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Serve operational managers and staff. Perform and record daily routine transactions necessary to conduct businesses. Allow managers to monitor status of operations and relations with external environment. Serve predefined, structured goals and decision making

Practical:
Performs and records the daily routine transactions necessary to conduct business

– Enables distributed parallel processing of big data across inexpensive computers

– Key services
• Hadoop Distributed File System (HDFS): data storage
• MapReduce: breaks data into clusters for work
• Hbase: NoSQL database

– Used Yahoo, NextBio

–Used in big data analysis
– Uses computers main memory (RAM) for data storage to avoid delays in retrieving data from disk storage
–Can reduce hours/days of processing to seconds
–Requires optimized hardware

High-speed platforms using both relational and non-relational tools optimized for large datasets

–Multidimensional data analysis (OLAP)
–Data mining
–Text mining
–Web mining

• Supports multidimensional data analysis
–Viewing data using multiple dimensions
–Each aspect of information (product, pricing, cost, region, time period) is different dimension
–Example: How many washers sold in the East in June compared with other regions?

• OLAP enables rapid, online answers to ad hoc queries


Practical:
OLAP supports multidimensional data analysis, enabling users to view the same data in different ways using multiple dimensions. Each aspect of information— product, pricing, cost, region, or time period—represents a different dimension. OLAP enables users to obtain online answers to ad hoc questions such as these in a fairly rapid amount of time, even when the data are stored in very large databases, such as sales figures for multiple years

Analysis of large pools of data to find patterns and rules that can be used to guide decision making and predict future behavior.

• Finds hidden patterns, relationships in datasets –Example: customer buying patterns
• Infers rules to predict future behavior

• Types of information obtainable from data mining:
1. Associations
2.  Sequences
3. Classification
4. Clustering
5. Forecasting

–Extracts key elements from large unstructured data sets
–Sentiment analysis software

–Discovery and analysis of useful patterns and information from web
–Web content mining
–Web structure mining
–Web usage mining

– Ease of use of browser software
– Web interface requires few or no changes to database
– Inexpensive to add web interface to system

1. Trade secret: intellectual work or product belonging to business, not in the public domain
2. Copyright: statutory grant protecting intellectual property from being copied for the life of the author, plus 70 years
3. Patents: grants creator of invention an exclusive monopoly on ideas behind invention for 20 years

–Software bugs, errors
–Hardware or facility failures
–Poor input data quality (most common source of business system failure)

–Computer hardware platforms
–Operating system platforms
–Enterprise software applications
–Data management and storage
–Networking/telecommunications platforms
–Internet platforms
–Consulting system integration services

–IBM (DB2)
– Oracle
–Microsoft (SQL Server)
–Sybase (Adaptive Server Enterprise)
– MySQL
–Apache Hadoop

EMC Corporation

–Web-hosting services
– Routers
–Cabling or wireless equipment

– Smartphones
– Netbooks
–Tablet computers
–Digital e-book readers (Kindle)
–Wearable devices

Forces businesses and IT departments to rethink how IT equipment and services are acquired and managed

–Uses quantum physics to represent and operate on data
–Dramatic increases in computing speed

–Allows single physical resource to act as multiple resources (i.e., run multiple instances of OS)
–Reduces hardware and power expenditures
–Facilitates hardware centralization
–Software-defined storage (SDS)

–On-demand computing services obtained over network
• Infrastructure as a service (IaaS)
• Software as a service (SaaS)
• Platform as a service (PaaS)

–Cloud can be public or private
–Allows companies to minimize IT investments –Drawbacks: Concerns of security, reliability –Hybrid cloud computing model

Practical: style of computing in which IT services are delivered on- demand and accessible via the Internet.

– Practices and technologies for manufacturing, using, disposing of
computing and networking hardware
–Reducing power consumption a high priority
–Data centers

–Multicore processors
–Power-efficient microprocessors

• 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

• Files maintained separately by different departments
• Data redundancy
• Data inconsistency
• Program-data dependence
• Lack of flexibility
• Poor security
• Lack of data sharing and availability

Data redundancy is the presence of duplicate data in multiple data files so that the same data are stored in more than one place or location. Data redundancy wastes storage resources and also leads to data inconsistency, where the same attribute may have different values.

Serves many applications by centralizing data and
controlling redundant data

– 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

–More flexible data model
–Data sets stored across distributed machines
–Easier to scale
–Handle large volumes of unstructured and structured data

–Appeal to start-ups, smaller businesses
–Amazon Relational Database Service, Microsoft SQL Azure
–Private clouds

Massive sets of unstructured/semi-structured data from web traffic,
social media, sensors, and so on

Practical:
Data sets with volumes so huge they are beyond the ability of typical relational DBMS to capture and analyse.

• Volumes too great for typical DBMS –Petabytes, exabytes of data
• Can reveal more patterns, relationships and anomalies
• Requires new tools and technologies to manage and analyze

Array of tools for obtaining information from separate systems and from big data

- is a contemporary term for data and software tools for organizing, analyzing, and providing access to data to help managers and other enterprise users make more informed decisions.
Using data analysis tools and applications to help business make more informed decisions. Actually, one can see BI as the transformation on raw data into a meaningful form that can be used for business purposes.

–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 tools

– Subset of data warehouse
– Typically focus on single subject or line of business


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.

Tiny software programs invisibly embedded in e-mail messages and Web pages that are designed to monitor the behavior of the user visiting a Web site or sending e-mail.

– Tiny graphics embedded in e-mails and web pages
– Monitor who is reading e-mail message or visiting site

technology that aids in gathering information about a person or organization without their knowledge (e.g. banner ads)

– Surreptitiously installed on user’s computer
– May transmit user’s keystrokes or display unwanted ads

–E-mail encryption
–Anonymity tools
–Anti-spyware tools

– Intangible property of any kind created by individuals or corporations

They create opportunities for:
–Intense social change, threatening existing distributions of power, money, rights, and obligations
–New kinds of crime

• Information rights and obligations
• Property rights and obligations
• Accountability and control
• System quality
• Quality of life

• Computing power doubles every 18 months
• Data storage costs rapidly decline
• Data analysis advances
• Networking advances
• Mobile device growth impact

Combining data from multiple sources to create dossiers of detailed
information on individuals

Combining data from multiple sources to find obscure hidden connections that might help identify criminals or terrorists

• Responsibility
– Accepting the potential costs, duties, and obligations for decisions

• Accountability
–Mechanisms for identifying responsible parties

• Liability
– Permits individuals (and firms) to recover damages done to them

• Due process
–Laws are well-known and understood, with an ability to appeal to higher authorities

1. Identify and clearly describe the facts.
2. Define the conflict or dilemma and identify the higher-order values involved.
3. Identify the stakeholders.
4. Identify the options that you can reasonably take.
5. Identify the potential consequences of your options.

Tiny file deposited on a computer hard drive when an individual visits certain Web sites. Used to identify the visitor and track visits to the Web site.

– Identify browser and track visits to site
– Super cookies (Flash cookies)

1. Identify your firm´s collaboration challenges
2. Identify what kinds of solutions are available
3. Analyze available products cost and benefits
4. Evaluate security risks
5. Consult user for implementation and training issues
6. Evaluate product vendors

Serve middle management. Support non routine decision making. May use external information as well TPS/MIS data. Model driven DSS. Data driven DSS

Practical:
Combine data and sophisticated analytical models or data analysis tools to support semi structured and unstructured decision making

Support senior management. Adresses nonroutine dessinions. Incorporate data about external events (new tax laws or competitors) as well as summarized information from internal MIS and DSS. Ex. digital dashboard with real-time view of firm´s financial performance


Practical:
Help senior management address non-routine decisions requiring judgment, evaluation and insight because there is no agreed-on procedure for arriving at a solution

Systems for linking the enterprise. Span functional areas. Execute business processes across the firm. Include all levels of management. Four major applications (Enterprise systems, SCM, CRM, knowledge management systems). Collect data from different firm functions and store data in single central data repository. Resolve problems of fragmented data

are used to bridge the communication gap between all departments and all users of information within a company. Enterprise systems truly allow a company to use information as a vital resource and enhance the bottom line.

Manage firm´s relationships with.
Share information about:
- Orders, production, inventory levels, delivery of products and services
Goal:
- Right amount of products to destination with least amount of and lower cost


Practical:
These systems help supply chain members to share information about orders, production, inventory levels, and delivery of products and services so they can turn the supply process more efficient.

Provide information to coordinate all of the business processes that deal with customers: Sales, marketing, customer service.
Helps firm identify, attract, and retain most profitable customer

- Supports processes for capturing and applying knowledge and expertise (how to create, produce and deliver products, services)
- Collect internal knowledge and experience within firm and make it available to employees
- Link to external sources of knowledge


Practical:
These systems collect all relevant knowledge in the firm, and make it available to improve business processes and management decisions.

Internal company websites accessible only by employees

- Company websites accessible externally only to vendors and suppliers
- Often used to coordinate supply chain

Serve middle management. Provide reports on firm´s current performance, based on data from TPS. Provide answers to routine questions with predefined procedure for answering them. Typically have little analytic capability

Practical:
Provides reports on organizational performance to help middle management monitor and control the business

An opt-out model permits the collection of personal information until the consumer specifically requests that the data cannot be collected.

An opt-in model prohibits businesses from collecting any personal information unless the consumer specifically takes action to approve information collection and use

Businesses utilize search engine optimization (SEO) to improve their website’s organic listings on SERPs. Process of getting traffic from organic/natural search results on search engine without paying the search engine service.

- Reputation or popularity; Relevance; User satisfaction (Bounce Rates, CTR, etc)

A collection of online marketing strategies and tactics that promote brands by increasing their visibility in search engine results pages (SERPs) through optimization and advertising.

• Pay-per-click(PPC)
• SEO

Pay-per-click advertising: advertisers pay the SE based on how many people click on the ads. (Google AdWords)
• Keywords & Bid pricing
• Geographic location & time of day
• Landing pages

1. Computer Virus
2. Worms
3. Trojan Horses
4. SQL Injection attacks
5. Spyware

SW program that is attached to other programs/files in order to be executed. They spread from computer to computer when human take actions (usually without their permission)

Independent computer programs that copy themselves from one computer to the other, not requiring human intervention.

SW program that appears to be benign but then does something other than expected. It is often a way for viruses or other malicious code to be introduced into a computer system.

Taking advantage of vulnerabilities in poorly coded web application software to introduce malware into a company’s systems and networks

These programs install themselves on a computer to monitor user web surfing activities and serve up advertising

1. Spoofing
2. Sniffing
3. Denial-of-Service attacks
4. Identity theft
5. Click fraud
6. Global threats

Using fake e-mail addresses or masquerading as someone else. May also involve redirecting a customer to a fake Web site to collect information.

Type of eavesdropping program that monitors information traveling over a network. Allows hackers to steal proprietary information from anywhere on a network

Flooding a network server or Web server with many thousands of false communications or requests for services to crash the network

A crime in which an imposter obtains key pieces of personal information to impersonate someone else

Occurs when an individual or computer program fraudulently clicks on an online ad without any intention of learning more about the advertiser or making a purchase

Internet vulnerabilities have also turned individuals and even entire nation states into easy targets for politically-motivated hacking to conduct sabotage and espionage

Firm’s suppliers, suppliers’ suppliers, processes for managing relationships with them

Organizations and processes responsible for
delivering products to customers

• Suite of integrated software modules and a common central database
• Collects data from many divisions of firm for use in nearly all of firm’s internal business activities
• Information entered in one process is immediately available for other processes

– Components arrive as they are needed
– Finished goods shipped after leaving assembly line

Buffer for lack of flexibility in supply chain

Information about product demand gets distorted as it passes from one entity to next across supply chain

–Model existing supply chain
–Enable demand planning
–Optimize sourcing, manufacturing plans –Establish inventory levels
–Identify transportation modes

Manage flow of products through distribution centers and warehouses

–Greater geographical distances, time differences
–Participants from different countries

– Earlier SCM systems
– Schedules based on best guesses of demand

– Web-based
– Customer orders trigger events in supply
chain

– Knowing the customer
– In large businesses, too many customers and
too many ways customers interact with firm

– Capture and integrate customer data from all
over the organization
– Consolidate and analyze customer data
– Distribute customer information to various systems and customer touch points across enterprise
– Provide single enterprise view of customers

• Integrating lead generation, pricing, promotions, order configurations, and availability
• Tools to assess partners’ performances

• Setting objectives, employee performance management, performance- based compensation, employee training

– Sales force automation (SFA)
• Sales prospect and contact information
• Sales quote generation capabilities

– Customer service
• Assigning and managing customer service
requests
• Web-based self-service capabilities

– Marketing
• Capturing prospect and customer data, scheduling and tracking direct-marketing mailings or e-mail
• Cross-selling

– Customer-facing applications
– Sales force automation
Call center and customer service support
– Marketing automation

– Based on data warehouses populated by operational CRM systems and customer touch points
– Analyzes customer data (OLAP, data mining, etc.)
• Customer lifetime value (CLTV)

– Increased customer satisfaction
– Reduced direct-marketing costs
– More effective marketing
– Lower costs for customer acquisition/retention – Increased sales revenue

– Number of customers who stop using or purchasing products or services from a
company
– Indicator of growth or decline of firm’s customer base

• Highly expensive to purchase and implement enterprise applications
• Technology changes
• Business process changes
• Organizational learning, changes
• Switching costs, dependence on software vendors
• Data standardization, management, cleansing

– Incorporating social networking technologies
– Company social networks
– Monitor social media activity; social media analytics
– Manage social and web-based campaigns