The Big Data Challenges
While dealing with information technology, big data challenges are the enormous and complex collections of data sets, which are difficult to process or handle using the traditional data processing systems. Notably, big data challenges vary in different stages. These stages include capturing of the data, storage, analysis, and sharing of information. The rise of the huge data is due to the growth of technology in organizations making it easy to derive information from different places. The acquisition of these data involves various components of the information technology systems. These components of information technology system interrelate in the organization so that they can be able to come up with computer-based information. Namely, some of the components are hardware, software, data, procedures and the people using machines.
The paper explicates the interaction of the components of information technology system and makes comparisons and contrasts between strategic and operational use of data management systems.
Explain How the Components of an Information Technology System Interrelate In an Organizational Context
Key components of information technology systems that interrelate in an organization set up include the hardware, software, data, people and procedures. Here is how these components interrelate.
Firstly, the hardware is a physical part of computers used for imposing commands on the software. Normally, these two components interrelate during data entry in an organization. O'Reilly Radar Team (2011) asserts that after the data collection, there is the application of commands on the hardware that interacts with the software to come up with the final information, which is process data.
Secondly, another interrelation is between the procedures and the user or the people. A user of the computer in an organization follows certain procedures while entering the data for processing to finished information. Garson (2007) affirms that this implies that the user cannot work without procedures, which provide the information that they want to use. It is significant to note that procedures cannot guide themselves and come up with the final information. Instead, they have to interrelate.
Compare and Contrast the Strategic and Operational Use of Data Management Systems
The strategic and operational uses of data management have both similarities and difference despite the fact that both are used in data management systems.
Similarity
The key similarity between these two uses of data management is that both of them center on assuring single view of master data. According to Ohlhorst (2012), the master data is ideal for an organization since it determines the eligibility of the final information. Normally, if an error occurs at the master data, then the whole process may be affected.
Differences
Remarkably, the difference between the two data management systems is that operational management system centers on assuring the single view of master data in the core systems mainly applied by organizational users. On the other hand, the strategic management normally concentrates on assuring single view of master data in the downstream data warehouse, which is mostly applicable in the supply of data for business intelligence solutions.
Regarding that, the main difference between the two systems occurs at the master center, and their similarity is evident in the use of some technologies.
Judge how Volvo Car Corporation integrated the cloud infrastructure into its networks
The Volvo Car Corporation incorporated the cloud infrastructure into its networks so that they could acquire data from the Volvo vehicles to assist assemble superior cars as well as to aid the clients to have a enhanced experience. Notably, capturing of data is for use inside the vehicle itself, and ever more, for broadcast through the cloud back to the firm. At Volvo, those colossal amounts streamed into a notable examination center, the Volvo Data storehouse, along with data captured from client affiliation systems, dealership systems, as well as goods enhancement and design systems.
Explain how Volvo Car Corporation transforms data into knowledge
Notably, during the previous years, though, Volvo is undergoing a bottomless revolution in its business replica leveraging at least four digital technologies: which are social media, mobility, as well as smart entrenched devices analytics. Moreover, intention is to build up a further direct affiliation with the end client devoid of distracting the relationship brokers have with their clients. Notably, anxiety for transformation emerged from mutually clients as well as rivalry.
Identify the real-time information systems implemented and evaluate the impact of these implementations
Remarkably, the allocation hub gets a standard of 55 trucks each day amid ordered products from the thousands of diverse dealers all around the globe. Purnell (2012) asserts that regarding the huge inbound goods capacity, controlling the figure of incoming trucks every day is vital for mutually the economic as well as operational motives. Furthermore, two of the effects that tag along from difference in inbound goods capacity are firstly an incapability to organize as well as optimize the products receiving's manning-capacity, and to add on that being enforced to situate goods in the open; exposed to climatic conditions that contribute to expenses as well as risk the clients service. Today, the quantity of inbound trucks regulates at 55, but experience a disparity from 45 to 75 trucks each day.
Argue how the Big Data strategy gives Volvo Car Corporation a competitive advantage
The big data strategy obliviously gives the Volvo car Corporation a competitive advantage. This is notable from the way the big data strategy has enabled the Volvo Corporation to undergo evolution. After going through the business replica leveraging at least four digital technologies, the Volvo Corporation is planning to build up a further direct affiliation with the end client devoid of distracting the relationship brokers have with their clients.
