The Value of Data and the Use of Databases

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Use of systems & Data _                                                                                       James Leong Mook Seng

The Value of Data and the Use of Databases

Data is valuable for a number of reasons:

  • It takes time to compile.
  • It takes time to input the data into the computer.
  • Its historical value
  • It can be analysed, accurate, and up-to-date.

Data can be very valuable to an organisation providing it can be clearly analysed.  An example of the value of data is the use of stock control systems.  As the data about stock can be updated each time a stock item is sold, the stock situation is always up-to-date.  This means that, as soon as the amount in stock falls below a reorder level, an order can be placed.  Indeed, many systems trigger the reordering automatically as soon as the number in stock falls below its reorder level.  This is often done by the system sending the order to the supplier using electronic data interchange (EDI).  

This automatic stock reordering has two cost effects.  First it means that the organisation should rarely run out of stock which causes a loss of sales and, hence, loss of income.  It also means that the organisation should not need to store large quantities of stock which leads to high inventory costs.

If the organisation also keeps data showing the rates of sales of products, the system can recognise changes in these rates and so change its ordering patterns.

Thus, data about products in stock and rates of sales is valuable as they improve the profitability of the organisation.

In order for data to be of value they must be accurate and up-to-date.  Often data are inaccurate due to them not being frequently updated.  If the sales figures are only used once a week to update the stock database, the stock levels are soon out of date and the data have little value.

These days banks offer services other than banking.  They offer mortgages, insurance and business support.  If a bank is considering a loan, it is important that the bank is aware of the risks involved.  Keeping data about previous borrowers, such as age, income and social background, and comparing the data for a potential new borrower with the historical data can help to determine whether or not to make the loan.  This is often done using artificial intelligence (AI) techniques and leads to fewer people reneging on their loan.  Thus, the data used is very valuable to the bank.

Another example is of an international company that has run two advertising campaigns in two different countries.  The one was much more successful than the other.  It is important that the company keeps data about the two campaigns in order to determine why the one campaign was more successful than the other.  This will lead to better sales campaigns in the future, improving the profitability of the company.

A company can lose its data for the following reasons:

  • Hardware / Software failure
  • Attack by a virus or hacker
  • Theft of data
  • Accidental misplacing of data
  • Theft of the equipment that data is on
  • Sabotage by an employee

Hardware which could be used for back-up purposes:

  • Floppy disks
  • Zip disks
  • CDROM
  • CD-RW
  • Creating a mirror hard drive
  • Backing up to Internet Storage

EDI (Electronic Data Interchange) is the electronic transmission of business data such as purchase orders and invoices from one firm’s computerised information to that of another firm. EDI was developed to provide an interface between two separate computer systems. Each company could have its own way of doing things, but by using EDI, they could now ‘talk’ to each other without one company having to re-enter data or redesign its system to match the other company’s.

A company who wants to use EDI with another company does the following:

  • They form an EDI trading agreement with that company: they need to agree which EDI protocols they will use
  • Once this has been agreed, both companies will write programs that convert documents that they want to send and receive into the agreed EDI format

Benefits of EDI

  • Savings in labor costs (through the elimination of data entry, paper document handling, reconciliation and other manually performed tasks).
  • Elimination of mailing costs.
  • Reduction of document management costs (on site and off site storage).
  • Reduction in data entry error rates.
  • Elimination of communication lag time between agency and customer.
  • Improved customer service.
  • Expendability of the system to other functions (using the same translation software for various applications such as procurement, collections, payments, etc.).

Value Added Networks (VANS)

As EDI became more widespread, enhanced communication links between companies were offered by companies. VANS simplify the exchange of data between users of the service by using computer networks.

In these systems, users plug into the interface provided by the VANS operating company and the software does everything else.  A VANS may operate in a single company or may be of use to several companies.  For example, estate agents may share a VANS in order to match potential buyers with sellers over a much wider area than is possible if each estate agent only has access to their own data.  

VANS provide services such as:

  • Allow different  EDI protocols to be used by different companies
  • Allow companies to store data within the VANS so they could more easily be accessed from outside the company, for example, by other organisations.
  • Provide the technical know-how for companies
  • Provide a vehicle by which companies could set up an EDI trading agreement.

One of the problems with so much data being available is trying to sift the data for useful information.  This is often achieved using data mining techniques.  A lot of work is going on to develop sophisticated datamining software which looks for patterns in vast quantities of data.

The ability to sift through data to find patterns such as

  • finding people who are most likely to respond to 'junk mail',
  • which products (such as bread and milk) are most often sold together in a supermarket,
  • which people are likely to live longest,

can lead to much better targeting of customers with the result that there are better returns on investments.

Data Warehousing

A data warehouse is a central store of data that has been extracted from operational data. Data in a data warehouse is typically subject-oriented, non-volatile, and of a historic nature, as contrasted with data used in an on-line transaction processing system. Data in data warehouses are often used in data mining and on-line analytical processing tools.

The idea behind data warehouse is that

  • Historical data mainly from past transactions that the company has carried out, are separated out from the business
  • The data is re-organised in such a way as to allow it to be analysed
  • The newly structured data is then queried
  • The results of the query are reported

Data warehousing could be used as a predictive tool, to indicate what should be done in the future. However, the main use of data warehousing is not as a predictive tool but as a review tool, to monitor the effects of previous operational decisions made in the course of a business.

For example, if Marks and Spencers decided to open stores in Asia, data could be collected as the stores opened and over the first few months. This could then be passed to a data warehouse. The wisdom of opening stores in Asia for the business as a whole could then be reviewed and conclusions backed up with statistical evidence.

Data Mining

Data mining and knowledge discovery in databases are often used synonymously.  Data mining is the term applied to the software technique that looks at a huge set of data and tries to find hidden trends in it. Data can be extracted in such a way that they can be put to use in areas such as decision support, prediction, forecasting, and estimation. The data is often voluminous but, as it stands, of low value as no direct use can be made of it; it is the hidden information in the data that is useful.

Data mining can be used to answer such questions as “who is most likely to buy a book at Christmas” and “why are they more likely to buy a book at Christmas”. The most important thing about the role of data mining is that it is predictive. It seeks to answer questions about the future. Data mining techniques are used in mathematics, cybernetics, and genetics.

Data mining and data warehousing has become possible for the following reasons:

  • Sophisticated software is now available
  • Vast data storage is possible
  • Vast processing power is available, for example using parallel processing
  • The price of sophisticated hardware has fallen dramatically

Standardisation

Standards are documented agreements containing technical specifications or other precise criteria to be used consistently as rules, guidelines, or definitions of characteristics, to ensure that materials, products, processes and services are fit for their purpose.

For example, the format of the credit cards, phone cards, and "smart" cards that have become commonplace is derived from an ISO International Standard. Adhering to the standard, which defines such features as an optimal thickness (0,76 mm), means that the cards can be used worldwide.

International Standards thus contribute to making life simpler, and to increasing the reliability and effectiveness of the goods and services we use

Without standards there would be a proliferation of formats and it would not be possible to move data electronically.  Not only must file formats be standardised but also communication methods.  For example, if two computers need to communicate, it is essential that both are sending and receiving data in the same format.  It is useless if one computer sends in one format and the other is expecting the data in a different forma.  As communications are world-wide and there are a multitude of computer manufacturers, it is essential that standards are set for consistency.

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In order to be able to share data successfully some form of standardisation is needed so that users can send, receive and interpret the data correctly. Some typical standards used for files are given below.

  • Text files  These are used to hold characters represented by the ASCII code.  Text files are used to transfer data between application packages.  The data consists of individual characters and there is no formatting applied to the characters.

  • Comma Separated Variable files  are used to transfer tabular data between applications.  Each field is separated by a comma.
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