Hub You - Computers and Technology

Newsletter Formatting
Formatting your text newsletter correctly can make a failure into a success! Learn how to do it, and why.Why using a text newsletter?Sending an email (newsletter) in text format instead of word or html format will allow everyone on the internet to read it. No special software or utility will be needed.However, to really make it work, consider the following.• Make sure you use a monospaced font. A font where the width of the letter i is the same as the letter w. The letters may look different in width, but if you use a monospaced (instead of proportional) font, the space each character use, will be the same. This is necessary to be able to use row length row breaks and alignment.• As said above the monospaced font in your newsletter will allow you to format your newsletter to use for example 65 characters width. This is pretty much the standard number of characters used in a newsletter today.• Also, remember that things like underline, bold, italic, left, center, right and justified are adjustments not allowed in pure text, as they require special formatting.• Use white space to make reading easier. Allow for two or more empty lines between content that is different.• Also, make sure your formatting includes some kind of planning. This will allow you to maintain a similar look for your newsletter in each issue and that makes reading easier for your subscribers.Tools of the tradeUse things like newsletter templates to make creation and publishing of your newsletter easier. Make sure you use the correct tool to write and format your newsletter.

rong>In the same context, we should understand the components of Decision support systems (DSS).Components of DSS The primary components of a DSS are a database management system (DBMS), the User Interface (Dialog) Subsystem, the Knowledge Based (Management) Subsystem.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

ID Cards
ID cards are used for a number of different reasons and come in many shapes and sizes. Convenient for any business or individual, ID cards can make a world of difference in the efficiency and safety of your security and identification system. ID cards are designed for everyone from employees to students over a wide variety of fields.Schools:ID Cards are ideal for schools because they offer a higher amount of security for teachers, students, and school employees. For example, implementing an ID Card System would limit the entrance of unidentified individuals into the school by requiring an ID Card upon entering school premises. This would increase the school’s security and promote a safe environment. Another reason they might be used in a school environment has to do with safety. If every student, teacher and employee has to have an ID Card, identification in emergency situations would be far easier to achieve.Businesses:ID Cards are ideal for businesses because they allow the employees to feel secure and safe in their work environment. Many large corporations require identification cards and badges for their employees to maintain the confidentiality of their projects and safety of their workers. An ID Card would limit the number of unauthorized visitors and ensure the privacy and safety of a work environment.They prevent theft and vandalism, such as corporate espionage and thieves, while promoting an atmosphere of safety and privacy. They are the most efficient and effective way to ensure the security and safety of your business. Besides supporting the integrity of the workplace

As we know, decision making is the fundamental job of managers and there are various information systems i.e. Management information systems (MIS), Executive information system (EIS) that are helping managers in decision making process. Our central consideration point of this article is DSS and its roles in management perspectives. We will discuss –

The role played by DSS in the process of decision making
The changes coming in scenario about the role of DSS in decision making.

DSS is a system that supports technological and managerial decision making by assisting in the organization of knowledge about structured, semi structured, or unstructured issues.

Decision Support Systems (DSS) are a class of computerized information system that supports decision-making activities. DSS are interactive computer-based systems and subsystems intended to help decision makers use communications technologies, data, documents, knowledge and/or models to complete decision process tasks.

Decision Support Systems have evolved over the last 25 years from inflexible mainframe systems, to isolated PC tools, to client/server data dippers, and now to high-performance and extensible enterprise decision-support applications, often involving the organization’s intranet. At the same time, the relationship between the IT Department and users has evolved from stormy to co-operative.

The huge umbrella of decision support systems (DSS) has long provided a welcome gathering spot for those interested in building software applications based on a mixture of models, data analysis, and powerful interfaces. DSS attracts practitioners, scholars and students from a range of fields including information systems, operations research/management science, computer science, psychology and other business disciplines.

The problem: There has been a virtual revolution in terms of spreadsheet based management science and operations management courses that seems to have stuck in business schools. Spreadsheets have evolved into a quite capable platform for end-user decision support modeling.

For example, within Microsoft Excel, this evolution has resulted in the inclusion of Solver for optimization, Pivot Tables, database connectivity, numerous mathematical and statistical functions and the Visual Basic for Applications (VBA) programming language.

The problem is coming from this picture where instead of using management skills for making decision, managers are very much dependent on DSS tools for making decisions. It might be more crucial when new managers will have lack of management skills and they will totally dependent on DSS tools.

So, we can make questions:

What are the reasons behind that managers are depending so much on DSS tools?
What should be the optimized ratio of using desktops and management skills for decision making?

My Idea: First of all we have to understand decision making model: the set of activities that DSS environments support. The key elements of this model are fairly common, and include:

A decision-maker: an individual or group charged with making a particular decision.
A set of inputs to the decision-making process: data, numerical or qualitative models for interpreting that data, historical experience with similar data sets or similar decision-making situations, and various kinds of cultural and psychological norms and constraints associated with decision-making
The decision-making process itself: a set of steps, more or less well-understood, for transforming the inputs into outputs in the form of decisions,
A set of outputs from the decision-making process, including the decisions themselves and (ideally) a set of criteria for evaluating decisions produced by the process against the set of needs, problems or objectives that occasioned the decision-making activity in the first place.
As soon as we look at this model, we realize that talking about decision support systems outside of a particular domain of decision-making is not particularly useful.

If we considered only the timeframe in which a given decision has to be made and the risks and constraints associated with the decision-making process, we would recognize that there is a great deal of qualitative and quantitative difference between governmental agencies, not-for-profit (NFP) organizations, and commercial firms. Put simply, commercial decisions, in the aggregate, have the shorter timeframes and higher associated risks (including extinction) than either public sector or not-for-profit decisions, and as such would presumably require the most assistance from information technology.

For this reason alone, this essay limits its scope to commercial decision support systems: IT infrastructure designed to support the decision-making processes in publicly-held and private firms that compete in open markets for customers, revenue and market share.

How do DSS environments support decision-making? DSS environments support the generic decision-making model above in a number of ways:

In decision preparation, DSS environments provide data required as input to the decision-making process. This is all about data mart and data warehousing environments do today.
In decision structuring, DSS environments provide tools and models for arranging the inputs in ways that make sense to frame the decision. These tools and models are not pivot tables and other aspects of data presentation found in query tools. They are actual decision making tools, like fault tree analysis, Bayesian logic and model-based decision-making based on things like neural networks.
In context development, DSS environments again provide tools, and provide the mechanisms for capturing information about a decision’s constituencies (who’s affected by this decision), outcomes and their probabilities, and other elements of the larger decision making context.
In decision-making, DSS environments may automate all or part of the decision-making process and offer evaluations on the optimal decision. Expert systems and artificial intelligence environments purport to do this, but they work only in very limited cases.
In decision propagation, DSS environments take the information gathered about constituencies and dependencies and outcomes and drive elements of the decision into those constituencies for action.
In decision management, DSS environments inspect outcomes days, weeks and months after decisions to see if (a) the decision was implemented/propagated and (b) if the effects of the decision are as expected.

What is required is to-

Pick the class of decision-making processes to focus on,
Narrow the range of inputs, the range of activities and the differences in models and methods,
Most importantly, to understand where technology ceases to play any meaningful role in decision-making, and where policy becomes the determinant of the quality and quantity of decisional effectiveness.

Related work:In the same context, we should understand the components of Decision support systems (DSS).Components of DSS The primary components of a DSS are a database management system (DBMS), the User Interface (Dialog) Subsystem, the Knowledge Based (Management) Subsystem.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

Web 2.0 Tactics That Shoot Your Traffic Through The Roof!
Web 2.0 finally hit the Internet over the past few years. If you’re not aware yet, this simply means another opportunity for marketers to market their business! Web 2.0 is the present and the near future, and if you’re only using old school marketing tactics (which still great, I must say), then you’ll be losing out to your competition.This article will share a few ways to drive in traffic to your website using advanced Web 2.0 tactics:1) Viral Marketing (Web 2.0 style)Post up a content-packed video on YouTube and make it viral by saying at the end of your video: “If you liked this video, feel free to post it to your website or send it to a friend.” This simple sentence will drive in loads of visitors you otherwise would not have. It is how MSN’s hotmail spread so quickly!2) BloggingAlmost everyone on the Internet has a blog these days, and your business should have one too. Start a blog at a service such as Blogger or Wordpress and send traffic to it. Allow your visitors to post comments on your articles. Web 2.0 is all about interactivity!3) Social NetworkingVisit all the biggest social networking websites and start creating an account! Create an intriguing profile and expand your circle of friends through the network. Provide some good information that educates people in your profile, so that they will be enticed to click through to your website. Use bulletins to make announcements to your list of friends.The best thing about these tactics is that they are all free...

rong>The problem: There has been a virtual revolution in terms of spreadsheet based management science and operations management courses that seems to have stuck in business schools. Spreadsheets have evolved into a quite capable platform for end-user decision support modeling.

So, we can make questions:

What are the reasons behind that managers are depending so much on DSS tools?
What should be the optimized ratio of using desktops and management skills for decision making?

My Idea: First of all we have to understand decision making model: the set of activities that DSS environments support. The key elements of this model are fairly common, and include:

A decision-maker: an individual or group charged with making a particular decision.
A set of inputs to the decision-making process: data, numerical or qualitative models for interpreting that data, historical experience with similar data sets or similar decision-making situations, and various kinds of cultural and psychological norms and constraints associated with decision-making
The decision-making process itself: a set of steps, more or less well-understood, for transforming the inputs into outputs in the form of decisions,
A set of outputs from the decision-making process, including the decisions themselves and (ideally) a set of criteria for evaluating decisions produced by the process against the set of needs, problems or objectives that occasioned the decision-making activity in the first place.
As soon as we look at this model, we realize that talking about decision support systems outside of a particular domain of decision-making is not particularly useful.

How do DSS environments support decision-making? DSS environments support the generic decision-making model above in a number of ways:

In decision preparation, DSS environments provide data required as input to the decision-making process. This is all about data mart and data warehousing environments do today.
In decision structuring, DSS environments provide tools and models for arranging the inputs in ways that make sense to frame the decision. These tools and models are not pivot tables and other aspects of data presentation found in query tools. They are actual decision making tools, like fault tree analysis, Bayesian logic and model-based decision-making based on things like neural networks.
In context development, DSS environments again provide tools, and provide the mechanisms for capturing information about a decision’s constituencies (who’s affected by this decision), outcomes and their probabilities, and other elements of the larger decision making context.
In decision-making, DSS environments may automate all or part of the decision-making process and offer evaluations on the optimal decision. Expert systems and artificial intelligence environments purport to do this, but they work only in very limited cases.
In decision propagation, DSS environments take the information gathered about constituencies and dependencies and outcomes and drive elements of the decision into those constituencies for action.
In decision management, DSS environments inspect outcomes days, weeks and months after decisions to see if (a) the decision was implemented/propagated and (b) if the effects of the decision are as expected.

What is required is to-

Pick the class of decision-making processes to focus on,
Narrow the range of inputs, the range of activities and the differences in models and methods,
Most importantly, to understand where technology ceases to play any meaningful role in decision-making, and where policy becomes the determinant of the quality and quantity of decisional effectiveness.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

Purchasing And Selling Online
With the increase in costs of auction websites for people to buy or sell online items like household appliances or outdoor commodities, many people are focusing towards free classifieds websites for selling or purchasing items because of free cost and the traffic they generates towards the advertisements.Auction websites are ideal for individuals who place high price on their items. People who are looking for paying high amount to purchase their desired items or who will not negotiate on high price for items which they are selling can use these websites. The merits of these websites are that they are free of spam and transactions are made through secure payment gateways which will be easy for people to deal with international buyers or sellers. The only demerits are that they charge high for auctioning items including extra price for tagging graphics with them and there will be no contact between the owners and buyers.The affordable and productive alternative to auction websites is online free classifieds. The classified ads owners who want to sell their items should mention all the necessary details of them in the advertisements and instantly there will be grabbed by potential buyers. The ad owners who want to purchase any desired items can browse related advertisements for selecting the required items, even if they do not find ads, they can place their advertisements mentioning the items sought along with the required details like price, color, age or warranty and directly they will be attracted by item sellers. It is the task of classified ad owners who are purchasing or selling items t

for transforming the inputs into outputs in the form of decisions,

A set of outputs from the decision-making process, including the decisions themselves and (ideally) a set of criteria for evaluating decisions produced by the process against the set of needs, problems or objectives that occasioned the decision-making activity in the first place.

As soon as we look at this model, we realize that talking about decision support systems outside of a particular domain of decision-making is not particularly useful.

How do DSS environments support decision-making? DSS environments support the generic decision-making model above in a number of ways:

In decision preparation, DSS environments provide data required as input to the decision-making process. This is all about data mart and data warehousing environments do today.
In decision structuring, DSS environments provide tools and models for arranging the inputs in ways that make sense to frame the decision. These tools and models are not pivot tables and other aspects of data presentation found in query tools. They are actual decision making tools, like fault tree analysis, Bayesian logic and model-based decision-making based on things like neural networks.
In context development, DSS environments again provide tools, and provide the mechanisms for capturing information about a decision’s constituencies (who’s affected by this decision), outcomes and their probabilities, and other elements of the larger decision making context.
In decision-making, DSS environments may automate all or part of the decision-making process and offer evaluations on the optimal decision. Expert systems and artificial intelligence environments purport to do this, but they work only in very limited cases.
In decision propagation, DSS environments take the information gathered about constituencies and dependencies and outcomes and drive elements of the decision into those constituencies for action.
In decision management, DSS environments inspect outcomes days, weeks and months after decisions to see if (a) the decision was implemented/propagated and (b) if the effects of the decision are as expected.

What is required is to-

Pick the class of decision-making processes to focus on,
Narrow the range of inputs, the range of activities and the differences in models and methods,
Most importantly, to understand where technology ceases to play any meaningful role in decision-making, and where policy becomes the determinant of the quality and quantity of decisional effectiveness.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

Profitability And Stock Turn Rate
The inventory of the typical store represents the largest single element of its total assets. The sale of goods from this inventory is the merchant's chief source of operating profit. Thus, the way in which this merchandise investment is put to work is of utmost importance in achieving a profitable operation.To illustrate, a retailer may carry an average retail inventory of $200,000, with sales of $400,000, resulting in a 2.0 Stock Turn Rate. If this retailer had the same $400,000 sales but a 3.0 Stock Turn Rate, the average retail inventory would be $133,300. This is a difference of $66,700 at retail or approximately $32,000 at cost.The cost of owning excess inventory is approximately 2?% per month, or 30% per year. This is due to increased expenses such as interest, insurance, buying expense, receiving department expense, property taxes, markdowns and shrinkage. Therefore, a retailer can reduce these expenses by reducing his average inventory level. In the example above, the annual savings would be approximately $10,000 ($32,000 times 30%).All other things being equal, a higher stock turn rate tends to lead to higher sales and a higher profit, which should be an essential goal of every merchant. I will discuss this more later, but first we must have a good understanding of what Stock Turn Rate is and how it is to be computed.WHAT IS STOCK TURN RATE?Stock Turn Rate can be computed using units, cost dollars or retail dollars. For comparative purposes, it is desirable that the Stock Turn Rate calculation be standard. We advocate retail, which is the generally accepted method in the retai

>, DSS environments provide tools and models for arranging the inputs in ways that make sense to frame the decision. These tools and models are not pivot tables and other aspects of data presentation found in query tools. They are actual decision making tools, like fault tree analysis, Bayesian logic and model-based decision-making based on things like neural networks.

In context development, DSS environments again provide tools, and provide the mechanisms for capturing information about a decision’s constituencies (who’s affected by this decision), outcomes and their probabilities, and other elements of the larger decision making context.

In decision-making, DSS environments may automate all or part of the decision-making process and offer evaluations on the optimal decision. Expert systems and artificial intelligence environments purport to do this, but they work only in very limited cases.

In decision propagation, DSS environments take the information gathered about constituencies and dependencies and outcomes and drive elements of the decision into those constituencies for action.

In decision management, DSS environments inspect outcomes days, weeks and months after decisions to see if (a) the decision was implemented/propagated and (b) if the effects of the decision are as expected.

What is required is to-

Pick the class of decision-making processes to focus on,
Narrow the range of inputs, the range of activities and the differences in models and methods,
Most importantly, to understand where technology ceases to play any meaningful role in decision-making, and where policy becomes the determinant of the quality and quantity of decisional effectiveness.

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

When Someone Finds Themselves In Debt, The Best Solution Is Debt Consolidation
When someone finds themselves in debt the best solution is debt consolidation. Consolidate all the debts and take a loan to pay them off then you will only have a loan to pay off and be rid of all the debts at once. This makes economic sense as the debts will have a higher interest rate than the loan. You will be changing many debts for one debt. This will make life very much easier for you.You will have to shop around for a suitable loan to pay off the debts. This will not be a problem as all banks and financial institutions give loans that will be suitable for this purpose. The ideal loan will be the personal loan. It will be a good idea to tell the lender what you intend using the money for and they will help you by giving you checks made out to your creditors instead of giving you the cash. This will eliminate any temptation to spend the money on anything else.Debt consolidation is usually the last resort people take when they cannot get out of debt. There is normally nowhere to turn if you are not earning any extra money. The only solution is to pay the debts off with a loan. It is so easy to fall prey to debt, but so difficult to get out of it again.You will have to find the best loan to pay off all your debts. The personal loan works well for this purpose. There is no control by banks and lenders what you have to do with the proceeds of this loan.If you are a home owner there are loans such as the home equity loan or you could take a second mortgage on your home if the amount owing was a very large amount of money. Both these loans are secured against the home so will probably be e

Database management system (DBMS):- An appropriate database management system must be able to work with both data that are internal to the organization and data that are external to it.

Database
Database management system
Data directory ( A database must contain data about the tables & all other objects)
Query facility

The User Interface (Dialog) Subsystem: - Dialog generation and management system is designed to satisfy knowledge representation, and control and interface requirements.

Typical information that a decision support application might gather and present would be:

Accessing all of your current information assets, including legacy and relational data sources, cubes, data warehouses, and data marts.
The consequences of different decision alternatives, given past experience in a context that is described.
Projected revenue figures based on new product sales assumptions.

The Knowledge Based (Management) Subsystem - A knowledge based system, is a computer program that contains some of the subject-specific knowledge of one or more human experts. The most common form of expert systems is a program made up of a set of rules that analyze information (usually supplied by the user of the system) about a specific class of problems. A related term is wizard. A wizard is an interactive computer program that helps a user solves a problem. Knowledge based systems are expert in specific “application domain”.

The aim of KBMS is to create, organize & make available important information knowledge in context of procedures, forecast. The key technology is data mining.Data Mining (DM) is the process of automatically searching large volumes of data for patterns using association rules.

These systems provide-

Provides expertise in solving complex unstructured and semi-structured problems Expertise provided by an expert system or other intelligent systemn Advanced DSS have a knowledge based (management) componentn Leads to intelligent DSSn Example: Data mining Types of DSS DSS can have narrow as well as broad sense. A narrow sense DSS is function oriented or industry specific DSS and on the other hand the most general purpose DSS are DSS generators. There are six categories based on based technology component-

Communication driven
Knowledge Driven
Model Driven
Document Driven
Data Driven

Communication driven: - Most communications-driven DSSs are targeted at internal teams, including partners. Its purpose are to help conduct a meeting, or for users to collaborate. The most common technology used to deploy the DSS is a web or client server. Examples: chats and instant messaging softwares, online collaboration and net-meeting systems.

Knowledge Driven: - Knowledge-driven DSSs or 'knowledge base' are they are known, are a catch-all category covering a broad range of systems covering users within the organization setting it up, but may also include others interacting with the organization - for example, consumers of a business. It is essentially used to provide management advice or to choose products/services. The typical deployment technology used to set up such systems could be client/server systems, the web, or software running on stand-alone PCs.

Model Driven: - Model-driven DSSs are complex systems that help analyze decisions or choose between different options. These are used by managers and staff members of a business, or people who interact with the organization, for a number of purposes depending on how the model is set up - scheduling, decision analyses etc. These DSSs can be deployed via software/hardware in stand-alone PCs, client/server systems, or the web.

Document Driven: - Document-driven DSSs are more common, targeted at a broad base of user groups. The purpose of such a DSS is to search web pages and find documents on a specific set of keywords or search terms. The usual technology used to set up such DSSs is via the web or a client/server system. Examples:

Data Driven: - Most data-driven DSSs are targeted at managers, staff and also product/service suppliers. It is used to query a database or data warehouse to seek specific answers for specific purposes. It is deployed via a main frame system, client/server link, or via the web. Examples: computer-based databases that have a query system to check (including the incorporation of data to add value to existing databases.

Conclusion and further work: The challenge for any organization considering DSS environments is the most complex. Organizations that deploy DSS technologies, but do not enforce decision-making policy, cannot expect to derive significant returned business value from their DSS environments, since the ultimate value of a decision is in its implementation and management: areas that DSS environments cannot, by definition, support.

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The easiest way to prove your credentials in any B2B sale situation is through referrals and references. Obviously, if you can have someone refer you to a colleague, a friend or even a competitor, you walk into that door about five steps ahead of anyone else.

Search engine optimization will help you get more traffic and sales to your site. Use these tools to help you optimize your site for free.

All of us have our own unique personalities, but some of us will be more dominate in one area over another. Sometimes we are a beautiful mixture of all four colors (red, blue, green and yellow) with each personality presenting itself in various situations.

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