Information Systems Final Paper
Levels Of Data Sources
Level 1 (structured) can only tell us what happened in the past Level 2 (semi structured) includes e-commerce data, website data, advertising data. Typically, not internally generated but still business critical Level 3 (structured) data includes social media data, emails, product reviews, blogs, environmental data
Business Intelligence Toolkit
Provide regular summaries of information in a predetermined format. AD HOC REPORTING TOOLS Puts users in control so that they can create custom reports on an as-needed basis by selecting elds, ranges, summary conditions, and other parameters. DASHBOARDS Heads-up display of critical indicators that allows managers to get a graphical glance at key performance metrics. ONLINE ANALYTICAL PROCESSING (OLAP) Takes data from standard relational databases, calculates and summarizes the data, and then stores the data in a special database called a data cube. Data cube: Stores data in OLAP report
Which countries rank among the fastest growing economies? A. Sub-Saharan Africa B. Asia and India C. Europe D. North America
A. Sub-Saharan Africa
5. What are the four characteristics of data? A. Volume, Velocity, Variety, Veracity B. Volume, Persistence, Velocity, Veracity C. Persistence, Structure, Security, Velocity D. None of the above
A. Volume, Velocity, Variety, Veracity
Enterprise Software
APPLICATIONS THAT ADDRESS THE NEEDS OF MULTIPLE USERS THROUGHOUT AN ORGANIZATION OR WORK GROUP • Software package: Software product o ered commercially by a third party. • Enterprise resource planning (ERP): Software package that integrates the many functions of a business: - Sales and inventory - Manufacturing and purchasing - Human resources - Order tracking and decision support
8. The three types of Data Analytics are: A. Conscriptive, Reactive, Descriptive B. Forecasting, Simulation, Optimization C. Descriptive, Predictive, Prescriptive D. Alerting. Reporting, Visualizing
C. Descriptive, Predictive, Prescriptive
4. Which of the following is an example of unstructured data? A. A retail clothing store's inventory spreadsheet B. A bank's general ledger C. Your Twitter tweets D. Your monthly online electric bill
C. your twitter tweets
7. Which best describes Business Analytics? A. Technology to analyze business problems B. The skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. C. Post-mortem processes to determine the causes of financial losses and business decline. D. Comparing the annual reports of competitors to achieve a competitive advantage
B. The skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.
2. What percent of New York Stock Exchange trades are completely automated? A. 25% B. 30% C. 60% D. 100%
c. 60%
data is growing
exponentially and demands new approaches (technology and strategy)
Buying Time
• Multicore microprocessors: Contain two or more calculating processor cores on the same piece of silicon. • Multicore chips outperform a single speedy chip, while running cooler and drawing less power. • Now mainstream, most PCs and laptops sold have at least a two-core (dual-core) processor. • Can run older software written for single-brain chips by using only one core at a time. • Firms are radically boosting speed and e ciency of chips. - Taking chips from being paper- at devices to built-up 3-D a airs. - Transistors: Super-tiny on-o switches in a chip that work collectively to calculate or store things in memory.
Operating system Applications
• Operating system: Software that controls the computer hardware - Establishes standards for developing and executing applications • Applications: Desktop applications, enterprise software, utilities, and other programs that perform speci c tasks for users and organizations • Examples: Microsoft Windows, Linux, Apple macOS High Sierra, Android, IBM zVM, IBM zOS
External Sources
• Organizations can have their products sold by partners and can rely heavily on data collected by others. • Data from external sources might not yield competitive advantage on its own: - Can provide operational insight for increased efficiency and cost savings. - May give rms a high-impact edge.
Financial Functions
• PMT - Calculates payments required each period on a loan • PPMT - Calculates the amount of a loan devoted to paying o a principle • IPMT - Calculates the amount of a lad devoted to paying o the loan interest • PV - Calculates the present value of loan or investment • NPER - Calculates the number of periods required to pay o a loan or investment • RATE - Calculates the interest rate of a loan or investment based on periodic constant payments
Evolution of the Technological Landscape
• Price elasticity: Rate at which the demand for a product or service uctuates with price change. • Evolving waves of computing: - 1960s - Mainframe computers - 1970s - Minicomputers - 1980s - PCs - 1990s - Internet computing - 2000s - Smartphone revolution - 2010s - Pervasive computing: • Vision of embedding low-cost sensors, processors, and communication into a wide array of products and the environment. • Allow a vast network to collect data, analyze input, and automatically coordinate collective action
What is involved in machine learning?
Machine learning prep • Clearly define business problem • Select data set to address business problem • Transform historical data (label outcomes) Machine learning process • Prepare data for use in algorithm (transform text values to integers) • Select an algorithm and train the model against a subset of the data (repeat using a different algorithm) • Identify the best algorithm/model and test that model with a new subset of the same data • Evaluate/Validate the model (retest with yet another new subset of the same data) • Deploy the model (score against a previously unseen set of data) • Maintain/monitor the model (to ensure quality is not degrading)
Cloud Computing Characteristics Common
Massive Scale, Homogeneity, virtualization, low cost software, resilient computing, geographic distribution, service orientation, and advanced security
EARNING MONEY THROUGH SAAS
Money can be earned via a usage-based pricing model similar to a monthly subscription. • Other SaaS rms: - O er free services that are supported by advertising. - Promote the sale of upgraded or premium versions for additional fees. - Compete directly with the biggest names in software.
Death of Moore's Law
Moore's Law is possible because the distance between the pathways inside silicon chips gets smaller with each successive generation. - Fabs: Semiconductor fabrication facilities - Silicon wafer: Thin, circular slice of material used to create semiconductor device • Packing pathways tightly together creates problems associated with size, heat, and power.
Nonvolatile Memory Flash Memory Solid State Electronics Semiconductors Optical Fiber Line
NONVOLATILE MEMORY • Storage that retains data even when powered down. FLASH MEMORY • Nonvolatile, chip-based storage. SOLID STATE ELECTRONICS • Semiconductor-based devices. SEMICONDUCTORS • Substance such as silicon dioxide used inside most computer chips that is capable of enabling and inhibiting the flow of electricity. OPTICAL FIBER LINE • High-speed glass or plastic-lined networking cable used in telecommunications
Database Management System
SOFTWARE FOR CREATING, MAINTAINING, AND MANIPULATING DATA • Referred to as database software. • Stores and retrieves the data created and used by enterprise applications. • Firms with common database systems and standards bene t from increased organizational insight and decision-making capabilities.
Application Software
SOFTWARE THAT PERFORMS THE WORK THAT USERS AND FIRMS ARE DIRECTLY INTERESTED IN ACCOMPLISHING • Platform: Products and services that allow for the development and integration of software products and other complementary goods • Desktop software: Applications installed on a personal computer, typically supporting tasks performed by a single user
Public Cloud
Software, hardware and platforms are hosted externally by a third party vendor who manages all aspects of the services for the business value - standardization, capital preservation, flexibility and time to deploy
Private Cloud
Software, hardware and platforms are hosted in a data center owned by the business and used by different internal business units value... customization, efficiency, availability, resiliency, security and privacy
Transaction Processing Systems
Some form of business-related exchange, such as a cash register sale, ATM withdrawal, or product return • Transaction: Any kind of business exchange. • POS: Point of Sale. A device that initiates an electronic debit or credit transaction. • Loyalty card: System that provides rewards in exchange for consumers, allowing tracking and recording of their activities. - Enhances data collection and represents a signi cant switching cost.
Data and Decision Making: MasterCard
The business model: Processing electronic transactions Handles 43 million data instructions per second - Definitely a Big Data processor! The Challenge: Analyze unstructured social media data regarding customer buying experiences. Involved 1.6 million unprompted online conversations over 12 months MC marketing analysts discerned two distinct trends from this information: − Mobilepayments − Security The Result (Business Actions): Changes in marketing and public relations messaging and communications to focus on security and merchant acceptance issues.
Clouds and Tech Industry Impact
• Shifting to cloud computing modi es the margin structure for many in the computing industry. • Cloud computing can accelerate innovation. - Changes the desired skills mix and job outlook for IS workers. - Enables organizations to spend less on hardware infrastructure and reinvest in strategic e orts and innovation. • Firms need to think about the strategic advantages that can be created.
Super computers processing grid computing cluster computing
• Supercomputers: Computers that are among the fastest of any in the world at the time of their introduction. - Supercomputing was once considered the domain of governments and high-end research labs. - Modern supercomputing is done by massively parallel processing: Computers designed with many microprocessors that work together, simultaneously, to solve problems. • Grid computing: Uses special software to enable several computers to work together on a common problem as if they were a massively parallel supercomputer. • Cluster computing: Connecting server computers via software and networking so that their resources can be used to collectively solve computing tasks.
90% of data created in the 10 last years
was ABANDONED
Finance
- technology-based trading platforms -Quantitative Analysis The tech industry continually sprouts new business Tech firms are actively involved in mergers and acquisitions Investors may evaluate a firm's technology when considering it for an investment portfolio
9. What best describes a Decision Support System? A. A Ouija board B. A meeting methodology for management to use when developing strategic business plans C. A Computer-Based Information System that is intended to support, but not replace, decision makers in performing their problem-solving tasks D. A technique for deciding which skills to hire for an critical project
. A Computer-Based Information System that is intended to support, but not replace, decision makers in performing their problem-solving tasks
Basic Notes on Charting
1. Different charts have different purposes - E.g., pie chart 2. Label things (with reasonable labeling) 3. Add a descriptive title
More Charting Notes
1. Remove noise from your chart background 2. Delete legends with one data series 3. Sort your data before charting (This doesn't apply to all types of charts) 4. Don't make people head tilt 5. Clean up your axes - Add thousands separators - Avoid cluttered axes - Remove unnecessary decimals 6. Explore other themes and select the color
The micro evolution of Data Centricity
2012- volume. Velocity, Variety, and Veracity 2013- Confluence of social, mobile, cloud, big data, and analytics 2014- systems of insight data transforming industries' 2017- data has disrupted entire industries
Decision Support System (DSS)
A Computer-Based Information System that is intended to support, but not replace, (managerial) decision makers in performing their problem-solving tasks. DSS combine DATA, MODELS, and DISPLAYS to assist decision makers. The Idea: To combine the best features of human decision makers and computers
Virtualization
A TYPE OF SOFTWARE THAT ALLOWS A SINGLE COMPUTER OR CLUSTER OF CONNECTED COMPUTERS TO FUNCTION AS IF IT WERE SEVERAL DIFFERENT COMPUTERS • Each computer runs its own operating system and software. Can be used to reduce an organization's hardware needs. Can create a rm's own private cloud of scalable assets. Can cut energy consumption and lower carbon footprint.
Excel
A grid of cells arranged in numbered rows and letter-named columns Excel Spreadsheets Charting (e.g., line graph, histogram, pie chart etc) Formulas (e.g., cell references, functions etc) Pivot table
Pivot Table Analysis
A pivot table is an Excel tool that allows you to reorganize and summarize selected columns and rows of data in a spreadsheet or database table to obtain a desired report. A way to derive information from raw data Also known as a Multidimensional Data Cube
Using Excel as a Decision Support Tool
A set of related computer programs and the data required to assist with analysis and decision-making within an organization.
Discriminant Analysis
Analyzes the difference between data groups to achieve a business outcome. Examples: A bank classifies its account holders by account balance value to target a new certificate of deposit campaign Garanty Bank used discriminant analysis to isolate clients who did not use mobile banking
Why Analytics is Critical for Business
As the degree of complexity (X-axis) increases, the level of analysis required to maintain competitive advantage (Y-axis) increases
Cloud Computing
Cloud Computing is a general term used to describe a new class of network based computing that takes place over the Internet, - basically a step up from Utility Computing - a collection/group of integrated and networked hardware, software and Internet infrastructure (called a platform). - Using the Internet for communication and transport provides hardware, software and networking services to clients These platforms hide the complexity and details of the underlying infrastructure from users and applications by providing very simple graphical interface or API (Applications Programming Interface).
Cloud Computing Summary
Cloud computing is an umbrella term used to refer to Internet based development and services A number of characteristics de ne cloud data, applications services and infrastructure: - Remotely hosted: Services or data are hosted on remote infrastructure. - Ubiquitous: Services or data are available from anywhere. - Commodi ed: The result is a utility computing model similar to traditional that of traditional utilities, like gas and electricity - you pay for what you would want!
Artificial Intelligence
Computer software that seeks to reproduce or mimic human thought, decision making, or brain functions • Data mining has its roots in AI. • Neural network: Examines data and hunts down and exposes patterns, in order to build models to exploit ndings. • Expert systems: Leverages rules or examples to perform a task in a way that mimics applied human expertise. • Genetic algorithms: Model building techniques where computers examine many potential solutions to a problem. - Modi es various mathematical models that have to be searched for a best alternative.
Computing hardware Software
Computing hardware: Physical components of information technology, which includes the computer and its peripherals - Storage devices - Input devices - Output devices • Software: Computer program or collection of programs. - Precise set of instructions that tells hardware what to do
Data Analysis Process
Data Acquisition, Data Extraction/Cleaning, Data Curation & Integration, Data Modeling Analysis, and Develop Actionable Insights
Data Aggregation Data Migration Data Visualization Data Warehouse
Data Aggregation: Collecting data from multiple sources (Variety!) Data Migration: Moving data between two different storage or computing systems. Data Visualization: Utilizing visual representations of data so that it is easy to spot trends. Data Warehouse: Physical storage area for data.
Data Quality Data Cleansing Data Integration
Data Quality: Data must be clean and consistent in format and accuracy (Veracity!) Data Cleansing: Process of removing duplicate data (De- duplication) (Volume!) Data Integration: Data combined from different sources and engineered to a common reporting format (Variety!)
Risks associated with SAAS
Dependence on a single vendor. • Concern about the long-term viability of partner rms. • Users may be forced to migrate to new versions. - Possibly incurring unforeseen training costs and shifts in operating procedures. • Reliance on a network connection, which may be slower, less stable, and less secure. • Data assets stored o -site may lead to security and legal concerns. • Limited con guration, customization, and system integration options compared to packaged software or alternatives developed in-house. • User interface of Web-based software is less sophisticated and lacks the richness of most desktop alternatives. • Ease of adoption may lead to pockets of unauthorized IT being used throughout a rm.
Types of Business Analytics in Excel
Descriptive - Pivot table Predictive - Predictive Modeling Prescriptive- Goal Seek
Regression Analysis
Determines and measures the degree of influence of independent variables on dependent variables. Used to: Develop a predictive model Test a hypothesis Model the relationship between two variables One-way analysis of variance
Which business division relies the most on business analytics? A. Finance B. Accounting C. Marketing D. Human Resources E. All of the above
E. All of the above
Black Swans
Events that cannot be predicted but can cause an impact. Scalable computing resources can help a rm deal with spiking impact from Black swan events.
Server Farm
MASSIVE NETWORK OF COMPUTER SERVERS RUNNING SOFTWARE TO COORDINATE THEIR COLLECTIVE USE • Provide the infrastructure backbone to SaaS, hardware cloud e orts, and many large-scale Internet services. • Require plenty of cheap land, low-cost power, ultrafast ber-optic connections, and benefit from mild climates. • Google, Sun, Microsoft, IBM, and HP have all developed rapid-deployment server farm modules.
Moore's Law Microprocessor Random Access Memory (RAM) Volatile Memory
MOORE'S LAW • Chip performance per dollar doubles every eighteen months. MICROPROCESSOR • Part of the computer that executes the instructions of a computer program . RANDOM ACCESS MEMORY (RAM) • Fast, chip-based volatile storage in a computing device. VOLATILE MEMORY • Storage that is wiped clean when power is cut o from a device.
Hybrid Cloud
Software, hardware and platforms are hosted both in third party data centers as well as internally value flexibility and benefits of private and public cloud while addressing data security, governance, compliance and budgetary
Cloud Offerings
Hardware and software exists "in the cloud," meaning somewhere on the Internet. • You only pay for the amount of processing, storage, and telecommunications used. • Cloud vendors typically host your software on their systems. • Cloud computing e orts focus on providing a virtual replacement for a subset of operational hardware like storage and backup solutions. • SaaS provides the software and hardware to replace an internal information system. - A rm replaces software and hardware with a service provided by a third party online.
More about cloud computing
In addition, the platform provides on demand services, that are always on, anywhere, anytime and any place. Pay for use and as needed, elastic - scale up and down in capacity and functionalities The hardware and software services are available to - general public, enterprises, corporations and businesses markets
How is Business Analytics being used today?
Kewton provides educators with applications that calibrate learning content based on data analytics of thousands of students taking digital courses A major insurance underwriter integrated radar data, geo maps, and aviations images to create predictive models for writing property insurance policies GE is creating software that will help customers utilize predictive analytics to spot mechanical issues before they become problems1
Open Source Software -Linux -LAMP
Linux: Open source software operating system. • Source code for OSS products is openly shared. - Can be changed and redistributed by anyone. • In stark contrast to the practice of conventional software rms who: - Treat their intellectual property as closely guarded secrets. - Almost never provide the source code for their commercial products. • Seen by some rms as a threat that undermines their economic model. • LAMP: Acronym for Linux, Apache Web server software, MySQL database, and Perl/Python/PHP. - Powers many of the sites visited each day, from Facebook to YouTube.
Operating system
PROVIDE A COMMON SET OF CONTROLS FOR MANAGING COMPUTER HARDWARE • Make it easier for users to interact with computers and for programmers to write application software. • User interface: Mechanism through which users interact with a computing device. • Firmware: Software stored on nonvolatile memory chips. • Embedded Systems: Special-purpose software designed and included inside physical products.
Platform as a Service Infrastructure as a Service
Platform as a service (PaaS): Cloud providers offer services for customers to build their own applications on the provider's infrastructure. - Services include hardware, operating system, tools, and hosting. • Infrastructure as a service (IaaS): Cloud providers offer services that include running the remote hardware, storage, and networking. - Client rms can choose the software used.
Business Analytics
Refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.
Cloud Computing Network
Shared pool of configurable computing resources On-demand network access Provisioned by the Service Provider
The shift to data centricity is critical for the vitality of all business and industries
Shift 1- data is becoming the world's new natural resource, transforming industries and professions Shift 2- the emergence of Cloud is transforming IT and business processes into digital services Shift 3- Mobile and social are transforming individual engagement- creating expectations of security, trust and value in return for personal information
Cloud Service Models
Software as a Service (SaaS) - SalesForce CRM Platform as a Service (PaaS) - Deploy customer created applications Google App Windows Azure Infrastructure as a Service (IaaS) - Rent Processing, storage, N/W capacity & computing resources Amazon web services backspace hosting
Data Warehouses and Data Marts
Structured for fast online queries and exploration. • Collects data from many di erent operational systems. • Data mart: Database or databases focused on addressing the concerns of a speci c problem or business unit.
Introduction to Machine Learning
The role of data in a machine learning Data scientists spend a significant portion of their time dealing with data access, volume and integration
Business Intelligence (BI)
To enable interactive access to data ... and to give business managers and analysts the ability to conduct appropriate analysis. By analyzing historical and current data ... decision makers get valuable insights that enable them to make more informed and better decisions. Opportunities Falling Sales Shrinking Profits Cost Increases Raw Material Shortages ChangingTastes Cash Flow/Credit Issues Competitor Behavior The Weather Existing Market Growing New Market to Target Complementary Products Your Competitor Fails Partnerships Innovations Regulatory Changes The Weather
Conjoint Analysis
Trade-off analysis Measure the relative values of attributes jointly rather than in isolation Example: Determining whether customers make choices based on shopping convenience or lower prices.
Cloud Bursting
Use of cloud computing to provide excess capacity during periods of spiking demand. It is a scalability solution that is provided as an over ow service, kicking in as needed.
What-if Analysis
Uses existing data and estimated data points to calculate a range of probable outcomes Example: Using fixed product costs and estimated variable costs (raw material costs, special sales, wholesale pricing) to determine a range of probable profit margins.
Data Mining
Using computers to identify hidden patterns in large data sets and to build models from this data • Models based on: - Customer segmentation and market basket analysis. - Marketing and promotion targeting. - Collaborative ltering and customer churn. - Fraud detection, nancial modeling, hiring and promotion. • Prerequisites - Organization must have clean, consistent data. - Events in that data should re ect trends.
Sharing data and keeping secrets
Walmart shares sales data only with relevant suppliers: - Stopped sharing data with information brokers. - Custom-builds large portions of its information systems to keep competitors o its trail. - Other aspects of the rm's technology remain con dential.
Cluster Analysis
classify data in groups example: customers grouped by price sensitivity and brand loyalty (two clusters0
Variables to consider for technology
competitive advantage, skill/expertise, security, cost & time, legal & compliance requirements, vendor issues
Machine Learning Basics
influencing nearly everything we do... Machine learning is everywhere, Identifies patterns in historical data Builds/trains behavioral models from patterns Makes recommendations
Cloud computing Characteristics Essentials
on demand self service, broad network access, rapid elasticity, resource pooling and measured service
Big data and Decision Making
• Big data: The collections, storage, and analysis of extremely large, complex, and often unstructured data sets that can be used by organizations to generate insights that would otherwise be impossible to make. • The massive amount of data available to today's managers. - Unstructured, big, and costly to work through conventional databases. - Made available by new tools for analysis and insight. • Decision making is data-driven, fact-based and enabled by: - Standardized corporate data. - Access to third-party datasets through cheap, fast computing and easier-to-use software.
Business intelligence Analytics Machine Learning
• Business intelligence (BI): Combines aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis. • Analytics: Driving decisions and actions through extensive use of: - Data - Statistical and quantitative analysis - Explanatory and predictive models - Fact-based management • Machine Learning: leverages massive amounts of data so that computers can act and improve on their own without additional programming.
Excel Stuff
• Cell References (Cengage EX 162-163) • Relative References Formulas in a cell are referenced relative to the cell containing the formula • Absolute References ($) Cell references remain xed even when the formula is copied to a new cell • Lookups • VLOOKUP: Retrieves a value from a vertical lookup table • Logical Functions • IF
Data Warehouses and Data Marts
• Marts and warehouses may contain huge volumes of data. • Building large data warehouses can be expensive and time consuming. • Large-scale data analytics projects should build on visions with business- focused objectives.
Enterprises that Have Bene ted from Data Mastery
• Data leverage is at the center of competitive advantage in rms such as Amazon, Net ix, and Zara. • Walmart: Moved to the top of the Fortune 500 list. • Encourages rms to make their product the best it possibly can • Data-driven insights are credited with helping politicians win elections.
Database Database management system structured query language (SQL) Database administrator (DBA)
• Database: Single table or a collection of related tables • Database management systems (DBMS): Software for creating, maintaining, and manipulating data - Known as database software • Structured query language (SQL): Used to create and manipulate databases • Database administrator (DBA): Job focused on directing, performing, or overseeing activities associated with a database or set of databases - Database design and creation - Implementation - Maintenance - Backup and recovery - Policy setting and enforcement - Security
Cloud Services
• Examples of hardware cloud services: - Salesforce.com o ers Force.com. • Includes several cloud-supporting tools to write applications speci cally tailored for Web-based delivery. - Google's App Engine o ers developers several tools. • Including a database product called Big Table. - Microsoft o ers Windows Azure.
Challenges
• Finding huge markets or dramatic cost savings to boost pro ts and continue to move its stock price higher. • Criticisms: - Accusations of sub-par wages draw union activists. - Poor labor conditions at some of the rm's contract manufacturers. - Demand prices so aggressively low that suppliers end up cannibalizing their own sales at other retailers.
Maintaining Data Warehouses and Data Marts
• Firms can address the broader issues needed to design, develop, deploy, and maintain its system through data: - Relevance - Sourcing - Quantity and quality - Hosting - Governance
Enterprise Software
• Firms set up systems to gather additional data beyond conventional purchase transactions or Website monitoring. • Customer relationship management systems (CRM) - Empower employees to track and record data at nearly every point of customer contact. • Includes other aspects that touch every aspect of the value chain, including SCM and ERP.
Surveys
• Firms supplement operational data with additional input from surveys and focus groups. • Direct surveys can give better information than a cash register. • Many CRM products have survey capabilities that allow for additional data gathering at all points of customer contact.
Data mining process
• Gets data from varying environmental conditions. • Protects the rm from a retailer's twin nightmares: - Too much inventory - Too little inventory • Helps the rm tighten operational forecasts. - Enables prediction. • Data drives the organization. - Reports form the basis of sales meetings and executive strategy sessions.
Insights from Unstructured Big Data
• Hadoop: Made up of half-dozen separate software pieces and requires the integration of these pieces to work • Advantages: - Flexibility - Scalability - Cost e ectiveness - Fault tolerance
Cloud Computing Challenges
• Installing a complex set of systems on someone else's hardware is very di cult. • Firms considering cloud computing need to do a thorough nancial analysis. • Firms should enter the cloud cautiously, particularly where mission-critical systems are concerned.
Walmart: Data-Driven Value Chain
• Largest retailer in the world. - Source of competitive advantage is scale. • E ciency starts with a proprietary system called Retail Link. - Retail Link: Records a sale and automatically triggers inventory reordering, scheduling, and delivery. - Inventory turnover ratio: Ratio of a company's annual sales to its inventory. • Back-o ce scanners keep track of inventory as supplier shipments come in.
Benefits of SAAS to users
• Lower costs and nancial risk mitigation. • Faster deployment times and variable operating expense. • Scalable systems. • Higher quality and service levels. • Remote access and availability. • Limits development to a single platform. • Tighter feedback loop. • Ability to instantly deploy bug xes and product enhancements. • Lower distribution costs. • Greater accessibility. • Reducing software piracy.
Software Industry -marginal cost -open source software (OSS) -cloud computing -software as a service (SaaS) -Virtualization
• Marginal cost: Cost of producing one more unit of a product - Is e ectively zero to produce an additional copy of a software product. • Network e ects and switching cost can o er a degree of customer preference and lock in. • Open source software (OSS): Software that is free and where anyone can look at and potentially modify the code. • Cloud computing: Replacing computing with services provided over the Internet. - Software as a service (SaaS): Firm subscribes to a third-party software and receives a service that is delivered online. Virtualization: Technology that can make a single computer behave like many separate computers. Helps consolidate computing resources and creates additional savings and e ciencies.
Formulas and Functions
• Using Constants • Functions • AVERAGE • COUNT, COUNTA • INT • MAX • MEDIAN • MIN • RAND • ROUND • SUM
Problems in Data Mining
• Using bad data can give wrong estimates, thus exposing the rm to risk. • When the market does not behave as it has in the past, computer-driven investment models are not e ective. • Overengineering: Building a model with so many variables that the solution arrived at might only work on the subset of data used to create it.
So why do Business Majors need to care about Cloud Computing?
• Utility computing models save money • Subscription services provide on-demand compute power that would otherwise be too expensive to purchase • The Amazon Growth Cycle
Marketing
● Firms are shifting advertising spending from traditional media to the Web because of its ability to ― Track and target customers ― Analyze campaign results ● Firms are using social media to ― Generate sales ― Improve their reputations ― Better serve customers ● Firms use lots of di erent types of Information Systems such as Customer Relationship Management (CRM) systems
Accounting
● The reliability of any audit is inherently tied to the reliability of the underlying technology ● Increased regulation (e.g., the Sarbanes-Oxley Act) has strengthened the link between Accounting and IT ● Major accounting firms have spawned IT- focused consulting practices
