1
Q
IT Infrastructure
A
- Set of physical devices and software required to operate
an enterprise - Set of firm-wide services including:
– Computing platforms providing computing services
– Physical facilities management services
– I T management, education, and other services - “Service platform” perspective
– More accurate view of value of investments
2
Q
Evolution of IT Infrastructure
A
- General-purpose mainframe and minicomputer era: 1959
to present - Personal computer era: 1981 to present
- Client/server era: 1983 to present
- Enterprise computing era: 1992 to present
- Cloud and mobile computing: 2000 to present
3
Q
Drivers of Infrastructure
Evolution
A
- Moore’s law and microprocessing power
– Computing power doubles every 2 years
– Nanotechnology - Law of Mass Digital Storage
– The amount of data being stored each year doubles - Metcalfe’s Law and network economics
– Value or power of a network grows exponentially as a
function of the number of network members - Declining communication costs and the Internet
– Exponential growth in size of the Internet - Standards and network effects
– Technology standards
Specifications that establish the compatibility of products
and the ability to communicate in a network
Unleash powerful economies of scale and result in price
declines
4
Q
Components of IT
Infrastructure
A
- Computer hardware platforms
- Operating system platforms
- Enterprise software applications
- Data management and storage
- Networking/telecommunications platforms
- Internet platforms
- Consulting system integration services
5
Q
Computer Hardware Platforms
A
- Client machines
– Desktop PC s, laptops
– Mobile computing: smartphones, tablets
– Desktop chips vs. mobile chips - Servers
- Mainframes
– IBM mainframe
– Digital workhorse for banking and telecommunications
networks
6
Q
Operating System Platforms
A
- Corporate servers
– Windows Server
– Unix
– Linux - Client level
– Microsoft Windows
– Android, iO S, Windows 10 (mobile/multitouch)
– Google’s Chrome O S (cloud computing)
7
Q
Data Management and Storage
A
- Database software providers
– IBM (DB2)
– Oracle
– Microsoft (SQL Server)
– SAP Sybase (Adaptive Server Enterprise),
– MySQL (Oracle)
– Apache Hadoop
8
Q
Telecomunications Platforms
A
- Network operating systems
– Windows Server, Linux, Unix - Network hardware providers
– Cisco, Juniper Networks - Telecommunication services
– Telecommunications, cable, telephone company
charges for voice lines and Internet access
– AT&T, Verizon
9
Q
Internet Platforms
A
- Hardware, software, management services to support company
websites, intranets
– Web-hosting services
– Routers
– Cabling or wireless equipment - Internet hardware server market
– IBM, Dell, Oracle, HP - Web development tools/suites
– Microsoft (Visual Studio and .NET), Oracle-Sun (Java),
Adobe
10
Q
Current Trends in
Computer Hardware Platforms
A
- The mobile digital platform
- Consumerization of IT and BYOD (bring your own device)
- Quantum computing
– Uses quantum physics to represent and operate on data
– Dramatic increases in computing speed - Virtualization
– Allows single physical resource to act as multiple resources, also enables multiple physical resources to appear as a single logical resource
– Reduces hardware and power expenditures
– Facilitates hardware centralization - Cloud computing
Infrastructure as a service (IaaS)
Software as a service (SaaS)
Platform as a service (PaaS) - Edge computing
– Servers at the edge of the network, near the source of
the data
– Reduces latency and network traffic - Green computing (Green IT )
– Practices and technologies for manufacturing, using,
disposing of computing and networking hardware
– Reducing power consumption a high priority
– Green data centers - High-performance, power-saving processors
– Multicore processors
11
Q
Current Computer Software
Platforms and Trends
A
- Linux and opensource software
– Produced by community of programmers
– Linux - Software for the web: Java, HTML, and HTML5
– Java Virtual Machine
– Web browsers
– HTML and HTML 5
– Ruby and Python - Web services and service-oriented architecture
– SOA : service-oriented architecture
Set of self-contained services that communicate with one
another to create a working software application
Software developers reuse these services in other
combinations to assemble other applications as needed - Software outsourcing and cloud services
- Mashups and apps
12
Q
Dealing with Platform and Infrastructure
Change
A
- Scalability
– Ability to expand to serve larger number of users
13
Q
How should IT department be organized?
A
– Centralized
Central IT department makes decisions
– Decentralized
Business unit IT departments make own decisions
14
Q
Total Cost of Ownership (TCO) Model
A
- Analyzes direct and indirect costs
- Hardware, software account for only about 20% of TCO
- Other costs: Installation, training, support, maintenance,
infrastructure, downtime, space, and energy - TCO can be reduced
– Use of cloud services, greater centralization and standardization of hardware and software resources
15
Q
Competitive Forces Model for IT
Infrastructure Investment
A
- Market demand for firm’s services
- Firm’s business strategy
- Firm’s IT strategy, infrastructure, and cost
- Information technology assessment
- Competitor firm services
- Competitor firm IT infrastructure investments
16
Q
File Organization Terms and Concepts
A
- Database: Group of related files
- File: Group of records of same type
- Record: Group of related fields
- Field: Group of characters as word(s) or number(s)
- Entity: Person, place, thing on which we store information
- Attribute: Each characteristic, or quality, describing entity
17
Q
Problems with the Traditional File
Environment
A
- Files maintained separately by different departments
- Data redundancy
- Data inconsistency
- Program-data dependence
- Lack of flexibility
- Poor security
- Lack of data sharing and availability
18
Q
Database Management Systems
A
– Interfaces between applications and physical data files
– Separates logical and physical views of data
– Solves problems of traditional file environment
Controls redundancy
Eliminates inconsistency
Uncouples programs and data
Enables organization to centrally manage data and data
security
19
Q
Relational DBMS
A
- Represent data as two-dimensional tables
- Each table contains data on entity and attributes
- Table: grid of columns and rows
– Rows (tuples): Records for different entities
– Fields (columns): Represents attribute for entity
– Key field: Field used to uniquely identify each record
– Primary key: Field in table used for key fields
– Foreign key: Primary key used in second table as look-
up field to identify records from original table
20
Q
Operations of a Relational DBMS
A
- Three basic operations used to develop useful sets of data
– SELECT
Creates subset of data of all records that meet stated
criteria
– JOIN
Combines relational tables to provide user with more
information than available in individual tables
– PROJECT
Creates subset of columns in table, creating tables with
only the information specified
21
Q
Capabilities of Database Management
Systems
A
- Data definition
- Data dictionary
- Querying and reporting
– Data manipulation language
Structured Query Language (SQ L) - Many DBM S have report generation capabilities for
creating polished reports (Microsoft Access)
22
Q
Designing Databases
A
- Conceptual design vs. physical design
- Normalization
– Streamlining complex groupings of data to minimize redundant
data elements and awkward many-to-many relationships - Referential integrity
– Rules used by RDBM S to ensure relationships between tables
remain consistent - Entity-relationship diagram
- A correct data model is essential for a system serving the
business well
23
Q
Non-relational databases: “No SQL”
A
– More flexible data model
– Data sets stored across distributed machines
– Easier to scale
– Handle large volumes of unstructured and structured data
24
Q
- Distributed databases
A
Stored in multiple physical locations
25
* Blockchain
– Distributed ledgers in a peer-to-peer distributed database
– Maintains a growing list of records and transactions shared by all
– Encryption used to identify participants and transactions
– Used for financial transactions, supply chain, and medical records
– Foundation of Bitcoin, and other crypto currencies
26
Big data
– Massive sets of unstructured/semi-structured data from
web traffic, social media, sensors
27
The Challenge of Big Data
* Volumes too great for typical DBM S
* Can reveal more patterns, relationships and anomalies
* Requires new tools and technologies to manage and analyze
28
Business Intelligence Infrastructure
– Data warehouse
– Data mart
– Hadoop
– In-memory computing
– Analytical platforms
29
Data warehouse
– Stores current and historical data from many core operational transaction
systems
– Consolidates and standardizes information for use across enterprise, but
data cannot be altered
– Provides analysis and reporting tool
30
Data marts
– Subset of data warehouse
– Typically focus on single subject or line of business
31
Hadoop
– Enables distributed parallel processing of big data across
inexpensive computers
– Used by Yahoo, NextBio
32
In-memory computing
– Used in big data analysis
– Uses computers main memory (RA M) for data storage to
avoid delays in retrieving data from disk storage
– Can reduce hours/days of processing to seconds
– Requires optimized hardware
33
Analytic platforms
– High-speed platforms using both relational and non-relational tools optimized for large datasets
34
Analytical Tools
– Multidimensional data analysis (O LA P)
– Data mining
– Text mining
– Web mining
35
Online Analytical Processing (O L A P)
* Supports multidimensional data analysis
– Viewing data using multiple dimensions
– Each aspect of information is different dimension
* O LA P enables rapid, online answers to ad hoc queries
36
Data Mining
* Finds hidden patterns, relationships in datasets
* Infers rules to predict future behavior
* Types of information obtainable from data mining:
– Associations
– Sequences
– Classification
– Clustering
– Forecasting
37
Text mining
– Extracts key elements from large unstructured text data sets
– Sentiment analysis software
38
Web mining
– Discovery and analysis of useful patterns and information from web
– Web content mining
– Web structure mining
– Web usage mining
39
Advantages of using the web for database
– Ease of use of browser software
– Web interface requires few or no changes to database
– Inexpensive to add web interface to system
40
Data governance
– Encompasses policies and procedures through which
data can be managed as an organizational resource.
– Establishes rules for sharing, disseminating, acquiring,
standardizing, classifying and inventorying information
41
Data Quality Assurance
Before new database is in place, a firm must
– Identify and correct faulty data
– Establish better routines for editing data once database
in operation
ITM
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Decks in class (3)
# Cards
