Introduction
After human resources, data is the most important asset in an organization. Data becomes useful when it is analyzed, and great insights are drawn from it, which guides the decisions of an organization. Organization data comes from various sources systems into the data warehouse of an organization. Data warehouses are very important as they provide the needed data for carrying out business intelligence and analytical tasks. The amounts of data that organizations are getting from their source systems have increased, forming what is currently known as big data. New technologies have been developed to cater for big data. Additionally, as technologies are being increased, so are organizations trying to reduce the effects that these technologies have on the environment. This paper will discuss the components of the data warehouse, big data, and green computing.
Components of a data warehouse is a repository of data both past data and cumulative data that comes from different source systems of an organization. A data warehouse is important in an organization as it acts as the main source of data that is used in reporting and business intelligence (BI) processes of an organization. The data warehouse architecture is made up of six key components. The first component is the data warehouse database. This is the main component of any data warehouse. It acts as a tank that stores data which will later be used for reporting. Thus, an organization has to choose its database well. There are four major databases that an organization can choose from. The first one is the relational database where data is stored in tabular form. Example of relational databases includes Oracle and SAP. Relational databases are the most used kind of database. The second type of database is the analytics databases which are mainly used for analytics purposes. An example of an analytics database is Teradata. The third type is the data warehouse applications which are basically applications that can store data. Lastly is the cloud-based data warehouse, which is a database that is hosted on the cloud.
The second component of a data warehouse is the Extraction, Transformation and Loading (ETL) tools. These are the tools that are involved in extracting data from different data sources, converting it into a suitable format and later loading it into the data warehouse. Choosing the correct ETL tools is key. This is because the tool that is selected will determine the time that will be taken to load data into the warehouse, how business rules will be defined, the transformations that will be done on the data, and the approach that will be taken in extracting the data. The third component of the data warehouse is the metadata. Data warehouse metadata refers to the data about data in the data warehouse. There are two types of metadata. The first one is the technical metadata that contains information which can only be used by developers and managers. Second is business metadata which contains information that business users can easily understand about the data warehouse.
The fourth data warehouse component is data warehouse access tools. These are tools that are used to access data from the data warehouse fro reporting and analytical purposes. These tools include (Online Analytical Processing) OLAP tools, querying tools, reporting tools, mining tools, and application development tools (Fatima, 2020). The fifth component is the data warehouse bus. It defines how data flows in a data warehouse. It also a data mart. The last component is the reporting layer. This layer allows users to access the data warehouse using different access tools.
Currently, there are several data warehouse trends. The first data warehouse trend is that data warehouses are becoming cloud-centric (Naeem, 2018). This means that a lot of organizations are migrating their data warehouses to the cloud. The second data warehouse trend is that data warehouses are now being automated. Traditionally, a data warehouse implementation solely depended on IT personnel which is very time consuming and tedious. With the automation of the data warehouse, organizations will be able to avoid all the complexities that are involved in data warehouse task, and it will help them save time. The third trend in the data warehouse is there is an increase in column-based storage to in make querying easier.
Big Data
The term big data is used to refer to large amounts that in different formats which originate from different source systems. The amounts of data that organization are getting form their source systems have been increasing as days pass by. Organizations are adopting different technologies that will help them make sense of these large amounts of data in order to gain a competitive advantage in the market. One of the ways in which I have seen big data being used is that it used to improve customer service (Memon et al., 2017). By using the existing customer data, organizations are able to get information on what their customers prefer, which is helping the organization serve their customers well. The second way that big data is being used is to discover new market gaps and opportunities. Organizations are using data to understand the market more and identify any gaps which they are using as an opportunity.
Big data is different from the traditional data that organizations were dealing with over the last years. Thus, there are several demands that big data is placing on organization and technology in general. To begin with, organizations need to change the analytical methods and techniques which they were using to analyze data (Pugna et al., 2019). This is because traditional methods are not able to deal with big data. This is due to the complex nature of big data. Secondly, one of the characteristics of big data is that it has a big volume. This means that it will require a lot of storage. Thus organizations are required to change their traditional storages to more advanced storage that can handle the huge amounts of data. The third demand that big data is placing is that it requires technologies now to be built in a way that they can handle large amounts of data. This means the technologies must have a high processing speed.
Green Computing
Due to the environmental pollution that is being caused by electronic devices, a lot of organizations are trying to go green. This is being achieved by implementing “green technologies.” Although environmental pollution cannot be controlled by a single organization or a government entity, various contributions can be made from different levels that can help to conserve the environment. One of the technologies that have been known to emit a lot of waste and consume a lot of energy is the data centres (Mata-Toledo & Gupta, 2010). Thus, organizations are trying to contribute to the worldwide effort of conserving the environment by making their data centres “green”. One of the methods in which organizations are trying to make their data centres green is by redesigning them in a way that consumes less energy. It is estimated that any given data centre consumes as much energy as five power plants would consume annually. Therefore, organizations are trying to redesign them in such a way that they will need less power. Other organizations are replacing their data centres and rebuilding new ones.
The second way in which organizations are trying to make their data centre green is by changing ore redesigning their cooling system. Cooling systems are also another concept of data centres that consume a lot of energy. Cooling systems are always overlooked when organizations are trying to go green (Mata-Toledo & Gupta, 2010). Organizations always forget that they consume a lot of energy as they try to bring a cooling effect to the data centres. Thus, as organizations are trying to go green, the are eliminating or changing the cooling systems that consume a lot of energy. The third way that organizations are trying to make their data centers green is by eliminating servers that are underused. If there are excess servers that are underused, it means that they are consuming power but they not necessary.
One of the organizations that have implemented IT green computing strategies is Microsoft. The major reason why Microsoft went green is to ensure that its people, products and programs all turn into the green revolution in order to conserve the environment. One of the ways in which Microsoft has gone green is by refurbishing computers (Treehugger, 2017). This means that Microsoft is giving computers that were discarded a makeover. Discarded computer is very dangerous to the environment as they are not bio-degradable. Microsoft launched a refurbished program in 2007 where it would help to reduce the environmental burden of the discarded computers. The second strategy that Microsoft has implemented is by creating products that consume less energy. This is not only helping Microsoft to go green but also the consumers of the products that are manufactured by Microsoft.
Some of the products that Microsoft is manufacturing that is consuming less power as compared to how they were a few years ago are data centers. Data centers are very important in organizations as they help to keep critical data of an organization safely. Data centers are one of the IT computing devices that consume a lot of energy. Thus, by creating “green” data centers, Microsoft is helping companies to also go green (Treehugger, 2017). Additionally, Microsoft allows server consolidation, which helps to eliminate underused servers. This helps to ensure that less power is consumed.
To conclude, a data warehouse is one of the most important IT infrastructures in an organization. It helps in carrying out business intelligence and analytical tasks. The amounts of data that organizations have right now are a lot as compared to earlier years. To get the maximum benefit from data, organizations have implemented different technologies. A lot of computing technologies consume a lot of energy and release a lot of toxins to the environment. Thus, organizations are trying to adopt technologies that will help them go “green”—one of the companies that have adopted various strategies for going “green” it Microsoft.