Decision Support Systems - Application Case 2

1. What capabilities of a wiki are not available in email?

Answer : From my point of view, I think what wiki does that email couldn’t do the same is to edit someone else’s post because in email it is already fix. The interaction between users is limited to give and take, while wiki enables a discussion session about particular post or document where users can interact with it.

2. Describe the applications of wikis in finance and operations.

Answer : Wiki helps them to eliminate the cumbersome number of emails, view the development of business plans, store commonly used information, and create a forum to make interactions between one and another user.

3. How does DrKW’s wiki increase employee productivity?

Answer : Ofcourse, wiki makes employee’s work environment become more convenient and connected to each other and eventually it will make their productivity higher.

4. How does DrKW’s wiki help with foreign language and training?

Answer : Enables the users to edit the intranet quickly and easily for foreign users by helping them build an internal glossary that defines company jargon through employees doing similar jobs. That consider as effective and efficient training method.

Decision Support Systems - Application Case 2

Based on the case

1. What capabilities of a wiki are not available in email?

Wiki can track project development so that the team and management know what progress has been made, regardless of individual geographic locations, and to raise the team's awareness about what each person is doing, the status of each project, and what actions should follow.

Decision Support Systems - Application Case 2

1.Capabilities of a wiki that are not available in email:

• information sharing for users, freely update information
• wiki allows to provide feedbacks from users
• different ways of communication

2.Applications of wikis in finance and operations:

• can improve the communications
• provides status update for users
• organize meeting agendas
• external communications with clients
• can act as a medium to collect resources

Decision Support Systems - Application Case 2

What capabilities of a wiki are not available in email?

the wiki allow all team members to upload information more easily which encourages collaboration and transparency by making the sharing of email conversations and other ideas uncomplicated.

Describe the applications of wikis in finance and operations.

Finance:

application of wikis can strengthens business relationship among employees, especially among employees who have never met by by using communicating tools.

Decision Support Systems - Application Case 2

1. What capabilities of a wiki are not available in email?

The capabilities that wiki have is a structure that a geographically dispersed, publication and collaboration skill through the workspace. And wiki has an important roles that is tracking project development so that the team and management know the progress

2. Describe the applications of wikis in finance and operations.

They use the unit deals with the loans, equity swaps, and the other so it will eliminate the cumbersome number of emal, view the development of the business plan and store the useful information

Balanced Scorecard

1. What are the four perspectives in BSC ?

• Customer. Encourages the identification of measures that answer the question "How do customers see us?" Examples: percent of sales from new products, on time delivery, share of important customers' purchases, ranking by important customers.
• Financial. Encourages the identification of a few relevant high-level financial measures. In particular, designers were encouraged to choose measures that helped inform the answer to the question "How do we look to shareholders?" 
• Internal Business Processes. Encourages the identification of measures that answer the question "What must we excel at?" Examples: cycle time, unit cost, yield, new product introductions.
• Learning and Growth. Encourages the identification of measures that answer the question "How can we continue to improve, create value and innovate?". Examples: time to develop new generation of products, life cycle to product maturity, time to market versus competition.

2. What does the term balanced refer to in BSC ?

The term balanced means BSC make sure the balance of four perspectives in BSC, because 

BSC designed to overcome the limitation of system that are financially focused.

3.What is strategy map ?

A visual display that delineates the relationships among the key organizational objectives for all four BSC perspectives  

Administration and Security of Data Warehouse

1. Steps to ensure the security of data warehouse

• Isolate sensitive databases: maintain an accurate inventory of all databases deployed across the enterprise and identify all sensitive data residing on those databases.
• Eliminate vulnerabilities: continually assess, identify and re-mediate vulnerabilities that expose the database.
• Enforce least privileges: identify user entitlements and enforce user access controls and privileges to limit access to only the minimum data required for employees to do their jobs.
• Monitor for deviations: implement appropriate policies and monitor any vulnerabilities that cannot be re-mediated for any and all activity the deviates from authorized activity.
• Respond to suspicious behavior: alert and respond to any abnormal or suspicious behavior in real time to minimize risk of attack.

Benefits of Data Warehouse

1. Benefits of data warehouse

• Enhances data quality and consistency - Insights will be gained through improved information access.  Managers and executives will be freed from making their decisions based on limited data and their own "gut feelings".  Decisions that affect the strategy and operations of organizations will be based upon credible facts and will be backed up with evidence and actual organizational data.
• Saves time - Since business users can quickly access critical data from a number of sources, all in one place, they can rapidly make informed decisions on key initiatives. They won't waste precious time retrieving data from multiple sources.
• Generates a high ROI - Companies that have implemented data warehouses and complementary BI systems have generated more revenue and saved more money than companies that haven't invested in BI systems and data warehouses. According to a 2002 International Data Corporation (IDC) study "The Financial Impact of Business Analytics", analytics projects have been achieving a substantial impact on a business' financial status.
• Increased query and system performance - Data warehouses are purposely designed and constructed with a focus on speed of data retrieval and analysis.  Moreover, a data warehouse is designed for storing large volumes of data and being able to rapidly query the data.

Architectures of Data Warehouse

1. What are the key similarities and difference between two-tier and three-tier architecture?

Similarities: 

Give user an interface to access and use application and data warehouse

Differences:

2-tier, Data warehouse and Application in one machine

3-tier, Data warehouse and application in different machine

2. how the web influenced data warehouse design?

with the web, the application and data warehouse can be placed in the server and the user interface also can be displayed in web browser.

Data Warehouse - What is Data Integration

What is data integration?

Data integration is a process in which heterogeneous data are retrieved and combined as an incorporated form and structure. Data integration allows different data types (such as data sets, documents and tables) to be merged by users, organizations and applications, for use as personal or business processes and/or functions.

Data integration primarily supports the analytical processing of large data sets by aligning, combining and presenting each data set from organizational departments and external remote sources to fulfill integrator objectives. 

Real-Time Data Warehouse

1. RDW(Real-time Data Warehouse)Definition

A Real-time data warehouse is a process of decision support that is up to date and ongoing when all business transactions occur. Real-time data warehouse is usually also called as active data warehouse.

2. Benefits of using a real-time data warehouse

• RDW is making a better quality from the traditional data warehouse 
• Propagate decision making process until a tactical level and maybe going to the operational level. 
• Users can interact with customers and suppliers directly 

Processes in Data Mining

Processes in Data Mining

To carry out projects in Data Mining systematically, a process that generally applies is usually applied. Based on 'best practice', practitioners and researchers DM proposes several processes (workflows or approach step-by-step simple) to increase the chances of success in implementing projects DM. Efforts that eventually resulted in several processes that serve as standards, some of which (the most popular) are discussed in this section.

Myths and Blunders in Data Mining

Data mining is a great analitics tool. Data mining helps many manager to see customer behaviour. Result in data mining is to increase revenue, to decrease production cost, and to discover fraud. Data mining is usually linked into many myths, below are some of them.

• Data mining give instant results, this is not true because data mining is a step by step that need many consideration.
• Not yet ready for business, this is the best to implement in business environment.
• Need a separated  database, data mining can use available data base.
• only those with high technology that only can use it.
• only for big company

Real Life Implementation of Data Mining

Real Life Implementation of Data Mining 

From the examples stated in the article in this link about "Real Life Implementation of Data Mining", the conclusions are pretty much simple.

To begin with, i think all of us should first take an understanding about the definition of this so called "Data Mining" itself. Data Mining is a computational process of digging through a collection of data to find unique patterns and behaviours by using mathematical formula in order to help users to make a future prediction about what's going to happen to their organization in the near future. To simplify this, Data Mining is a computational process of finding predictions about what's going to happen in the future, like a psychic.

How Data Mining Works

Data mining creates few model to identify patterns on attributes which is inscribed on dataset. Some of those patterns will create  “descriptive” results, whereas some pattern creates “Predictive” results.

Generally, data mining identifies four kind of main patterns: 

• Associations : groups same or similar events, for example a purchase of same item at supermarket.
• Predictions : forecast future events based on historical record. For example: predict future world cup winner based on winning streak pattern.
• Clusters :  groups objects based on known characters, for example create a customer differentiation based on purchase history.
• Sequential relationships : find a relation between events, for example :  predict a customer whom purchased a car will purchase spare parts a year later.

These general patterns are extracted from data manually for hundred years, but increased data volume on modern times demands  an automated approach. The automated (or semi – automated) approach which analyzes very large amount of dataset is called Data Mining.

Methods in Data Mining

Classification

In data mining classification perhaps considered being the most used method for problem solving. Classification studies the patterns of historical data (a set of information - like characteristics, variables, features - on a variety of characteristics of the items that have been labeled previously) for the purpose of placing new instances (objects) into groups or classes. For example classifications can be used to predict weathers, frauds, communications, and other class labeled conditions. However when the condition type to be predicted is in a numerical data it cannot be called classifications instead of regression.

Various Data Mining Tools

Examples of data mining tools are SPSS (PASW Modeler, formerly known as Clementine), SAS (Enterprise Miner), StstSoft (Statistica Data Miner), Salford (CART, MARS, TreeNet, RandomForest), Angoss (KnowledgesSTUDIO, KnowledgeSeeker), and Megaputer (PolyAnalyst).

BI tools such as IBM Cognos, Oracle Hyperion, SAP Business Objects, Microstrategy, Teradata, and Microsoft only focused on multi-dimensional modeling and data visualization and not intended to be competitor of data mining tools.

Data Perprocessing - Online Quiz Data Mining - by Ria Liuswani - 1501144950

Tahap awal dan sekaligus tahap yang paling penting dalam data mining adalah ‘data preprocessing’. Apa saja bentuk atau teknik dalam data preprocessing?

by Ria Liuswani  - 1501144950

Pre processing dapat dilakukan dengan beberapa teknik yaitu:

Data Mining for Business Intelligence - Application and Data Mining Concept

Application and Data Mining Concept

Definition of Data mining in BI is a step for developing businesses that created by gathering the data, organize, and save them in the organization. The techniques of data mining is very global and itself get used widely by many companies.

The first component of the data mining is begin with analyzing the total of the data that much more to gathered inside the company. 

List And Describe The Major Issues in Modeling

List and describe the major issues in modeling:

• Problem identification and environmental analysis (information collection)
• Variable identification
• Influence diagrams, cognitive maps
• Forecasting/predicting
• More information leads to better prediction
• Multiple models: A MSS can include several models, each of which represents a different part of the decision-making problem
• Categories of models 
• Model management