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Posted: February 17th, 2024
Data Analysis and Design: Approaches to File Processing Systems and Data Mining
Database Management Systems (DBMS)
1.1. Compare and contrast traditional file processing system with database environmentContents Table
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More control of data redundancy
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Improvement in responsiveness and accessibility
Analysing the different approaches to data design
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TASK-1
1.1.
Compare traditional file processing system with database environment:
In the very early days there was no database computers because computers were not as powerful as the ones we have today. In the early days, the powerful computers were mainly used for engineering and scientific calculations. They were slowly introduced in the business world mainly for business applications. computers should be able to manipulate, store as well as retrieve large data files, and that is the reason why computer file processing system were created for this purpose. Over time they have evolved, their basic purpose and structure have slightly changed.
Due to the more complex nature of business applications, the old traditional file processing had its flaws and limitations which has resulted in them being replaced by the database processing systems in most of the business applications nowadays
The old filing system are still used mainly
- for backing up database systems
- To understand limitations and faults that arise in the old system in order to avoid these problems when designing new databases.
There are numerous disadvantages of the old filing system which are listed below.
Duplication of data- Applications are independently developed in the old file processing system which could result in unplanned duplication of such data which results in loss of the integrity of the data because data format might be relatively inconsistent or the data might not agree. This could also lead to loss of metadata integrity.
Program data dependency- File descriptions are stored in each application program which accesses a particular file e.g. an invoicing system and the customers master file, which gives a full detailed description for both files, as a result if any changes have to be made to all programs that access these files and sometimes difficulties arise as it changes will not cover all programs that access file. Errors can also be made when making changes
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Limited data sharing- with the old filing processing approach users have limited opportunities in sharing data outside of their own applications as each application has its privately-owned files. It causes frustration when a requested report requires major effort in obtaining from numerous incompatible files from separate systems. It could also require that other different organisations own these other files making it difficult to obtain.
Long development times- the old filing system offers little opportunity for leverage for previous development efforts. The developer must create a new application from scratch designing the new files access logic for each new program created. The longevity of creating the new program are quite inconsistent with the fast-moving business environment.
Excessive program maintenance- All other factors combine to make it a difficult program to maintain for companies that rely on this filing system. a high rate percentage are allocated which leaves limited budget for creating new applications.
All the disadvantages listed are the limitations of databases if organisations do not apply the approach properly.
The advantages of the old filing system
There is no need for a highly skilled technician to handle the database and there is no external storage required on external platforms which are used to control and regulate data
Database Management Systems (DBMS):
In the early 1960’s an improvement was made upon the old filing system and thus, replaced with the Database Management System. This can be a small or very large database that holds lots of data.
This approach bases its emphasis on the integration and sharing of data throughout the organisation. This requires a fundamental orientation or change in thought processes which should start from top management
The DBMS eradicated the problem of manually seeking data. A solid structure was put in place to make it much easier to locate and retrieve data from relevant databases instead of going through repetitive files that are created on the old filing system. A more logical view of imputing data.
A database is a collection of information which is arranged in order for it to be accessed when required by a user. Data can be in various forms numeric, images, text and more. Which are stored in tables. The basic idea of DBMS is for data to be extracted in a fast-reliable way when it is required for use.
DBMS creates a relationship with its high-level entities of the company its association within these entities.
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Example:
- Customers
- Order
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Customers are required to order products from a border line and thus, a relationship is formed. In DBMS, it is required that entity relationship (ER) diagrams are used as they are used to show relationships of how the database would be modelled.
Diagram of a DBMS
The DBMS approach can offer much better advantages compared to the old filing system, only few can realise if the company implements many databases standing alone, if this is done it would be like the old filing system which would demonstrate the old filing system’s disadvantages.
The advantages are as following:
Improves decision making:
This Improves decision making and intracompany communications by installing a web based internet which is only accessible with the company or organisation. Employee’s workstation can be used in accessing information swiftly e.g. Phone directories, electronic mail and various other information. Workstation can be used to access various databases through the internet
More control of data redundancy:
Redundancies are not completely removed from the DBMS approach but it can control redundancies in the actual database.
Consistency:
As redundancies are less in the database it makes the database more consistent and effective to the users as they will not input an entry and retrieve the wrong information required.
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Data sharing:
DBMS allows all users within an organisation to share information. only authorised users will be allowed to access information to certain aspects of data.
Improved data integrity:
This is the provision of consistency validity of stored data on the database. Constraints are normally expressed as integrity; these are consistent rules that the database cannot violate
Improvement in security:
DBMS protects data from unauthorised users. Passwords are required in order to users as well as restrict users to sensitive information that might not be required for that department, which can be implemented in operations such as retrieving, updating, inserting and deleting of the data.
It enforces standards:
The DBMS sets standards that have to be met while integrating the database from data formats, documentation standards, naming conventions, access rules and updating procedures
Scale of economy:
Savings are made when all of the companies’ operational data combined into one database with applications working on one data source.
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Data quality:
Many tools and processes are provided to enhance quality of data constraints are created, and cannot be violated, as they are a rule of the database approach
Improvement in responsiveness and accessibility:
It is relatively easy for a user without programming experience to display and retrieve data even by crossing departmental boundaries
Analysing the different approaches to data design:
Data modelling can be described as the process of documenting and formalising of existing events and processes that arise during software application design and development. The tools and techniques translate and capture complicated development and design which is translated into easily understood representation data processes and its flow, thereby creating a blueprint for its construction or updating previous versions.
A data model can be imagined as a flowchart or diagram which illustrates relationships between different forms of data. Capturing all the possible relationships can be quite intensive but should be done with care to portray a well-documented model which allows for change when errors are sighted before coding is done.
Multiple models are viewed by the architecture to ensure that all entities, processes dataflow and relationships are identified
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A database schema can be described as the structural skeleton, representing the logical view of the whole data base. Data is organised, defined and showing how relationships are associated, thereby showing all constraints that are to be applied on data.
The schema identifies its relationships and entities between them. A descriptive detail of the database is contained which can be illustrated by schema diagrams.
Schemas can be divided into two main categories
A database schema can be divided broadly into three categories
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Conceptual data model:
This model identifies relationships at the highest level between its different entities.
Conceptual data modelling
Enterprise data modelling:
This quite similar to the conceptual model but it bases it emphasis on the unique business requirement.
Enterprise data modeling
Logical data modelling:
This stands for the basis of creating the physical data model. it outlines the specific attributes, relationships and entities for a business function.
Logical modelling
There are four main data models:
A flat database:
This the simplest database system created. it represents data in single tables where all records are stored in single rows, delimiters, such as commas and tabs, are used in the separating rows of data. Representation of tables are a simple text file.
Network database
This allows multiple records linked to same file. this model can be described as a tree turned upside down whereby the branches are member information linked to the owner
Hierarchal Model:
In this model databases consist of number of records which are connected by links. it is quite like the network model reach record has many fields or attributes of which a data value is contained. The link shows association between records
Advantages of this model are easy to understand and navigation through records is relatively fast. The drawback is that it does not allow for changes
The Relational Model:
The basic concept of a relational model are the tables. Fields or columns are used in identifying all attributes
All data is view in the form of tables with each column representing an attribute. Importance is placed on the relationships between entities by the values stored in each column of corresponding tables.
Each table must contain a unique identifying key which could be used in relating to other tables.
One main advantage is that it allows for changes to be made anywhere, unlike the Hierarchal Model
1.2
Data Mining:
The computerised process of investigating and analysing large amounts of data to extract the trends or patterns of the data. These trends are monitored by data mining tools, to predict behaviours of future trends. These allows the businesses to make important business decisions. The data mining tool has resolved the problem of earlier years that were too time consuming rectify. The mining tool observes the patterns and trend. it also seeks out predictive information that experts might miss.
What can data mining do for our small DVD business are numerous other small businesses have taken up this concept. Tools are in place to gather up historic data using pattern recognition technology, mathematical and statistical methods to go through warehoused information. it would help the company create relationships with what their customers would want to buy, the bestselling payments, create a safe environment for customers to purchase their DVD films, by being able to create trends on their database by obtaining more useful information about their customers.
The DVD business could have better decision making, all the patterns and trends analysed can help spot trends in sales which would result in smarter marketing of the DVD’s, it also show loyalty of customers
Other uses of data mining are:
- Market segmentation it would identifythe common features of customers who regularly buy the same DVD’s from the company.
- The company would be able to predict the mostly likely customer to deal with another competitor
- They would also be able to identify a lot more fraudulent transaction based on the analysis of the data mining tool
- Direct marketing would be identified by the inclusion in a mailing list to obtain the highest response rate.
- They would be able to predict individual’s interests (being able to know what the customers would prefer to see on their websites
- Also, would be able to evaluate the trends from month to month
Automated predictions of behaviour and trends it automates processes of locating predictive information, hands on analysis can be answered from the data, the use of promotional past mailing can be used to maximise the most likely return on investments in future mailing
Data Warehousing:
Illustrates the capturing of data from different sources that are used for useful access and analysis which don’t always start from the point of view of end user that may require access to specialised, occasionally local databases. The latter statements are known as Data Mart
Data warehousing has two different approach which are:
- Top down approach
- Bottoms up approach
The top down approach is taken off data mart for specific groups of users after the complete data warehouse which has been created.
In the bottoms up approach firstly builds up the data mart then combining them into a single data warehouse.
A mainframe server or cloud (the storage technology used today) houses a data warehouse. Data from numerous transactions online that process (OLTP) and other various sources is extracted to use by analytical applications and the user’s queries
2.1
Normalisation:
This is the process of organising data in a database, this is done by creating tables which have relationships with the other tables which is done in order not to eliminate inconsistent dependency and redundancies.
Standardisation includes decaying a table into less excess (and littler) tables without losing data; characterising remote keys in the old table referencing the essential keys of the new ones. The goal is to separate information so that augmentations, cancellations, and adjustments of a trait can be made in only one table and afterward engendered through whatever remains of the database utilizing the characterized outside keys.
UNF:
Un-normalised form is a preliminary phase of the standardisation process permitting us to
Make an organized edge, illustrative of a bit of hierarchical information, for example, a
Shape or archive (e.g. receipt, report, buy request and so forth.). This is our underlying
Normalisation “connection” that contains both genuine information, taken from the structure or record,
Also, demonstrated information, based upon and reached out from the first from or report.
Right now, the un-standardized connection is only a major muddle of information however this preliminary
Stage is the most vital. As every phase of the normalisation procedure is needy
Upon the past, it is key for this, as the beginning stage, is set up with the privilege
Areas and information to guarantee a smooth move between the stages
For the case study, the un-normal form attributes are listed
| ORDER (order no, order_ date, customer ID, customer _name, customer_ address, customer_ telephone, customer_ email, customer_ city customer _postcode dvd _id, dvd _title, unit _price, order _quantity, order_ total, delivery _date, delivery _address, debit _card, card _no, expiry _date, CVC_no, order _quantity, genre, directors, certification, dvd _title, subtotal) |
1NF:
A database is in first normal form on the off chance that it fulfils the accompanying conditions:
Contains just nuclear qualities
There are no repeating attributes
| ORDER (order no, order date, order total, customer ID, customer name, customer address, customer telephone, customer email, city. Customer postcode, debit card, card no, expiry date, CVC_no, delivery- date, delivery _address,) |
| ORDER-LINE (order no, dvd no, dvd title, unit price, order quantity, line total, genre, certification, directors, actors, titles, subtotal) |
2NF:
A database is in second normal form on the off chance that it fulfils the accompanying conditions:
- It is in first normal form
- All non-key properties are completely utilitarian reliant on the essential key
In a table, if property B is practically reliant on A, however subject to an appropriate subset of A, then B is not practically being considered completely utilitarian subject to A. Consequently, in a 2NF table, all non-key traits can’t be reliant on a subset of the essential key. Note that if the essential key is not a composite key, all non-key traits are dependably completely practical subject to the essential key. A table that is in first typical frame and contains just a solitary key as the essential key is consequently in second ordinary structure.
| ORDER (order no, order date, order, total, customer ID,) |
| ORDER-LINE (order no, dvd id, dvd title, unit price, order quantity, order total, order date, genre, title, directors, actors, certification, subtotal) |
| CUSTOMER (customer-ID, customer name, customer address, customer telephone, customer city, customer postcode, card no, expiry date, CVC_no,, debit_card, customer email ) |
| DELIVERY (Delivery _no customer-ID, delivery date, customer_ address) |
3NF:
A database is in third normal form on the off chance that it fulfills the accompanying conditions:
- It is in second ordinary structure
- There is no transitive practical reliance
| ORDER (order no, customerID, order date, employee_ id) |
| CUSTOMER (customersID, customer name, customer address, customer telephone, customer postcode, customer city, customer email) |
| PAYMENTS (payment id, customer ID, debit card, card no, expiry date, CVC_no, order no, employee_ID,payment_colected ) |
| DELIVERY (delivery no, customer-ID, delivery date, customer_ address, order no,) |
| ORDERLINE (orderline no, order no, DVD id, order quantity, unit price, subtotal,) |
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