Components of a data warehouse, “big data”, and green computing


A data warehouse refers to the sources of business truth developed by combining data from various disparate sources. Kaur et al. (2016) argue that data warehousing enhances analytical reporting and structural and queries. Data warehousing systems, such as organizational designs, have several architectural options. According to Kaur et al. (2016), some data warehousing systems have Operational Data Source (ODS), while others are deployed with data marts. Also, some data warehouse may reference finite set of data source, or reference different internal and external sources of data, as Saltz (2017) finds that most enterprise data warehouses use this type of reference. Data warehouse architecture is unique to business use; therefore, common layers for all data are considered during development. In this regard, this study explores the major components of a data warehouse, “big data”, and green computing.

  1. Data Architecture Warehouse

According to Chamoni & Stock (2015), the five major components of data warehouse architecture include:

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  • Data warehouse database: the central database of the data warehousing environment that is implemented on the relational database management (RDBMS) technology. However, the implementation constrains since traditional RDBMS products optimize for transactional database processing.
  • Sourcing, clean-up, acquisition, and transformation tools: these tools are useful in obtaining data from operational systems and gathering accordingly, for informational applications. Also, the tools are useful in data transformation as they perform a conversion, summarization, key and structural changes, and condensation.
  • Metadata: describes the data warehouse by creating, managing, maintaining, and using the data. Metadata provides interactive access that helps users understand the content and find data. However, the inefficiency of metadata is that it many extraction tools are ineffective in gathering the data
  • Access Tools: useful in enhancing the principal purpose of data warehousing – proving information for strategic decision-making of the business. Most of these tools require an information specialist because, although many users develop expertise.
  • Data Marts: mostly, data marts present an alternative to a data warehouse because it consumes less money and time to build.

Various Forms of Data Transformation

  1. a) Format Revision

This form of data transformation contains numeric and text data types. In this case, a user needs to standardize and change the data to provide values that users can perceive correctly. The length of fields may be different, but easy to standardize.

  1. b) Recording of Fields

This transformation involves multiple source systems, whereby various field values describe the data. Weaver (2017) argues that many legacy systems use cryptic codes to determine business values. In this sense, the transformation changes codes into values to enhance the understanding of end-users.

  1. c) Calculated and Derived Values

Sometimes, a user has to calculate the total cost and profit margin before storing data in the data warehouse, an example of the calculated value. Also, a user may want to store customer’s contacts separates – an example of the driven value (Weaver, 2017).

  1. d) Splitting Single Fields

Splitting single fields occur when a user stores various information in different fields. For example, the first, middle, and last names are stored as a large text in a field.

  1. e) Merging of Information

This transformation form establishes a connection between different fields, like product price, package type, and description, whereby the fields are viewed as a single entity.

Current Key Trends in Data Warehousing

The data warehouse has been improving due to technological changes. Business organizations are adopting particular trends in technology to improve enterprise computing. The current key trends in data warehousing evolved from early terabyte technologies that helped businesses to manage large amounts of data (Kaur et al., 2016). In this regard, technology has implemented databases, applications, and other system sources that enhance business activities. For example, the databases enable a business to survive in the global market by reaching a broad base of customers, promoting supply chains, marketing, and other operations. In this regard, companies that have data warehouses are advancing and becoming more competitive due to technologies like Hadoop and in-memory processing, which are efficient in managing “big data.” The data warehouse has become bigger and faster than in the past, thus capable of performing business-critical functions and supporting new data types. Also, trends in the data warehouse are allowing stakeholders to access the enterprise at any time and place. Generally, the key trends in data warehouse include technologies that enhance innovation, business agility, and competitive advantage.

  1. “Big Data.”

My Understanding of Bid Data

Big Data is a term that represents the large volume of data, structured and unstructured, that inundates a business on a daily basis. However, of more importance is not the amount of data, but how the organization uses the data. Big Data needs technologies, such as databases, and applications to store since traditional data management tools cannot store the huge-sized data. More importantly, Big data promotes analysis for insights that helps results in better decisions and strategies for improving the business. The use of Big Data has become common in companies, as they try to sustain their competitive advantage. In most industries, competitors and new entrants use data analysis as a strategy for innovation and enhancing their value. Big Data helps an organization to create new growth and development opportunities since companies can combine and analyze industry data. In this regard, Big Data refers to the companies’ information about buyers and suppliers, products and services, and consumer preferences. Also, Big Data describes the collection of huge-capacity data that is useful in analyzing the business environment since the data provides essential information that helps a company to survive in the global market.

Example of How Big Data is Used

The use of big data has become crucial for most leading companies since companies can outperform their competition. In this regard, Big Data is used by new entrants and competitors to develop their strategies of enhancing their competitive advantage. For example, popular tech companies, like Microsoft and Apple Inc., use Big Data to analyze the global market and identify opportunities. Through the use of Big Data, tech companies have implemented features that meet customer needs and expectations. For example, Apple Inc. has implemented iPhone 11, which has a powerful camera, waterproof and big-sized touch screen, and other features that promote its marketing. In this regard, the company (Apple Inc.) analyzes the global market by the use of Big Data, thus obtaining essential information for sustaining its competitive advantage. Also, healthcare using Big Data to analyze the outcomes of pharmaceutical, as Saltz (2017) argues that companies discover risks and benefits in clinical experiments by the use of Big Data. The implementation of various products, like smartphones with different features, and children’s toys are also examples of the application of Big Data.

Demands of Big Data on Organizational and Data Management Technologies

According to Harvey (2017), Big Data needs organizational and data management technologies to adopt the best practices to overcome various challenges and maximize the benefits of Big Data management.

One of the requirements of Big Data is the involvement of team members in management efforts. In this regard, Big Data requires organizations to create policies and transform their organizational culture to enhance Big Data management. Apart from investing in technology, Big Data requires organizations to involve all relevant departments in big data management (Harvey, 2017). Big Data is also demanding for IT professionals to assist the organization in data management.

Another requirement of Bid Data is creating written policies and strategies for data lifecycle management. Big Data needs organizations to implement policies that promote data management. Due to the risks of cyberattacks and data breaches, Big Data demands data management technologies that can identify and protect sensitive data (Harvey, 2017). In this regard, Big Data requires organizations to implement access control policies for enhancing data security.

Also, Big Data demands organizations to train their employees about data management. According to Harvey (2017), Big Data management requires experts; therefore, employees must develop specific knowledge and skills for effective data management.

  1. “Green Computing.”

Green computing is the responsible use of computers and related resources to make them eco-friendlier. Green computing is essential in data centers because it improves functioning; users find information at the click of a button. According to Gifford (2014), Microsoft is one of the companies that have implemented IT green strategies successfully. In this regard, companies can learn different ways of implementing green computing by adopting Microsoft’s strategies.

Microsoft is engaging citizens in implementing IT green. According to Gifford (2014), Microsoft’s early products were packed in PVC materials. However, the company realized the hazards of PVS on the environment and began packing products in environmentally-friendly materials. In 2005, the company had eliminated 1.5 pounds of plastics. In this regard, organizations may implement IT green by adopting the use of environmentally-friendly materials.

Another way in which Microsoft implemented its IT green was by partnering with the government, whereby the company supported President Bill Clinton in his Clinton Foundation. The principal purpose of the foundation was to identify ways in which the largest cities, worldwide, can reduce greenhouse gases and carbon output. Microsoft has been supporting environmental agencies that advocate for a healthy environment. For instance, Gifford (2014) argues that Microsoft is a part of Climate Savers and The Green Grid Consortium, initiatives of power efficiency in all industries. In this sense, organizations can implement IT green by partnering with the government and environmental agencies, which advocates for a healthy environment.

Based on Microsoft’s practice of IT green, organizations can implement IT green by researching the needs of the environment. According to Gifford (2014), Microsoft supported university grants with $500,000 to enhance their research on environmentally-sensitive computing. In this case, Microsoft has not only implemented IT green successfully but also sustained its competitive advantage because the government supports its practices. In this sense, organizations can implement IT green by supporting university to research environmental needs, like Microsoft company, which facilitated the Imagine Cup software development challenge in 2008.

Gifford (2014) argues that Microsoft earned more popularity in 2011, as people recognized its effort in environmental conservation. In this case, Microsoft created a critical watchdog group (Greenpeace), which helped the company to eliminate toxic chemicals from its products. Gifford (2014) argues that some tech companies may not realize their electronic products consist of toxic chemicals that are hazardous. In this sense, organizations can implement IT green successfully by creating groups that may help them eliminate toxic chemicals from their products. According to Gifford (2014), companies competing in the global market need to have their environmental representative worldwide to ensure the products are environmentally friendly. Like Microsoft organized groups for eliminative toxic chemicals from its products, organizations can implement IT green by discouraging the production of toxic chemicals.

Organizations can also implement IT green successfully by employing environmental strategists. According to Gifford (2014), Microsoft appointed Rob Bernard to the new position of Chief Environmental Strategist. In this case, Rob Bernard was to find all the environmental aspects of the company and initiate improvements. Like Microsoft, organizations may implement IT green by creating special departments for monitoring the environment. Gifford (2014) argues that Bernard stated that his role would be providing more structure, assistance, and guidance in helping people realize environmental problems and challenges. Therefore, the environmental departments should research factors of a healthy environment, the products of a particular company.

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