Intro to Database Systems Chapter 1 Essay

According to Berson and Dubov (2011), there are four typical categories of drivers that explain the need for data management: Business Development, Sales and Marketing; Customer Service; Risk, Privacy, Compliance and Control; and Operational

* Describe the role of databases and database management systems in managing organizational data and information.

Data is ever increasing. We need a system to represent, store and manipulate complex information, detect correlations and patterns, construct data models etc. Furthermore, being independently maintained, data can change in time or even change its base structure, making it difficult for modelling systems to accommodate these changes. Current representation and storage systems are not very flexible in dealing with structural changes and also they are not powered with the ability of performing complex data manipulations of the sort mentioned above.

Gathering of values and variables which are related in some sense and differing in other sense is called as “DATA”. In recent days it is observed that size of data has been increasing. The quantity of data that is increasing for very two days is equal to the amount of data that has been produced until 2003. The year 2007 was the first year in which we were unable to store the data that we produced. This increase in size of data is proportional to the increase in the size of database. This lead to a

Dataset is a collection of information or data. More often dataset refer to the corresponding to single table of database in which every row represents a given member of dataset and every column corresponds to a specific variable. List values of the datasets for each variable is a member of data present in the datasets and each of its value is called as datum. Datasets may contain data for one or more than one members that is interrelated to the number of rows in the table. Datasets can contain more than one table that is related to one database in the database system.

Data is defined as useful raw material which is intended to be useful for both the originator and for the intended receiver. Data consists largely of facts and figures ideal for communicating the intended meaning. This data can be interpreted and can be categorised as follows;

The data structure represents the logical relationships between data elements. In addition the data also determines the organizational structure, access methods, and alternative processing assosiativitas level for information.

Relational data is when you can put data in a computer one time and it grows

Data management is vital to any business as this is a key tool to an organisations business improvement, as you can refer back to data, and compare them against benchmarks. Analysing data can provide evidence for possible future structure such as identify trends, as well as indicate where improvements can be made. However there are strict procedures to be followed when collecting and storing data.

Data comprises of factual information. Data are the facts from which information is derived. Data is not necessarily informative on its own but needs to be structured, interpreted, analysed and contextualised. Once data undergoes this process, it transforms in to information. Information should be accessible and understood by the reader without needing to be interpreted or manipulated in any way.

Example 1 – Consider the following relational database for the Super Baseball League. It keeps track of teams in the league, coaches and players on the teams, work experience of the coaches, bats belonging to each team, and which players have played on which teams. Note the following facts about this environment:

The databases are required to be accessed very properly; the broken or fragmented data needs to be recovered. For querying and reporting purposes the data should be easily accessible

Databases allow us to easily store and retrieve data in a purely digital format. The strength of this is that large amounts of data can be stored and retrieved with minimal effort on the part of the user. Opposed to manually flipping through files, one can quickly pull up the requested data through a computer program. Many systems that were conventionally paper and file based have been converted to a digital format which are now stored in one or more databases.

Data independence is the property that lets you change the structure of a database without requiring you to change the programs that access the database. With data independence, you easily can change the structure of the database when the need arises.

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.