Quantity and Quality of Data

This report discusses the proper management of data in organizations, focusing on approaches for managing data more accurately and precisely. It also explores the impact of data quantity and quality on business performance.

Running head: QUANTITY AND QUALITY OF DATA
QUANTITY AND QUALITY OF DATA
Name of student:
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Introduction
This report aims to discuss about proper management of data in organisations. A
detailed discussion of the best approaches for managing data more precisely and accurately is
provided in this report. Lastly, this report concludes with an appropriate conclusion.
In the current times, as the functions of business are increasing, the requirement of
appropriate data management is increasing in organisations for fortifying the customer data
(Stonebraker et al. 2013). The data that is stored in the database of the organisations needs to
have integrity and proper accessibility.
Discussion
There is a requirement of appropriate data management in the business of the recent
times for maintaining the integrity of the data of customers. DBMS is the most popular
application that is used for managing and creating the databases. DBMS offers the user and
the programmers with a organised method of retrieving, creating, managing and updating
data (DeBrabant et al. 2013). A DBMS provides the organisations with the opportunity of
creating, reading, updating and deleting data effectively in any database. DBMS
fundamentally functions as the interface among the database and the end users or the
applications programs, guarantee that the data is constantly organised and it rests quickly
available. DBMS monitors the most essential things, which are database engine, data, which
permits the easy accessing of data, locked and modified data and the schema of the database
that describes the logical organisation of the database (Reddy et al. 2014). These three
fundamental elements helps in providing concurrency, data integrity, uniform procedures of
administration, and security. The mutual tasks administration of database that are supported
by DBMS includes the performance monitoring, recovery, and the change management, and

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backup. Several systems of database management are also accountable for the recovery,
restarts, automated rollbacks, and the auditing and cataloguing of any action.
DBMS can provide both the physical and logical data independence (Arasu et al.
2016). It means that protection to the applications and the users can be provided about the
location of the storage area of the data or about any changes in the physical data structure of
the data (hardware and storage). As the programs practise API for database that is offered by
DBMS, the developers would not have to alter the programs due to any changes in the
databases (Shin et al. 2013).
The management of data is the crucial part of an organisation that stores, collects, and
manages the data, especially with new GDPR guidelines that monitors the management of
data across the organisations (Alam and Shakil 2013). The prospect of data management
relates to the data lifecycle and the processes by which the data transmits in the organisation,
whether the insights that are related to the customer, legacy data, which can be utilised for the
predictive analytics for observing the methods by which the previous events or the actions
have affected the operations of a business. It covers several stages of data cycle that includes
the acquisition, storing, processing and protecting the data for ensuring availability, relevance
and consistency of data for the users of organisation. It is considered that the best data
management must help in ensuring compliance to regulations and ensure the approach of a
company for utilising the data is secured to the penalties. The need of data management is
growing to be crucial issue for the businesses because of the huge quantity of the data that is
produced by the businesses. More data denotes the challenge of storage management and the
sorting of the important data from the duplicates.
The method that is commonly used for the management of data is with the utilisation
of master data file which is commonly known as the MDM or Master Data Management.

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This file denotes an asset and the properties of data for removing the rival policies of data and
provide any organisation an overall control of the data (Deelman et al. 2015). The alteration
of the master data is commonly managed from any single location.
The common practices that are used for the management of data for gaining business
insights starts with the decision of the major requirement of the business, and then obtaining
the data that is required for fulfilling the requirement. It is commonly suggested to the
organisations to judiciously consider the procedures and the documentation of the data
collection prior collecting data. Using the data templates must ensure the collection of usable
and relevant data. The data must be also subject to the quality control. It could include the
double-checked data that is provided manually by utilising the level flags of quality for
signifying the potential problems, check the consistency of the format and include the
methods of data cleansing. The data must be documented for describing the information,
context and the parameters and identify the staff who can utilise the data most effectively.
The documentation also includes the creation of wide-ranging tags of meta-data for enabling
the users to find and use the data. When the archiving of the data is done by the organisations,
it is commonly observed that a repository is utilised for supporting the discovery of data,
distribution, and the access (Rajakumari and Nalini 2014). Advanced analytics is also
essential for the database management. The major challenge that is faced by several
organisations is that how to effectively utilise the analytics and then integrate it with the
processes of business. The integration of analytics in the processes of business would ensure
the better success degree in the projects of data management.

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ERD relationship
The impact on the performance of the business can be managed and monitored with
the implementation of the better quality database management system for the company. It
would help in the effective monitoring of all the data in the business.
Explanation of the Relationship:
To fulfil the requirements of the Pricilla three relationship need to be fulfilled which
are the one-to-one, one-to-many and many-to-many. In the case of the one-to-one both of the
tables may have just one record on the either side of the relation. Each of the primary key is
related with no record or only one record in the table which are related.

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In the case of the one-to-many relationship one row of a table may be linked with
many rows in the other related table. If the first table is considered as the table A and the
second related table is considered as the table B then in one-to-many relation case one row in
table B will be linked with only one row in the table A.
For the case of the many-to-many relationship it is a typical type of relationship
between the tables of a database when the parent row of a table holds many child rows in the
second table and vice versa so on.
Database Report:
Currently database report can be produced and available to her which can help to
enhance the business. To get the data first the data need to be extracted and for this query
must be run with various types of tools. The query language which can be used for the
producing the database report is the Hyper Text Structured Query Language, Poliqarp Query
Language and the SPARQL. Using these tools annotated text and graphical applications can
be made available to her. This report also provides the output of the parameters. This type of
report can help the organization to manage the customers which will enhance the business.
Impact on performance when increased data is stored:
In the initial condition when the amount of stored data is low the performance of the
database is very much high. In such of the cases the database might store about 100,000
records. With the increased amount data with the time actually the performance of the
database is dropped as it needs more time to perform a query due to huge amount of data.
Generally the performance drop is seen when the database is reached at the 10 million of
record.

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Conclusion
Therefore, it might be resolved that the organisations entail the efficient management
of data for helping in operations of business. In current times, as the functions of the business
are increasing, the requirement of the proper management of data in organisations to secure
data of customers. In order to manage the data properly of any company, a tendency of
businesses is increasing in the companies for implementing database management system.
The application DBMS is a system software, which is commonly used for the management
and creation of databases.
As it has been seen that performance of the database is decreased when amount of
data is increased. Thus it is very much important to improve the design of the database which
required for the business of the Pricilla. Thus for improving design the first required thing is
the planning. It is not possible for the developers to start coding randomly without having any
type of proper plan. There are many methods of developing the optimised database such as
agile and waterfall model. The second step is the model documenting. Documenting the
model is very much important because it helps the developer to understand the project
perfectly. The third step is following the conventions. Naming the conventions is very much
important for the database design purpose. This is because, the names provide insights which
is required for understanding a model properly. Caring about the keys is very much important
in the database design. The keys are important because these keys often generate
controversies. Normalization is required for an optimised database which can be generated by
the identifying key. Those above steps are the main requirement for an optimised design of
database. The other requirement for better designed database are the indexing the design,
avoiding common lookup tables and defining the archiving strategy.

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