ArtsAutosBooksBusinessEducationEntertainmentFamilyFashionFoodGamesGenderHealthHolidaysHomeHubPagesPersonal FinancePetsPoliticsReligionSportsTechnologyTravel
  • »
  • Business and Employment»
  • Business Management & Leadership

Companies With Bad Data Bases

Updated on November 13, 2013

Can't Find it Anywhere!

Where's That Information?

Wouldn't it be helpful to know how old data is? Of course, so why not time-stamp the data. Or, how does data work when it's inconsistent, which version is correct? The solution is obvious, the data has to be reconciled so that only accurate data appears. And, what can be done when there's missing information or blank fields? Same answer, work has to be done to find the data and insert it.

If quality data were easy, everyone would have it. But it's not. This is why companies are turning to the best software providers, who can create a customized data system that will help the company succeed, catch inconsistencies and missing information, and, for instance, make it easy to insert the correct data.

Executives and business people everywhere, be they CEO's, sales managers, database coordinators, developers, or IT staff, are very aware that inaccurate data can be a deadly ingredient in a company's system.

Each company and each individual the business deals with has a unique character and background history of dealings with that company. To be able to see that instantly on a screen is called quality data. It's quality because it translates into profitability and success.

It can come about only by using a data quality software provider that will take the time to get to know a company before tailoring a system exactly to the preferences and requirements of that business.

Finding such a software provider is the first step in acquiring good data quality. An old, hierarchical corporation that wants things done their way and not the client's way probably is a mistake for most business owners who are seeking to improve their data quality. The task of fitting the right software into a company's operation is never a routine service, but takes individual attention.

What do you have to do to have the kind of quality data that's going to make everyone involved more successful? Data that's right on point, easily accessible, and constantly proves to be a vital ingredient in producing results, is the goal.

While easier said than done, the process will involve being honest about the tough problems facing your company, and then ensuring that the best possible data improvements are made to attack or solve each and every one of those problems.

The human factor is essential to success because without the cooperation of key people in the company, nothing can get done. Therefore, all issues facing those people, such as the heads of each department in the company, must be addressed in one way or another by the plan for newer, more effective data.

The human element does not end there either. Once a new data system is in place, people may resist change as representing just another task to learn in their already busy schedule. All training and education must be extremely friendly and helpful.

Cost is always a factor and never can be ignored. If a new data system's cost will not pay off in handsome rewards that are easily seen as immediately realizable, data quality may be put on the shelf for next year or the year after.

What user-friendly features characterize excellent data quality? Because searching can be tedious and even maddening, the search features for the improved data must be logical and extremely considerate of what normally would occur at work in your company. Search terms must match with what's used daily on the job. There's no room for irrelevant frills that will only make matters more difficult for the people involved in the business.

Value added must be only the value desired by your company that will use the data, and nothing more. Reading through verbiage can be difficult enough. That's why careful attention and a lot of thought have to be given to customize the perfect information that's important, and delete or marginalize everything else.

It comes down to doing things the your way and not the software company's way.

Good quality data not only leads to fast results, but also contains information that can help plan for the future, make financial projections, and be an excellent tool for the strategic policy decisions for the business going forward.

Excellent data is always accurate, up to date, and not only useful but essential. All of these criteria are from the standpoint of the company that uses the data. You want real proven results, such as customer satisfaction, cost savings, less time wasted due to mistakes, more sales, and faster answers to questions about product specifications. Quality data is what can produce such results.

Quality data is just as important in the field of scientific research. Decisions made based on statistical sampling, surveys, and testing, also depend on excellent data records and storage.

In the field of advertising, for example, quality data is extremely essential to judge the demographics of people receiving a message, and tabulate the number of clicks on a digital ad. Fresh data and new data are indispensable tools for the marketing sector.

Just about any business can achieve quality data. The essential feature of quality is to understand your needs, and fully comprehend the flow of data both within and out from the business. Key people have to be interviewed to learn how they use the data and what they'd like to see. Being patient and avoiding a rush to a hasty solution are necessary ingredients for success.

Technology will be only a tool that results from human interaction and caring enough to do a good job of improving data quality.

As for when's the right time to improve data quality, the reasonable answer would be any time prior to when a crisis occurs. It's not an overnight product that can be thrown together in a few hours. There's a lot of communication, testing, troubleshooting, and hard work involved, but the end product will be worth its weight in gold.

Oracle has special "Data Quality" guidelines to help businesses succeed through efficiency in their technology. The integrity and quality of data involves profiling and categorization. There are specific steps to follow, from inputting date through sequencing the process in a final package.

To improve a company's data, "best practices," similar to accounting or any other profession, have to be followed by the technology experts. Human errors in filling out forms, and later keypunching that erroneous data into the computer system, account for a lot of the bad data in business. With a model plan to follow, checking data can become more efficient.

Governing the operation of a company's computerized information banks takes planning, cooperation, and feedback from everyone concerned. It should not be marginalized. It is a job worth doing well.


What is "Data Integrity"?

Data integrity takes place when information is consistently accurate. Every company will have its own way defining what it needs by way of consistent and accurate information. When standards are not met, it is said that data integrity is lost and "corruption" of the data base has taken place.

Corruption involves the loss of accurate data from a system. If it is possible to "retrieve" the data, the information must then be double-checked to ensure that it is accurately replacing the preexisting data that was on file before the corruption took place.

Although unauthorized persons can gain access to a data base and cause corruption, this is not what's meant by the term "integrity." Instead, a special term is used to the protections in place to try to prevent this. It's called "data security."

The "physical" integrity of a database involves the storing and obtaining of that data through systems designed to protect against hazards such as illegal human intervention, extreme temperatures and corrosion.

But "logical" integrity is more to the point in most cases, because it pertains to the correctness of the data itself. In plain language, the data has to make sense to the everyday user.

Human error is common to both types of integrity. Usually, errors are made in recording the data, or in the process of retrieving it.

It is important to fix accurately a time limit on how long data must be retained within your system. All data that's put into the system must have a time limit specified.

There are extremely beneficial advantages to have a good database with integrity. It will result in a stable, reliable system that can make operations highly efficient. The maintenance of the database can be assigned to one key unit in the company. The data will be the same information that's accessed by all departments, because it's one, integrated database usable by all divisions of the company.

Time, money, and personnel are made into the best resources possible through data integrity. Substantial savings result from accurate records. Data storage is the file system of the Twenty-First Century.


    0 of 8192 characters used
    Post Comment