators on one page, like a dashboard in a vehicle. Characteristically, developed dashboards will have predefined reports with static components and stationary structures. At the same time, customizations are always possible within a dashboard depending on available technology driven programs.

When looking at the customization and design of a dashboard, below are some key areas to consider:

Benchmark key performance indicators 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 users’ comments

Present information in different levels for best support

Pick the right visual construction using dashboard design principles

Provide a medium for guided analytics

Furthermore, another type of report that organizations and businesses will use are balanced score cards. When an organization or business uses balanced score cards, they are looking and applying an integrated view of success in the organization. The scorecard measurements can show all sorts of information based on customers, business processes, and future growth potentials to name a few.

Business Reporting (Part 2 – Best Practices)

As we continue with a foundation of business reporting, it is good to understand and explain the importance of Reports to an organization. Who typically reads the reports, and what use is made of reports? Who is responsible for delivering the content of reports?

When it comes to report design, there could always be some variance toward best practices depending on personal and professional preferences and even expectations when reports are used in an official work environment. Regardless, good reports will typically follow some or all of the following not limited to:

Reports when prepared, by a data scientist or data analyst, should always have scale and balance between textual content and any illustrations.

Reports should offer enhanced formatting in efforts to draw attention to key areas of the report. This could be as simple as using bold formatting for report headings.

Reports especially when associated with data analysis and data analytics should be enhanced with visualizations. These visualizations could be the use of charts.

In association more with charts, these are very important visualizations and can help any entity in an organization or business make better decisions. Common types of charts used in these cases include and is not limited to;

Histograms

Gantt charts

Column and Bar charts

PERT charts

Pie charts

Geographic maps

Bullets

Heat maps

Highlight tables

Tree maps and Decision Trees

Any may more

Regardless of overall presentation and format, reports are very important to any organization as data within will help managers, leadership, or any other entity that reviews the report to make better decisions.

ITS 531: Visual Analytics and Performance Management

Visual Analytics and Performance Management

In the realm of business intelligence, the support of data analytics is cortical in the decision making process and to support this process, we have visual analytics. For example,

The development of visual analytics associates with the growth of analytics in a fundamental and universal way.

Vendors that develop business intelligence and data analytic applications are seeing their customers require quick and preferably interactive visualizations, not just for their normal reporting systems, but also to illustrate predictive and prescriptive decision-making information.

The use of predictive and prescriptive decision-making methods are becoming more and more cortical because big data is everywhere and most organizations and businesses, with the capabilities, are using big data to be competitive based on offered services and products where applicable to customers.

In the realm of business intelligence, performance is really all that matters because competition is very high among organizations that may offer similar services and products. When it comes to general performance, below are performance measures an organization and or business should consider, not limited to:

Measurements that focus on key factors.

Measurements that mix and or compare past, present, and future data analytics.

Measurements that support needs of shareholders, employees, partners, suppliers, and other stakeholders but in harmony and balance.

Measurements showing top/down approaches

Measurements showing targets based on research and reality with the avoidance of arbitrary data or research.

Visual Analytics and Performance Management

Going even futher when thinking about the very nature of reports and visual analytics, always remember that:

A report is a communication object equipped with the precise purpose of relaying information in a presentable form and if the report concerns business or organizational matters, then it is called a business report.

Business and organizational reporting is a vital part of the business intelligence process toward improving managerial decision making. In other words, we use technology to help us prepare reports but it is what we do with the reports to support the decision making process.

Furthermore, these reports are more visually adapted to, often using colors and graphical icons that cooperatively look like a dashboard to enhance the information content. In these visual oriented reports, charts are one of the most common types of visual elements.

Business reporting with the aid of various technologies will enable business intelligence and analytics as a decision support tool and when done analytically, these reports are collected with integrated sets of processes, methodologies, metrics, and applications intended to drive the overall business and operative performance of a business or organization.

In other words, well designed reports which have raw data from a database transformed into usable business intelligence can help and business or organization translate strategies and objectives into plans, monitor performance against those plans, analyze variations between actual results and planned results, and adjust their objectives and actions in response to this analysis.

ITS 531: Week 2 Discussion – Case Studies

ITS 531: Week 2 Discussion (Cast Study – Tips) — 

For the week 2 discussion, we will be looking at and discussing the application case studies of chapters 1, 2, 3, and 4 and for the first case of chapter 1, think about the following questions:

Why would an organization need an enterprise-wide data warehouse?

In this case, things to potentially consider would be:

Duplication in the process gathering data

Data processing methods that are not consistent or uniform

Data redundancies

Operating cost to manage data is high

What could be the business value of integrated data?

In this case, integrated data could potentially do the following:

Improve marketing

Improve communications

Improve customer satisfaction correlating to increase sales

Improve data reporting correlating to better decision making

What forms of analytics are used?

In this case, analytics to discuss could potentially include:

Descriptive analytics

Predictive analytics

And prescriptive analytics

What other data applications could be developed in this case?

In this case, thinking about a business environment, other application tools could include:

Pricing of products

Regulatory compliance

Hiring and payroll

Risk management

Facilities management

ITS 531: Week 2 Discussion (Cast Study – Tips) — 

For the 2nd case of chapter 2, think about the following questions:

Why would an organization want to solve logistic problems with storage?

In this case, and when dealing with logistic problems with storage, always remember that space not typically used is wasted space and reducing wasted space issues will greatly improve spending and operational efficiency.

What could be some benefits of using optimization or other mathematical based models?

In this case, always remember that all mathematical based models including the optimization model can be used in so many ways to help organizations boost efficiency along with more flexibility of operations. In addition, these models can help organizations achieve better quality and safety and a better process of securing resources.

It should also be noted that forecasting models can help organizations reduce errors.

Could Empty Container Logistics Optimization (ECO) help other organizations having problems with empty storage?

When researching ECO in this case, think about the industry as a whole and that there could always be variance in every work condition and environment. At the same time, strategies, heuristics, and intelligent systems are always being tested and suggested to tackle these complex problems.

Could Empty Container Logistics Optimization (ECO) be applied to other domains?

In this case, always remember that several industries will have complex logistic issues well beyond storage and shipping and with limited resources, in many of these cases, the ECO idea could easily be applied to help industries with scheduling, inventory management, routing, and work flow and many other domains.

ITS 531: Week 2 Discussion (Cast Study – Tips) — 

For the third case of chapter 3, think about the following questions:

What are the benefits of implementing the Continental Go Forward strategy.?

In this case, things to potentially consider would be:

Restoring profitability

Better industry metrics

Reducing any occurrences of fraud

The role of a data warehouse in support of this case

What be some benefits of a real-time data warehouse?

In this case, things to potentially consider would be:

Improved decision making relying on data that is current and not old

Improved communications

Improved operations

Improved customer support

What are the major differences between the traditional data warehouse and a real-time data warehouse?

In this case, things to potentially consider would be:

A traditional data warehouse moves data from operational databases to a data warehouse on a scheduled basis, typically daily or weekly. This is a consistent process; however, data is never current and could be as old as week and in some cases longer.

A real time data warehouse works the same as the traditional with the exception that data is moved from and updated from databases on a more current time cycle. For example and instead of days or weeks, data is updated to the data warehouse, in most cases, on an hourly basis making data analysis to support decision making more reliable.

What are advantages of real-time system?

In this case, things to potentially consider would be :

Decisions are made based on current and up to date information.

Decisions become more strategic in nature and can be distributed across all levels with information that is more reliable being current.

ITS 531: Week 2 Discussion (Cast Study – Tips) — 

For the 4th case of chapter 4, think about the following questions:

What is Premier?

In this case, think about and do research on various health care services which can be used to help hospitals improve cost controls and quality of services.

What are challenges in this case?

In this case, discuss based on experience and or research issues when technology driven information systems do not offer scalability to handle various transactions.

Also in this case, think about ideas for technology and needed infrastructures to handle large or massive volumes of data.

What could be some solutions?

In this case, think about a new platform to be designed to deliver trusted information in the right context at the right time to users based on their roles.

In addition, this platform will need to be able to use a portal to access integrated systems for various clinical, business, and compliance-related applications in order to help the healthcare organizations provide their staff with accurate and timely information to support evidence-based, patient-centric, and accountable care.

Are there any other benefits from integrated systems?

In this case, always remember that potential benefits for saving lives, helping people enjoy healthier lives, and reducing healthcare costs are enormous and any technology which is integrated to do this is always a benefit.

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stuff!

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