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Management of Information (Chapter 5.IT Infrastructure:Hardware and…
Management of Information
Chapter 5.IT Infrastructure:Hardware and Software
Components of IT infrastructure
Computer Hardware
Computer Software
Application Software
applies the computer to a specific task for an end user
System Software
manages the resources and activities of the computer
Data Management Technology
Networking and Telecommunications Technology
Technology Services
Types of computers
personal computer(PC)
workstation
server
Mainframe computers
Supercomputer
Grid computing(網狀計算)
By using the
combined power of thousands of PCs
and other computers networked together, the grid can solve complicated problems at supercomputer speeds at
far lower costs
Computer networks and Client/Server Computing
distributed processing
is client/server computing
splits processing between clients and servers
Client (Request)→ Server
Client ← (Data and services) Server
↑ is called a
two-tiered clients/server architecture
the more complicated one can be called N-tier client/server architectures
EX:
Client ←internet→ Web server ←→ Application server ←→ Sales Production Accounting HR ←→ Data
Centralized processing
all processing is accomplished by one large central computer
Storage,Input,and output technology
devices are called :
peripheral devices(外圍設備)
Secondary Storage Technology
Magnetic disks
most widely used
ex:hard drives, multiple hard disk drives
solid state drives(SSDs 固態硬碟)
use
an array of semiconductors organized as an internal disk drive
. the portable USB flash drives use the similar technology
Optical Discs
use
laser technology
to store large quantities of data,including sound and images, in a highly compact form
CD-ROM(compact disc read-only memory) 660mb
CD-RW(CD-rewritable)
DVDs(Digital video discs) 4.7gb
Magnetic Tape(磁碟)
is slow compared to the other secondary storage technology
Storage Networking
ex:SANs(Storage area networks)
connect multiple storage devices on a separate high-speed network dedicated to the storage
Input and Output devices
Input devices
Keyboard
Touch screen
Audio input
...
Output devices
Display
Printers
Audio output
let human beings interact with computers
Contemporary hardware trends
Consumerization of IT and BYOD
BYOD - bring your own device
Nanotechnology(奈米科技) and Quantum Computing(量子計算)
Nanotechnology
to shrink the size of transistors to the width of several atoms
use individual atoms and molecules to create computer chips and other devices that are
thousands of times smaller
than current technologies permit
purpose :
enhancing the computer processing power
Quantum computing
perform multiple operations simultaneously and solve some scientific and business problems
millions of times faster
than can be done today
Virtualization
df: is the process of presenting a set of computing resources(data storage...) so that they all can be accessed in ways that are
not restricted by physical configuration or geographic location
ex:enables multiple physical resources to appear as a single logical resource
can boost server usage
, so higher usage means that the company needs fewer computers to process the same amount of work
Cloud Computing
df: is a model of computing in which computer processing, storage, software, and other services are provided as a
shared pool of virtualized resources over a network
NIST df essential characteristics
On-demand self-service
Ubiquitous network access
Location-independent resource pooling
Rapid elasticity
Measured service
service types
Infrastructure as a service(IaaS)
Customers use
processing, storage, networking and other computing resources
from cloud service provider to run their ITS
ex:Amazon sold their spare capacity of it IT for other company
Software as a service(SaaS)
ex: iCloud, Google drive
Platform as a service(PaaS)
ex: IBM Bluemix
Hybrid cloud(混合雲)
who ? Large company
why ? reduce the risks of losing the critical resources
How ? they use
their own infrastructure for their most essential core activities
and adopt
public cloud computing for less-critical systems
or for additional processing capacity during peak business periods.
Green Computing
literally ...
High-Performance and Power-Saving Processors
to reduce power requirements and hardware sprawl
multicore processor
is an integrated circuit to which
two or more processor cores have been attached
for enhanced performance reduced power consumption and more efficient simultaneous processing of multiple tasks
Operating System Software
df: manages and controls the computer's activities
is the computer system's chief manager
PC, Server, and Mobile Operating Systems
GUI(graphical user interface)
is used by PC operating system and many types of application software
makes extensive use of icons, buttons ...
The major types of computer software used in business and the major software trends
Application software and desktop productivity tools
Programming languages for Business
C
C++
Java
Software Packages and Desktop Productivity Tools
Spreadsheet - Excel
Presentation graphics - PPT
Personal information management - Outlook
...
HTML and HTML5
HTML(Hypertext Markup Language)
df : is page description language for specifying how text, graphics, video, and sound are placed on a web page and ...
HTML5
most recent version of HTML
it is possible to embed images, audio, video, and other elements directly into a document without processor-intensive add-ons
Web Services
XML(Extensible Markup Language)
the foundation tech for web services
can perform presentation, communication, and storage of data
Software trends
Open Source Software
users of the software can use the software as is, modify it at will
Cloud-based Software Services and Tools
Mashups(混搭) and Apps
ex:use Google Maps API in your blog
users and entire companies mix and match these software components to create their own customized applications and to share information with others
The principal issues in managing hardware and software tech
Capacity planning and scalability
Capacity planning
df: is the process of predicting when a computer hardware system becomes saturated
ex: considers factors such as the maximum number of users that the system can accommodate at one time
Scalability
df: the ability of a computer, product, or system to expand to serve a large number of users without breaking down
Total cost of ownership(TCO) of tech assets
TCO(total cost of ownership)
used to analyze these direct and indirect actual costs of owning a specific technology
Using tech service providers
Outsourcing(外包)
ex: contract with an external service provider to run their computer center and networks
web hosting service
ex: sugarhost
offshore software outsourcing
outsource software work outside their national borders
why? lower costs of maintaining especially in low-wage countries
SLA(service level agreement)
df: to manage their relationship with an outsourcer or tech service provider, which is a contract
typically specify the nature and level of services provided, criteria for performance measurement, support options, provisions for security and disaster recovery ...
Using cloud service
Managing mobile platforms
MDM(mobile device management)
monitors, manages and secures mobile devices used in the firm
managing software localization for global business
because English is adapted in higher level business but not throughout the middle and lower ranks
these factors should add to the TCO
Chapter.6 Foundation of Business Intelligence: Databases and Information Management
6.1:What is a database and how does a relational database organize data?
Preface
Data hierarchy(資料等級)
bit
- the smallest one
byte
- a group of bits, represents a single character = 8bits
field
- a group of words, such as a name or ID
record
- a group of related fields, such as a student's inro
file
- a group of records of the same type
database
- a group of related files makes up a database
Entities and Attributes
entity(實體)
ex:Course
the generalized categories on which we store info
attributes(屬性)
ex:Course's attributes, Student ID, Course, Date, Grade...
the characteristics of entity
Organizing data in a relational database
relational database
is the most common type of database today
organize data into
two dimensional tables
(called relation) with columns and rows
each table contains data about entity and its attributes
The tables of a relational database
rows(欄)
includes records or
tuples
key field
primary key
(主鍵)
each table in a r.d. has
one field
designated as it's p.k.
this key field is the
unique identifier
for all the info in any row of the table, and this primary key
can not be duplicated
ex:
people's ID card
, because each ID card represents a person
the principle of picking a primary key
1.絕對不能是空值
2.永遠不會改變
3.本身不是識別值(本身沒有其他意義，通常是人造欄位)
4.簡短而簡單的值
foreign key(外鍵)
表的單一欄，這個值通常參考到其他表的主鍵，扮演連結表與表的角色
referencing(子表) - 具有外鍵的表
referenced(父表) - 被參考表
Establishing relationships
one-to-one relationship
ex:訂購單 - 入庫單(都是同一筆產品的Table)
one-to-many relationship
ex:Supplier - Part(多個part都來自同一個供應商)
many-to-many relationship
ex:產品 - 訂購單(多個產品來自不同的訂購單)
6.2:What are the principles of a database management system
Database Management System(DBSM)
The main function
Data Independence
Logical data independence
資料整體邏輯資料結構改變時，不會影響到應用程式
Physical data independence
指資料的實際儲存方式改變時，不會影響到整體邏輯資料結構，也不會影響到應用程式
integrated
可以將資料之重覆(redundancy)減至最少
shared
在資料庫中任一資料可同時供多個使用者使用
Operations of a relational DBMS
Select(篩選)
df: creates a subset consisting of all records in the file that
meet stated criteria
(跟Project的差異在select是horizontal，project是 vertical)
ex: 光輝選了那些課？→從選課表中篩選學生姓名欄位為"光輝"，來列組成新的選課單
Join(合併)
df: combines relational tables to provide the user with
more information than is available in individual tables
ex:在選課表中加入學號→合併選課表和學生資料表組成選課表
Project(投影)
df: 由一表中找出所需
欄位
組成另一表
ex:依課程代號列出教師名稱→由開課表中，擷取課程代號、教師姓名欄位組成開課教師名單
Capabilities of DBMS
Basic
data definition
to specify the structure of the content of the database
data dictionary
the info about the database would be documented in ~~
is an automated or manual file that stores definitions of data elements and their characteristics
Querying and Reporting
data manipulation language
to add, change, delete and retrieve the data in the d.b.
SQL(Structured Query Language)
is the most prominent data manipulation language today
6.3:What are the principal tools and tech for accessing info from databases to improve business performance and decision making
Business intelligence infrastructure
Data Warehouse and Data Marts
Data Warehouse
df: is a database that stores
current and historical data
of potential interest to decision makers throughout the company
is not meant for current, "live" data
is primary, a record of an enterprise's
past transaction and operational info
effect
1.提供改良過的資訊，也使決策者更易獲得資訊
2.建構資料模型與重新建構資料模型的功能
function
1.提供報表與查詢工具
2.儲存目前與歷史資料
3.結合做管理報告與分析之用
Data Mart(資料超市)
df: is
a subset of a data warehouse
, in which a summarized or highly focused portion of the organization's data is placed in a separate database for a
specific population of users
difference: data mart is predicated on a
specific, predefined
need for a certain grouping and configuration of select data
The challenge of big data
There has been an explosion of data, and these data may be unstructured or semi-structured unlike the normal data we know, and these data is not suitable for relational database
Analytical tools: relationships. patterns, trends
OLAP(Online Analytical Processing)
supports multidimensional data analysis, enabling users to view the same data in different ways using multiple dimensions
ex: each aspect of info-- product, pricing, cost, region --represents a different dimension
Data Mining
is more discovery-driven
provides insights into corporate
data that can not be obtained with OLAP
by
finding hidden patterns and relationships
in large databases and inferring rules from them to predict future behavior
Types of info obtainable
Associations
df: occurrences linked to a single event
ex: in a supermkt, when corn chips are purchased, a coke is purchased 65 percent of the time
sequences
df: events are linked over time
ex: if a house is purchased, a new refrigerator will be purchased
within two weeks 65% of the time
Classification
df:
recognizes patterns
that describe the group to which an item belongs by examining existing items that have been classified and by inferring a set of rules
ex: helps discover the characteristics of customers who are likely to leave and can provide a model to help managers
Clustering
df: wrks in a manner similar to classification
when no groups have yet been defined
ex: partition a database into groups of customers based on demographics and types of personal investments
forecasting
df: uses a series of existing values to forecast what other values will be
ex: forecasting might
find patterns in data
to help managers estimate the future value of continuous variables,ex:
sales figures
Text mining and Web mining
origin
unstructured data account for more than 80% of useful organizational info, and is the major source of big data
Text mining
extract key elements from unstructured big data sets, discover patterns and relationships, and summarize the info
sentiment analysis
mine text comments in an email, blog... to detect favorable and unfavorable opinions
Web mining
df: the discovery and analysis of useful patterns and info from WWW
Database and the Web
database server
使用資料庫軟體來處理SQL指令，和執行資料庫管理任務的一台位於主從式環境(client/server environment)的電腦
application server
可以處理所有應用程式作業的一種軟體
Linking internal databases to the web
Client with web browser←→Internet←→Web server←→Application server←→Database server←→Database
6.4: Why info policy, data administration and data quality assurance essential for managing the firm's data resource
Establishing an info policy
info policy
specify the organization's
rules for sharing, disseminating, acquiring, standardizing ... information.
data administration
is responsible for the specific policies and procedures through which
data can be managed as an organizational resource
Ensuring data quality
Data quality audit(資料品質審核)
結構化地調查資料的準確性和完整性
Data cleansing(資料淨化) aka. data scrubbing
1.不完整的資料
2.不正確的資料
3.格式不符合的資料
4.冗餘(redundant)的資料
Chapter.9 Achieving Operational excellence and customer intimacy: enterprise applications
9.1: How do enterprise systems help businesses achieve operational excellence
What are enterprise systems
to help managers take advantage of the data in the database
Enterprise software
df: is built around thousands of predefined business processes that reflect best practices
ERP(Enterprise Resource Planning 企業資源規劃)
function
1.收集企業內各部門的所有內部業務活動資料
2.整合式的軟體模組和一個共用的中央資料庫
3.整合企業各流程的資訊流，提供即時、完整、正確的資訊
pros
提升企業的營運績效以及快速反應的能力
Business value of enterprise systems
provide value by both increasing operational efficiency and providing firm-wide info to help managers make better decisions
9.2: Supply Chain management systems
The Supply Chain
df: 一個從原物料開始一直到最終客戶來傳送產品和服務的整體網路，藉由一個設計好的資訊流、物流、金流來完成
upstream(上游)
includes the company's suppliers, the suppliers' suppliers, and the processes for managing relationships with them
downstream(下游)
consists of the organizations and processes for distributing and delivering products to the final customers
Information systems and supply chain management
Just-in-time(及時策略)
組件在他們被需要的時候抵達
成品在離開裝配線之後馬上被送運出廠
Bullwhip effect(長鞭效應)
產品的需求被扭曲，因為訊息在供應商與供應商之間傳遞
can be tamed when all members of the supply chain have accurate and up-to-date info
儘管特定產品的顧客需求變化不大，但是這些商品的庫存或是延期交貨的波動程度卻相當大
Safety stock(安全庫存)
為供應鏈中缺乏靈活性題供緩衝
Supply chain management software
連結企業內部與企業間的主要功能與程序，包含所有的物流活動、製造，也驅動了行銷、銷售、產品設計...等程序與活動間的協調
Supply chain execution systems
manage the flow of products through distribution centers and warehouses to ensure that products are delivered to the right locations in the most efficient manner
Global supply chains and the internet
Demand-Driven Supply chains: from push to pull manufacturing and efficient customer response
push-based model(推式供應鏈)(aka build-to-stock)
指主生產計劃以長期的預測為基礎
會花較長時間反應市場的變動
通常製造商會從零售商收到的訂單來預測顧客需求
cons
1.沒有能力滿足高變動的需求
2.商品的需求消失時，供應鏈存貨會過時
3.長鞭效應造成訂單變異性大
4.變異性增加會導致:(1)大量安全存貨所導致的超額存貨 (2)大量且變異性的生產批量，不能接受的服務水準 (3)商品的過時
pull-based model(拉式供應鏈)
aka a
demand-driven or build-to-order model
生產依實際顧客需求而非以預測資料為依據
真正的拉式系統不需要持有任何存貨，指需要針對訂單回應
pros
1.降低前置時間(更精準預測從零售商流入的訂單)
2.零售商存貨減少
3.系統變異性減少
4.製造商存貨減少(因為變異性減少)
Business value of supply chain management systems
reduce inventory levels
improve delivery service
speed product time to mkt
use assets more effectively
9.3 Customer Relationship Management systems
What is customer relationship management
在最佳的時間點，透過最適當的管道，提供最適當的產品，給當時最需要的顧客，以提高企業營收、顧客滿意度及獲益能力
touch point (aka contact point)
is
a method of interaction with the customer
, such as telephone, email, customer service desk, conventional mail, Facebook ...
Customer relationship management software
SFA(Sales Force Automation)
Customer Service
Marketing
cross-selling
package
PRM(Partner Relationship Management)
ERM(Employee Relationship Management)
Customer Loyalty Management Process Map
https://drive.google.com/file/d/1eA548k_ExawvEvYrzqRlZ1WhXWeupKO8/view?usp=sharing
Operational and Analytical CRM
Operational CRM
df: 客戶導向的應用，如銷售團隊自動化、客服中心、客戶服務支持...
ex: SFA, Marketing Automation, Customer Services ...
Analytical CRM
df:
includes applications that analyze customer data
generated by operational CRM applications to provide info for
improving business performance.
在透過報表系統、OLAP、Data mining等BI技術幫助企業了解客戶分類、行為、滿意度等資訊
CLTV(Customer Lifetime Value)
Three types of CRM
https://drive.google.com/file/d/1Lun4mSZZI1H0D1YR44-Y0KR9aety4rLt/view?usp=sharing
Business value of CRM system
churn rate(客戶流失率)
measures
the number of customer who stop using
or purchasing products or services from a company
it's an important
indicator of the growth or decline of a firm's customer base
9.4 Enterprise Applications: New opportunities and challenges
Enterprise application challenges
昂貴的購買與實施企業應用程序
技術的改變
企業流程的改變
組織學習的改變
轉換成本，對軟體供應商的依賴
資料的標準化、管理、淨化
Next-generation enterprise applications
Social CRM
結合社交網路技術
公司社交網路
客戶通過Facebook的交互作用
Business Intelligence
靈活彈性的報表
將BI與企業應用整合
Chapter 10: E-Commerce: Digital markets, Digital Goods
10-1 Unique features of e-commerce, digital markets, and digital goods
The new e-commerce: social, mobile, local
From eyeballs to conversations
it means that your brand is being talked about on the web and social media
From the desktop to the smartphone
Why e-commerce is different
ubiquity
reduces transaction costs(costs of participating in a mkt)
global reach
universal standards
lower market entry costs(the cost merchants must pay simply to bring their goods to market)
richness
refers to the complexity and content of a message
interactivity
information density
the total amount and quality of info available all market participants, consumers, ad merchants alike.
personalization/customization
key concept in EC
information asymmetry(資運不對稱)
lower menu costs(merchant's costs of changing prices)
dynamic pricing
disintermediation(非中介)
將供應鏈的多個環節cut掉，降低交易成本
Digital goods
df: goods that can be delivered over a digital network
ex: music tracks, video...
the marginal cost of producing another unit is about zero
10-2 Principal EC business and revenue models
Types of EC
B2C
B2B
C2C
m-commerce
EC business models
Portal
df: provides initial point of entry to the web along with specialized content and other services
ex: Yahoo, Bing, Google
E-tailer(online retail stores)
df: sells physical products directly to consumers or to individual businesses
ex: Amazon
Content provider
df: creates revenue by providing digital content, such as news, music, photos, or video...
ex: iTunes, Netflix
Transaction Broker
df: Saves users money and time by processing online sales transactions and generating a fee each time a transaction occurs
ex: Expedia, Trivigo
Market Creator
df: provides a digital environment where buyers and sellers can meet, search for products, display products, and establish prices for those products
ex: eBay
Service provider
df: provides applications such as photo sharing, video sharing, and user-generated content as services; provides other services such as online data storage
ex: Google Apps, Dropbox
Community provider
df: provides an online meeting place where people with similar interests can communicate and find useful info
ex: Facebook, Google+, Twitter
EC revenue models
Advertising revenue model
df: a website generates revenue by attracting a large audience of visitors who then be exposed to ads
ex: Google, Yahoo
Sales revenue model
df: companies derive revenue by selling goods, information, or services to the customers.
ex: Amazon, Gap, iTunes, Spotify
Subscription Revenue model