Data Warehousing Essay Example

Introduction

The concept of data warehouse refers to a collection of subject-oriented, integrated, nonvolatile, time variant data, for historical information and able to support decision-making. Subject-oriented warehouses are designed to store data by subject matter such as sales, region, brands etc. integrated warehouses aggregate data from different sources into a consistent format (integrated data). The data entered into the database should not change. Addition of data over extended periods allows the building of big data that can be analyzed for trends. All types of organizations use data warehouses to store their transactional data to support the decision-making process. As the organization continues to transact, new data is added to the warehouse. As such, data warehouses are dynamic because of the frequent addition of new data to the existing data (Coronel & Morris, 2016).

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The Significance of the Concept

Data warehousing is becoming an increasingly important concept for contemporary organizations. In particular, the data stored in databases is used for business intelligence. Business intelligence is a technology-driven process for analyzing data to help corporate executives and other end users to make more informed decisions. Organizations are looking to big data for new information about the industries they operate in including consumer behaviourbehavior and existing as well as future trends (Thomas, 2018). With increased competition in different sectors, data warehousing has become an essential competitive advantage tool for organizations.

Implementation Of of Activities Related To to the Concept

Because data warehousing is technology-centered, the practice is changing very fast in keeping with the pace of changing technology. New data warehouses that are agile, leverage the cloud and the next generation of data (associated with real-time data, streaming data and data from the Internet of Things (IoT) devices) are being developed.

The conventional Extract, Load and Transform (ELT) systems can be very expensive and labor-intensive. Organizations using big data leverage the latest technologies to improve efficiency. For example, instead of the extract, load, and transform process, data is extracted and directly ingested in new approaches.

Application Of of Concept In in Current Job

Data warehousing is used in the current job to store a wide variety of information. All transaction data are stored in the database. The company is leveraging the power of the cloud to store data online.

Usefulness Of Theof the Concept

Data warehousing is changing the way people interact with data and how they extract value from data. Virtually all organizations store data in some kind of database. They analyze this data for various decision-making purposes.

Thomas, B.E. (2018). The data warehouse in 2018. https://www.cio.com/article/3245386/data-warehousing/the-data-warehouse-in-2018.html

Operational systemSystemThis is a term used in data warehousing referring to the method used to process transactions in organizations. These systems are designed so that transactions are performed efficiently while preserving the integrity of the transactional data. Operational databases are normally "relational." They are designed for operational, data entry purposes (Di Tria, Lefons, & Tangorra, 2016).

There is an increasing need to integrate operational data from external firms as globalization, outsourcing, and mergers increase apace. The sharing of different types of data between industry players can increase business intelligence. The particular challenge with data warehousing is to quickly consolidate, cleanse, and integrate data from different databases that run on different technical platforms, and in many cases, different geographical locations.

The Significance Of Theof the Concept

An operating system plays at least five important roles in data warehousing. First, an operating system manages all the resources of a computer associated with data warehousing. These resources include the monitor, keyboard, mouse, printer, and memory. It ensures that the resources work in synchrony for the computer to receive and execute functions. Second, operation systems provide user interfaces. For example, the development of Graphical user interfaces (GUI) allows users to understand commands to the system easily. All icons on the computer desktop represent a code linking the icon to what it represents for all kinds of users. Third, an operating system provides the ability to run applications on the desktop by locating the application and placing it into the primary memory. The ability of an operating system to multitask allows users to run multiple programs or tasks at the same time. Fourth, operating systems support built-in utility programs that play the essential role of finding and fixing errors in the system. Finally, operating systems plan a critical role in controlling computer hardware. In other words, all programs that require computer hardware to function must go through the operating system which can be accessed through the device drivers.

Implementation Of of Activities Related To Theto the Concept

The dynamic nature of technology has far-reaching implications on research and development of new operating systems. The changes in the sector are mainly due to the changing ways in which people interact with data. Not so long ago, people used the landline telephones to communicate. At that time, computers were essential to data warehousing. In recent times, there has been widespread smartphones and other handheld devices. As such, users can collect, store, and access data via mobile devices. But mobile phones and computers use different operating systems. Thus, the current trends are associated with how we can have a responsive and unified system that can bring together computers and mobile phones to improve the computing experience. The current activities in the area of operating systems are related to the development of new operating systems that enable the application of the concept of data warehousing across all platforms. Recently, there has been introduction and development of mobile operating systems such as Android operating system, Bada, Blackberry operating system, iPhone operating system, and Symbian operating system among others.

Application of Concept In in Current Job

Microsoft Windows Operating systems are currently applied to the organization's computer systems. The company has a mobile application that can be downloaded on mobile devices running on either the iPhone operating system or Android operating system. This ensures that company data can be accessed via mobile phones as well as desktop computers.

Usefulness of the conceptConceptOperating systems are at the centrecenter of computing. There would be no computing without operating systems. Therefore, they are useful in the current world because they allow for the application of a wide variety of programs that make things easier for users. Operating systems are fuelling development of new applications that solve almost any other problem.

Flat File Database

The concept of flat file database relates to the storage of data in plain text format. A flat file includes a table with one record for each line in a relational database. The different columns are comma-delimited to separate the fields. However, a flat file database does not contain different tables like a relational database. In other words, data stored in plain text format does not have paths or folders associated with them. They are widely used to import data in data warehousing projects. They carry data from the server quite easily and store information in tables. There are no relationships between the tables included in the database. They are preferred among programmers when creating applications in Oracle and SQL. Flat files consume small space due to their simple structure, unlike the structured files (Yusof & Man, 2018).

The Significance Of Theof the Concept

As mentioned above, flat file databases constitute a one record per line in text format, a binary file that separates columns by using "delimiters." This plays an important role in searching for information through records. Delimitation of records can be through the fixed length. Some field-padding can be carried on records that are too short to allow for the same length of the record as the text leading to a uniform byte-length between texts. Another significance is that flat files allow for storage of configuration files Extended Markup Language (XML), which has some specific delimiters. As such, XML files are increasingly applied in the building of specific modules on a website.

Current Research Activities Related To The Concept/ Implementation Of Activities Related To The Concept

There are little research activities related to flat file databases. However, it is increasingly implemented in big data. XML is preferred by many people to manage and analyze large volumes of data for decision-making purposes. Organizations leverage the ability of XML in data retrieval and storage processes. Flat File databases are suitable for handling large records of publication data because of its query retrieving speed and CPU usage.

Application Of Concept In Current Job

Flat file databases are common in the workplace. A lot of data is stored in MS Excel files for sharing, analysis, planning, and decision-making. For example, marketers put data in these databases and use them to track their marketing activities.

Usefulness Of The Concept

Flat file databases are important in the real world because they are a simple way of storing large amounts of data. In particular, many organizations use spreadsheets as the initial storage of data before exporting it to relational databases.

Yusof, M. K., & Man, M. (2018). Efficiency of flat file database approach in data storage and data extraction for big data. Indonesian Journal of Electrical Engineering and Computer Science, 9(2), 460-473. https://www.researchgate.net/publication/322469571_Efficiency_of_flat_file_database_approach_in_data_storage_and_data_extraction_for_big_data

Relational Databases

In a relational database model, data is organized into rows and columns of a table. Attribute values are required to be indivisible (atomic). The domain is atomic if its elements are considered to be indivisible. Examples of non-atomic domains include a set of names, composite attributes and identification numbers that can be broken up into parts. A relational schema R is in the first normal domain if the domains of all the attributes of R are atomic. Non-atomic values complicate storage and encourage redundant storage of data. Relation instance refers to a specific instance of a relation containing a specific set of rows. SQL data allows the specification of information regarding relations, i.e. the schema for each relation, domain values associated with each attribute, integrity constraints, indices to be maintained for each relation, physical storage structure etc. (Adamski, 2011).

The Significance Of The Concept

The relational model is increasingly used in database design. When designing a database, decisions have to be made concerning taking a system in the real world and model it in a database. The decision-making process comprises selecting the types of tables, their columns, and the relationships between the tables. Based on this requirement, it follows that the design and development of a well-refined database take time and effort. It would be nice if this process is intuitive and obvious, or even better automated. A well-designed database takes time and effort (Wade & Chamberlin, 2012). The end product of a relational model design offers many benefits such as efficient entry of data, retrieval, delet...