Will You Add? - Business

International Trade Impact
International trade has become increasingly important to the world economy as well as the U.S. economy. Trade accounts for about 25 percent of U.S. and world gross domestic product (GDP). It is growing at twice the rate of any other economic sector. In terms of the United States, one-third of the small firms that make an exportable product and would like to export do not presently export what they manufacture. Of the small U.S. firms that do export, nearly two-thirds export to only one country.The international flows of goods and capital that underlie international finance are critically important to the well-being of the world's nations. United Nations statistics show that the ratio of world exports to total gross domestic product has consistently increased since 1970. Much of this growth in world trade can be attributed to the liberalization of trade and investment because of reductions in tariffs, quotas, currency controls, and other restrictions on the flow of international payments. In addition, the advances in communications and transportation facilities and their concomitant reductions in cost have also facilitated the

ip #3. Access to data means power, and talking about power is one of the greatest management taboos, still around. Sensitive as they are, even budgets are more readily discussed...

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

In Data Warehousing, it is not about hardware, and not about software: it is about the perfect integration of these two. Those who begin their project from either end, will pay dearly for this mistake. Reasons are:

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking

Bread For The Head
Whistleblowing as we know it is not a development of the late 20th century. The council of the city-state of Venice instituted a form of whistleblowing to help fight corruption and to give citizens a more meaningful voice in their government.Employees or franchisees do come across acts of dishonesty, fraud, corruption, theft, and transactions in prohibited goods, violence, and damage to property or plain unethical behaviour. If such activity is reported, undesirable repercussions can be avoided.Illegal, Immoral or illegitimate practices ranging from under-reported sales to misappropriation or pilferage of stock or non-compliance can undermine an organisation and, in severe cases, severally erode its brand and reputation in the marketplace. SMEs are particularly vulnerable as they are less likely to be audited or to employ measures to detect and avoid such dishonest actions.In many cases, if classified information is available and whistleblowers protection guaranteed, financial losses might be lower – at least corrective action can be taken more swiftly. Fraudulent activity is more likely to be detected by a tip

Data Warehousing was an innovation from the 90's that promised to change the data landscape for good. How far have we come? Many vendors have entered the marketplace because it makes sense to bring together data from throughout the organization, and this will continue to make sense in the future.

How large the Data Warehouse market will grow nobody knows yet. But for sure it is still growing fast, and currently is estimated at 4,5 billion dollar per year (IDC).

1. Why Do Data Warehouse Projects Run Into Scope Creep?

To quote Bill Inmon (guru and author of several great books on Data Warehousing) "Traditional projects start with requirements and end with data. Data Warehousing projects start with data and end with requirements." As soon as the project gets under way, users will find new applications, and with it will come new requests for data. Interestingly, these projects often are justified by moving Q&R work away from the 'data people'. What we've seen is that the first thing that happens as soon as the project delivers is that more requests for special queries are submitted to these same 'data people'. This may appear to undermine the initial business case but actually signals the onset of value creation from the DWH project.

2. Star Schema Versus Entity Relation Model?

There has been enormous debate in the community about the merits of different data models. At the risk of over simplifying: ER models tend to have better performance (processing time) for the end user, and are often perceived as "easier" to understand by end users. Drawbacks are that ER models require more disk space, and, because of the intrinsic redundancy in the data, have consistency problems from a maintenance perspective. Having said this, the practice seems to be that often some combination of the two is unavoidable in the practical setting, despite preferences (ER or Star) of the chief architects. Overall, Star models seem to have gained the most ground.

3. The Importance of a Data Warehouse Business Case

Much has been written about the business case for a Data Warehouse. What goes in to a good business case? IT savings are ubiquitous in DWH business cases. The important point is to not limit this to 'pure' savings, but to connect to primary business processes as much as possible. As an example, faster turnaround cycles for list selections are fine (when quantified in hourly rates), but it is even better if the revenue from more customer acquisitions that follow from these selections can be tied in. Not only will the relation to revenue growth rather than savings make for a more balanced business case, more important is the intrinsic business buy-in that results from a direct connection to the company bottom line. These days, changes in legislation (in particular Sarbanes-Oxley) play a major role in justifying business cases. This may be either through a higher company valuation for its transparent information gathering, or, less sleepless night for the CEO, which is of course priceless...

4. Why Do Data Warehouse Projects 'Never' Go Wrong?

Actually, Data Warehouse projects do sometimes fail. But, they fail so rarely, that it is actually very hard to believe... Especially after having talked to so many disgruntled end-users. And there are many ways a Data Warehouse project can go wrong. Delivering on time, data administration issues, and unavoidable data quality issues in feeding systems. Corporate politics (see Tip 7) are probably the best explanation for this phenomenon of near 100% success rates on DWH projects. In my experience, the reason why a failure or 'semi-failure' can go unnoticed is either because senior management is not aware, or, let's say "unmotivated" to talk about misspending of company funds. As a result, not enough is learned. Maybe we as consultants have a stake in this as well, as this assures the industry plenty of ongoing business... J

5. What is Different About Warehousing Web Data?

Kimball & Merz (2000): "Although this clickstream data in many cases is raw and unvarnished, it has the potential of providing unprecedented detail about every gesture made by every human being using the Web medium". The subatomic nature of clickstream data poses unique challenges. There are fewer built in feedback mechanisms to ensure data quality, compared to other data streams. The relation between user mouse clicks and server log records is not as tight as in "traditional" transaction processing due to technical issues like proxy servers and caching. Because of these differences, IT people need to adapt to the web process flow, rather than having the process adapt to IT needs as is common for most other DWH interfaces.

6. Which Data Should Be loaded In The Data Warehouse?

The data that enter the DWH ultimately determine its place in the organization. A "let's load all data, to be safe"-attitude is a sure fire way to derail your DWH project. Choices as to what should and should not be included need to be made early on, to keep the project manageable. After proven success of the delivered, deployed, and profitably exploited DWH, there always will be funding somewhere to include previously ignored interfaces. Given the anticipated lifecycle of the DWH, it makes perfect sense to consciously exclude certain sources. The choice as to what data to include needs to be driven by business considerations, and in particular reference to the company bottom line. If it can't be shown how data will be put to use profitably, they stay out! See also tip #3.

7. Data Warehousing & Company Politics

Data Warehouses have an impact on the company bottom line. Hence, they are likely candidates for turf battles, and are also at risk of becoming "small change" in budget allocation negotiations. None of these considerations benefit corporate long term goals. Managing a DWH project is hard enough as it is, and budget issues shouldn't make it any harder than it already is. Because DWH investments are in the present and revenues lie in the future, it is even more important to secure funding through a sound business case and buy-in from the appropriate (high) management level. See also Tip #3. Access to data means power, and talking about power is one of the greatest management taboos, still around. Sensitive as they are, even budgets are more readily discussed...

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking

How To Gear Up Your Network
The art of Networking is a key ability for any type of entrepreneur. Networking can bring you important information as well as give others important information about you. As an aspiring or current business owner, networking should be an area of interest of prime importance to you and the future of you business. For those of us working via the internet only, the concept of networking becomes at the same time daunting and almost hilariously easy. Just point and click. You can even get software to help you contact people you want to network with. Personally I like to do most things manually, to get a feel for the project at hand.If you don’t understand why networking is so important to business survival, then I suggest you do some research. You will be amazed at the potential inherent in the simple act of getting to know someone, in your line of business or not. For the Internet Marketer, networking is a matter of survival. You either do it or your business will die. It’s that simple. This article will focus on some of the ways to gear up your network to keep it ever changing and expanding. Networking never stops and

er" to understand by end users. Drawbacks are that ER models require more disk space, and, because of the intrinsic redundancy in the data, have consistency problems from a maintenance perspective. Having said this, the practice seems to be that often some combination of the two is unavoidable in the practical setting, despite preferences (ER or Star) of the chief architects. Overall, Star models seem to have gained the most ground.

3. The Importance of a Data Warehouse Business Case

4. Why Do Data Warehouse Projects 'Never' Go Wrong?

5. What is Different About Warehousing Web Data?

6. Which Data Should Be loaded In The Data Warehouse?

7. Data Warehousing & Company Politics

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking

For Anyone Wanting To Start Their Own Home Buisness
For those of you who have always wanted to try the making money online thing, but have thought it would be too hard or didn’t know where to start.I am new to the internet and was looking to make money at home on the computer; at first I tried the paid survey thing while it did bring in some cash. It also bought a lot of junk mail and to get the best paid surveys you had to pay to signup.” Well that was a waste of time.My mail box was filling fast with heaps more junk, and every survey I was invited to participate in, I would get “you don’t qualify for this survey”.Then in one of the Emails I found a lead to a website that was fully stocked and setup. I thought this doesn’t look real bad, after all I had nothing to lose and everything to gain.I bookmarked the page and returned to the page a few times but pushing the signup button didn’t come till about a week later when I signed up.• You choose my own domain name.• Build YOUR brand, your identity, including full meta tags, store name & more.• Over 90 categories or niches pre-made and Ready to Profit immediately.• Your admin pan

5. What is Different About Warehousing Web Data?

6. Which Data Should Be loaded In The Data Warehouse?

7. Data Warehousing & Company Politics

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking

Medical Billing - GU0 Record Fields 59 Through 61
In this segment on medical billing, believe it or not, we're over 80% through our review of the GU0 record, or CMN. This is the longest CMN for electronic billing using NSF 3.01 specifications. In this installment we'll be picking up our review of the GU0 record with field number 59.GU0 field 59, position 263, is Reply NUM L01 N01. This field refers back to the first question on any DMERC certification requiring a one position numeric response. The key here is the word numeric, as up until now, all the other responses were alpha or character responses, meaning they could be either numbers letters or spaces. The following forms are supported by this field. For form 01, the following responses are valid. A 1 for stage one, a 2 for stage 2, a 3 for stage 3, a 4 for stage four, or a 9 to designate that there was no ulcer or pressure area.For form 08, the following responses are valid. A 1 for heart, a 2 for liver, a 3 for kidney, a 4 for bone marrow, or a 5 for lung. This is to designate the type of transplant. This field cannot be left blank if a transplant was done.For form 09, the following responses are

process adapt to IT needs as is common for most other DWH interfaces.

6. Which Data Should Be loaded In The Data Warehouse?

7. Data Warehousing & Company Politics

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking

Top 3 Reasons For Writing Business Plans
Whether you are a start up or established business, and whether you are a non-profit organization, writing a business plan can be one of the most useful things you can do for your business. Obviously there are different types of business plans depending on the nature of your company or organization. It's not enough that you have a "hunch" your new start up will be a roaring success, or you believe your latest web. 2.0 idea a surefire "ten bagger" success for the lucky venture capitalist. There are people who need to take a close look at your business plan; whether it's you, internal management or external investors. In this article, we will look at the top three reasons for writing business plans.First to answer the question: "Is the business feasible?"Before you actually commit funds, manpower and time on starting a business, it helps to actually have a "dry run" to see if the venture you have in mind has a good chance of success. The business planning process forces you to look at what your competitors are doing and to ask yourself how you can differentiate your product or service. Typically we call this a SWOT analys

ip #3. Access to data means power, and talking about power is one of the greatest management taboos, still around. Sensitive as they are, even budgets are more readily discussed...

8. Data Warehouse Projects Traps

Some commonly recurring 'roadblocks' on the path to timely delivery of a Data Warehouse project:

ETL processes have eaten up so much time (and still need "babysitters"), that little if any time is left to develop applications needed to exploit the DWH
Some data are needed, but turn out not to be unavailable, or not in a timely fashion
Maintenance required for tuning, indexing, and backup and recovery is severely underestimated
Different ways of calculating the same phenomenon lead to different results, and nobody is able to conclusively explain the difference(s)
The data that is loaded (and recombined) turn out to contain previously unknown inconsistencies in the source systems, the 'classic' data quality issues that trip DWH projects
Metadata were lacking, and developers spend inordinate amounts of time finding out what a field really 'means'

9. DWH Hardware and Software Go Hand in Hand

· in terms of price/performance, new, pre-integrated hardware-software combinations are taking the lead

· from a project management perspective, you never want to be caught between vendors when a proposed solution doesn't work as expected

· database tuning and indexing is very important and a hugely complex job, necessarily left to specialists (in-house trained)

10. Performance is Key

Although I don't often find technology factors to be this important, in Data Warehouse acceptance, no other factor will be as important as performance. As size increases over time, this factor becomes even more important. There are three reasons for this:

performance has a huge impact on the development speed (initial load is always very time consuming), and hence the overall maturity of the DWH at delivery time
performance can make or break end-user acceptance, in particular the predictability of performance
performance has a tremendous impact on end user productivity, the ultimate driver of the business pay-off

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This methodology allows you to define in a quantifiable manner the compliance tasks involved in your company. All of the companies which use a type of Sarbanes Oxley software have the same financial data collection and their reporting needs are not really one and the same...

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