Database Administration

views updated Jun 27 2018

Database Administration

Database administration is simply maintaining records of any typecustomer lists, vendor histories, or addresses, for exampleusing computer software known as a database management system (DBMS). As Anne Kerven said in Colorado Business Magazine, "Database management means the transferring of file cabinet contents to an electronic file." Out of that simple statement has sprung a multimillion dollar computer software industry and a thriving database administration consulting niche. Almost every company has records of one type or another to maintain, which means that almost every company is affected by DBMS in some way or another.

Databases can range in size from a few hundred addresses maintained on a user's hard drive to hundreds of terabytes of data maintained on huge corporate mainframe computers. One of the benefits of using a database management system, however, is that even if the data is vast and is stored on a remote mainframe, end-users throughout a company can all access the data from their desktop using computer networking technology. Reports that in the past had to be requested days or even weeks in advance and created by computer technicians can be generated in minutes by the average user with today's database management systems.

The most common type of system is the relational database management system (RDBMS). It is found in almost every company data center. An RDBMS sorts data into unique fields and allows users to retrieve that data by each field and by linking fields between related records. Relational databases can sort the fielded data any number of ways and generate reports in a matter of minutes. Data can often be output in any form the end-user desires. In addition, a RDBMS can serve as the front-end program that brings data together from several individual databases and produces data tables that combine the information from the various databases.

Database management technology is improving every year, however, and relational databases are starting to be replaced by more sophisticated database management systems. This movement was spurred in large part by companies that realized that they had more than simple records to maintainthey had complicated files, with sounds and images; they had brochures, photographs, time-series inputs, and 3-D coordinatesall of which could be more easily maintained if they were organized and stored in a database. In response to this growing need, software developers have created new object-oriented database management systems (OODBMS) and object-relational database management systems (ORDBMS).

It is expected that ORDBMS will become the most popular type because the need to store disparate types of information is growing. An example of the type of data that might be stored in an object-relation system is a human resources file on an employee. In the past, the database record might have only included text information about the employeebirth date, address, starting date, etc. With an object-relational system, the record could also include the employee's photo or voice sample. Or, a company could maintain geospatial information that would allow it to query the database to locate all customers who made more than $50,000 and lived within 10 miles of the company's location.


For small business owners who are entertaining thoughts about purchasing a database management system, experts say that the first thing they need to do is determine what they hope to get out of the systemwhat type of reports do they need, etc. Once the output is known, it is easier to know what type of database is needed, what information will be gathered, and what fields will be created. It is a good idea to start smallsuch as with a mailing listto get used to the software. Once the first database is mastered, it is easy to set up additional ones for order tracking, inventory, or other purposes.

Most databases are one of two typestransactional or warehouse. Transactional databases are easier to build and are ideal for tracking simple things, such as the availability of a product or part. Warehouse databases collect company data of any type, such as sales histories or hiring statistics, and produce reports that can identify trends or group information in new and relevant ways. Small businesses use both types of databases.

Once you know what you hope to get out of a system and what type of database you will be building, you can move on to selecting the right software for the job. If you are a computer savvy user who is experienced with personal computers, and the database is simple, then you may be able to study the available software packages yourself and choose the one that is best for you. If you are not, or you expect the job to be complex, it is best to locate a consultant in your area and work with them to select your system.

The simpler the system you can get away with, the better. "If you can buy off-the-shelf, that's fantastic because it's less expensive," said Larry Skaff, owner of Junction Software Services, in Colorado Business Magazine. "But it will have tradeoffs. If they don't do business exactly the way that database is written, can they live with that?" The most common off-the-shelf system is Microsoft Access, which is sold separately and as part of Microsoft Office and Microsoft Small Office. Access allows users to build databases out of a number of templates so that they do not have to start from scratch. At the same time, it does allow advanced users to build custom databases, and it features fairly powerful sort and reporting options.

More adventurous users may opt for packages that are a notch or two above Access, such as Filemaker Pro, Borland's Paradox, or Microsoft's SQL Server. These are more robust than Access and allow users to define fields and create intricate databases. If you do not feel comfortable creating a database yourself but still need the additional features that these higher-level packages provide, then a consultant is once again the place to turn. Most will charge anywhere from $50 to $250 per hour to create a custom database. Be warnedthis can be a time-consuming project and can cost tens of thousands of dollars.

For small businesses that have even more extensive database needs, consultants and computer professionals will undoubtedly be required. High-level products from one of the big three database management systems companiesOracle, Informix, or Sybasecan manage huge amounts of complex data on either a stand-alone machine or a local- or wide-area network.


There is one important fact about databases that some people seem to forgetno matter how good the software is, no matter how expensive the computers are, they are only as good as the data that is put into them. Information must be loaded into the system via data entry work or some other form of input, and it is up to the business owner or manager of information systems to make sure that records are accurate and kept up to date.

Letting records slip from time to time may seem like a small thing, but especially for a small business enterprises, poor database maintenance can reflect poorly on the business and make clients think twice about doing business there. Database managers estimate that more than half of small businesses do not maintain their databases once they are created. Examples of the kinds of mistakes that can occur include failing to bill an account, mailing literature to someone who is deceased, or indicating that there is plenty of a particular product in stock when in fact the supply was exhausted weeks ago. Such situations can give rise to business disasters for owners of small businesses.

Writing in Colorado Business Magazine, Anne Kerven outlined some of the other common maintenance mistakes that are made:

  • Collecting too much or too little data. Collecting too much information slows down the system, clutters screens with unnecessary fields, and inflates the costs of gathering data. Recording too little data can render the database worthless for compiling reports that can help the business grow; instead, money spent on inputting the little data that is there is wasted.
  • Poorly conceived data fields. The most common mistake is putting too much information in one fieldthe computer can only sort by field, not by what is in the field. The best rule of thumb is to put each unique record elementZIP code, phone number, fax number, addressin its own searchable field.
  • Try to avoid using personal names as the key identifier of a record or as a link between records. Instead, use numbers, assigning a unique number to each record. Personal names cause problems when two or more people have the same name; additionally, if the name is not entered exactly the same way every time it is used as a linka middle initial is included in one instance and left out in another, for examplethe records will not link properly.
  • Check the database integrity at least once a month. Corrupted links or other problems can creep in over time. Utility programs are available for this function.
  • Back up information and store it in a separate location, preferably someplace that is fireproof and waterproof.
  • Set strict standards that must be followed whenever data is input into the system to ensure consistency. This is especially important if multiple departments will be adding data to the system.
  • Periodically clean out the database, weeding out records that are inactive or no longer relevant. If you do not want to lose those records permanently, create an archive database and move the records into that file.


As discussed, database management systems store company information and allow users to easily retrieve that information. But what does that mean in the business world? How exactly are database management systems being put to use so that companies get the most bang for their buck? Currently, there are two primary uses that are gaining in popularitydata marts and data warehouses, and the use of DBMS together with a company's Internet site or intranet.

Data Marts and Data Warehouses

Data marts and data warehouses refer to the information repositories that companies create with their database management software. Data marts are simply smaller versions of data warehouses, storing information on a department-by-department basis. Data warehouses are huge, centralized databases that unify information across an entire company. These huge databases can be used to improve customer service, profitability measurement, and product sales.

Data marts gained popularity before data warehouses. They were seen as a way for departments to achieve one of their main goalsgetting information into the hands of all their users quickly and at the same time. However, as DBMS technology improves and larger databases become possible, the flaws in using data marts are being exposed. Data marts do not unify data across an organizationin fact, they can fragment it because every department might be doing things a little differently. Each department's data becomes an island that yields different answers to the same query.

That is not to say that data marts cannot work, however. They can, if they are built after a main data warehouse is built. Most people think it is better to start small with data marts and build up to the big data warehouse, but many experts contend that the opposite is true. If the data marts are built first, then fragmented data held in uniquely structured databases that cannot be accessed by all employees are created.

Instead, small business owners should build the warehouse first. Look at the types of information that are gathered in each department around the company and select the key data from each area. Use this as the starting point for the warehouse. Do not try to build an all-purpose warehouse right from the start. Do what makes sense, then add historical data and other information as time goes by. If information is simply gathered and stored with no allowance made for cross-departmental analysis, then the warehouse is useless. Those considering building a database should understand that if, upon examination, the current processes a company uses do not allow for such cross-departmental analysis, then fundamental changes will have to be made to those processes if the warehouse is to work. This is a significant point that too many managers or business owners do not understand when they decide to build a warehouse.

Small businesses also have to make sure that end-users from every department are actively involved in the design of the data warehouse. Without that type of feedback, the database may turn out to be useless because it does not store the right type of information, or it stores it in the wrong way. Those end-users involved in the design can learn how to use the system first and then serve as trainers in their department. Once the main warehouse is built, it then becomes easy for each department to build its own data marts by pulling out the fields from the main database that it needs.

The initial costs of building a data warehouse are highsoftware, hardware, and consulting fees add up quickly. However, most businesses, from supermarkets to banks, are finding that having a data warehouse is a competitive necessity. One example of how data warehouses are being used is a practice called "data mining." Data mining is the technique of creating statistical and predictive models of the real world based on patterns that are discovered as a result of complex queries performed on the huge amounts of data stored in a warehouse. When data mining is done right, it can produce amazing results, spotting trends before they happen or identifying new sales prospects, for instance. When done incorrectly, however, data mining can produce false correlations and misleading results. Companies should not rely too heavily on data mining and should ensure that they hire professionals who fully understand statistical analysis to perform the task.


Data warehouses started out as internal projects, but now they are being seen as the next logical step on the Internet. Companies that need to gather data from customers and pass information down the line to business customers are finding it beneficial to make their data warehouse available over the World Wide Web. This means that either HTML or Java-based client servers need to be created to allow Web users to search the database. If the company desires to gather information on customers, it might make the warehouse available to the public over the Web. If the main purpose is to pass information on to business customers, then the company will make the warehouse available as part of its corporate intranet, which is available only to selected individuals.

At first, only basic queries could be run easily over the Web, but observers note that the situation has changed rapidly. Each of the major database management systems companies has scrambled to enable their databases to work closely with Web servers. Using new technology known as online analytical processing (OLAP), high-level, intricate queries of data warehouses will be possible. At the same time, consumers looking to data mine corporate information should be able to run simple queries.

There are risks associated with making such huge amounts of data available over the Web. Security is the paramount issue, since opening data warehouses to users around the world means that internal systems are exposed to outside interference or hacking. A second issue is the drain on system resources that unlimited access to the data warehouses would cause. Popular databases visited and searched by large numbers of users would need extremely powerful servers to keep up with demand. The servers would have to ensure that the employees and clients of a company would not be hindered by the excess traffic on the system. Finally, there is the issue of cost. As with any new technology, opening databases to the Web costs money. In addition to development costs associated with creating the search engines and OLAP tools, businesses will also have to weigh the cost of the powerful servers needed to meet the increased demand for information.


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                                  Hillstrom, Northern Lights

                                   updated by Magee, ECDI

Database Management

views updated May 11 2018


Database management refers to the process of storing and manipulating the information housed in a database. Databases can be as simple as the electronic address books used by individuals to keep track of e-mail recipients or as complex as electronic library systems or online flight reservation systems. Typically, some sort of query system allows users to gain access to specific information in a database. For example, electronic library systems often are designed to accept queries such as "a = author name," "t = title," and "s = subject." Therefore, the query "title = War and Peace" would retrieve all database entries which contained "War and Peace" in the title field. The tools used to actually manage databases are grouped together into database management systems (DBMSs). Several types of DBMSs exist, including those designed for personal computers (PCs), as well as those running on large mainframe systems.


Although various rudimentary DBMSs had been in use prior to IBM Corp.'s release of Information Management System (IMS) in 1966, IMS was the first commercially available DBMS. IMS was considered a hierarchical database, in which standardized data records were organized within other standardized data records, creating a hierarchy of information about a single entry. In the late 1960s, firms like Honeywell Corp. and General Electric Corp. developed DBMSs based on a network data model, but the next major database management breakthrough came in 1970 when a research scientist at IBM first outlined his theory for relational databases. Six years later, IBM completed a prototype for a relational DBMS.

In 1977, computer programmers Larry Ellison and Robert Miner co-founded Oracle Systems Corp. Their combined experience designing specialized database programs for governmental organizations landed the partners a $50,000 contract from the Central Intelligence Agency (CIA) to develop a customized database program. While working on the CIA project, Ellison and Miner became interested in IBM's efforts to develop a relational database, which involved Structured Query Language (SQL). Recognizing that SQL would allow computer users to retrieve data from a variety of sources and sensing that SQL would become a database industry standard, Ellison and Miner began working on developing a program similar to the relational DBMS being developed by IBM. In 1978, Oracle released its own relational DBMS, the world's first relational database management system (RDBMS) using SQL. Oracle began shipping its RDBMS the following year, nearly two years before IBM shipped its first version of DB2, which would become a leading RDBMS competing with the database management applications of industry giants like Microsoft Corp. and Oracle. Relational databases eventually outpaced all other database types, mainly because they allowed for highly complex queries and could support various tools which enhanced their usefulness.

In 1983, Oracle developed the first portable RDBMS, which allowed firms to run their DBMS on various machines including mainframes, workstations, and personal computers. Soon thereafter, the firm also launched a distributed DBMS, based on SQL-Star software, which granted users the same kind of access to data stored on a network they would have if the data were housed in a single computer. By the end of the decade, Oracle had grown into the world's leading enterprise DBMS provider with more than $100 million in sales.

It wasn't long before DBMSs were developed for use on individual PCs. In 1993, Microsoft Corp. created an application called Access. The program competed with FileMaker Inc.'s FileMaker Pro, a database application initially designed for Macintosh machines.


As stated by Uche Ogbuji in a July 2001 study of various DBMSs, "The database community is one of the oldest in the computer world, and it is almost as famous as the application programming community for the diversity of its ideas and the sharpness of the debates between its gurus. Lately events have conspired to expose these concerns to a wider audience. For instance, the seemingly inexhaustible march of the Web revolution has exposed more and more developers to database issues because of the desire for ever more dynamic Web sites." In fact, the rise of the Internet prompted the development of many new database management system features. These were designed to enable clients to take advantage of Internet-based opportunities such as e-commerce, which emerged in the late 1990s.

Database management giants like Oracle had begun tailoring their products to the Internet in the mid-1990s. For example, the firm's Web-enabled Oracle Express Server 6.0, launched in 1996, offered online data analysis functionality on both the Internet and corporate intranets. Oracle began to restructure itself around its Internet operations in 1998 when it released Oracle 8i, a version of its flagship database management product that allowed firms to manage all of their database functions on the Web. Oracle continued to develop new Internet-based technology in 2000. In May, the firm launched its E-Business Suite, as well as the Oracle 9i DBMS, which included an application server allowing users to run e-commerce applications related to their databases. The new product also offered file and document management, e-mail, Web server, and message queuing features.

By then, both Microsoft and IBM had begun to pay more attention to the DBMS market, recognizing its importance to the increasingly Web-based information technology industry. Microsoft began discussing plans to upgrade its SQL Server to support extensible markup language (XML), the language used to create Web documents, in 1997. According to an October 2000 article in InformationWeek, "XML is one of the primary areas that all the major database vendors have scrambled to embrace. Why is XML so important? XML facilitates communications between systems that normally don't speak the same language. Because of its self-describing nature, XML provides a way to pass information between dissimilar systems with some level of confidence that it will be properly interpreted on the other end. Direct XML support in the database means there is no need for any other tool to translate data from an external provider into something that can be used immediately." As a result, XML support, which included the ability to store, manage, index and search XML documents, was seen as increasingly necessary for DBMSs. Microsoft also wanted to be able to back up, restore, and reproduce XML applications. However, several delays kept the firm from offering these features until the release of SQL Server 2000 in mid-2000, well after both Oracle and IBM had added XML support to their databases.

Despite its delayed release, the new product boosted the firm's database management sales by roughly 45 percent, allowing it to gain crucial market share points. Microsoft also revealed its intent to include scale clusteringwhich would offer the increased processing and storage capabilities needed for e-commerce applicationsin its 2001 release of SQL Server. During 2000, Microsoft increased its DBMS market share from 13.1 percent to 14.9 percent, while industry leader Oracle increased its share from 31.4 percent to 33.8 percent. Third place IBM gained less than one percent, growing its share from 29.9 percent to 30.1 percent.

IBM had upgraded its DB2 system in 1999 with features designed to facilitate e-business. Late in the year, the firm made the DB2 XML Extender, which added XML support to DB2, available for free to DB2 customers via a download. IBM shipped version 7.1 of DB2 in October of 2000. Designed to facilitate e-business operations, DB2 7.1 included a Net Search Extender tool, which offered high-speed Internet index searching and data warehousing capabilities. Early in 2001, IBM paid $1 billion for rival Informix Corp., which had begun adding XML support to its Internet Foundation DBMS in October of 1999. Along with bolstering IBM's database management offerings, gaining access to the 100,000 Informix clients also boosted IBM's market share. Many analysts predict that the rivalry between IBM, Oracle, and Microsoft will only intensify as each firm scrambles to added increased functionality to its line of DBMS products.


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SEE ALSO: Data Mining; Data Warehousing; Ellison, Lawrence J. (Larry); IBM Inc.; Information Management Systems; Microsoft Corp.; Oracle Corp.

database administration

views updated Jun 11 2018

database administration (DBA) See database administrator.