Management of Business Telecommunications
Introduction
The greatest contributor to the success or failure of organizations is the infrastructure in place. According to Chaskin (2001), organizational infrastructure refers to how business policies and procedures of an organization are collected based on the various duties and responsibilities of the stakeholders involved. Often, organizations witness change in their internal and external requirements, and this means that having well-organized organizational infrastructures is essential. One of the key organizational infrastructural components is the network infrastructure, which without a doubt provides a foundation or platform on which every IT-related service and application resides or operates. In the real sense, organizational network infrastructure supports the critical organizational functions such as data storage, processing, voice communications, as well as the security of organizational data. With effective network infrastructures, organizations often get a return on investment as network-related services are delivered smoothly, and this, in turn, drives organizational growth. Every organization focuses on improving its network infrastructure and organizations such as Microsoft and Inspirage have not been left behind.
Cain et al (2015) argue that Microsoft, for instance, through its director of strategic sourcing, reaffirmed its commitment and focus on improving its network infrastructure to cope with the ever-changing technological world, especially the era of Big Data. In preparation for Big Data, Microsoft being one of the leading organizations in terms of profitability has expanded its data centers by deploying over 100 data centers in more than 40 countries. On the other hand, Inspirage, being one of the leading ‘integrated supply chain’ specialists that focus operational excellence, has been forced to make changes to its network infrastructure to cope with the new era of Big Data. Akerkar (2013) argues that big data refers to the large volume of structured and unstructured data, which plays a key role in the inundation of business operations on a daily basis. It is important to note that, with Big Data hurling toward the enterprise, the likelihood of it having an impact on existing organizational infrastructure cannot be ruled out. For example, organizations have in recent years embraced new and advanced network infrastructures to cope with the data traffic flows caused by the advent of Big Data. As such, this paper seeks to address how the network infrastructure of two organizations, Microsoft and Inspirage, can be impacted by the new era of Big Data.
Body
Microsoft Corporation: https://www.microsoft.com
Values, vision, mission statement
Microsoft Corporation, commonly referred to as Microsoft, is a multinational technology company situated in America, with its headquarters in Redmond Washington. It deals with the development, manufacture, licensing, provision of support, and sale of computer software, personal computers and services, as well as consumer electronics. Some of its software products include the Microsoft Windows, Internet Explorer, and Microsoft Office Suite. It was founded in 1975 by Paul Allen and Bill Gates, the latter being the overall person in charge currently. As with every other organization, Microsoft has core values, and it believes that its staff should act with honesty and dignity, have respect, be persistent, be passionate about technology and customers, be accountable to peers, and be questioning, self-critical and committed to excellence. Its mission is to work with and to help people, as well as business worldwide, realize their full potential, and this has helped it achieve most of its set goals and objectives such as increasing profitability and revenue generation over the years. Currently, the vision of Microsoft is to empower people through great software, at any time, on any device, and at any place.
Identification and description of new network adoptions
While seeking to pave the way for the new era of Big Data, Microsoft Corporation has adopted new network infrastructure, a move that has seen the abandonment of old network infrastructure. One of Microsoft’s latest network adoptions is the cloud system, which has seen several companies especially the big companies, shift from the email system to the clouds system. The cloud software adopted by Microsoft runs in the corporation’s data centers, and with the era of Big Data, its advantage is evident as it has enabled Microsoft to handle of information or data ranging from all the software, hardware, as well as networking upgrades. Thomas and McSharry (2015) are of the opinion that Microsoft’s adoption of the cloud software has made it easier for its customers who do not have to sweat when it comes to accessing or handling a bulk of the corporation’s data. Another new network adoption of Microsoft Corporation is the Windows 10 program. There is no doubt that the era of Big Data has seen organizations such as Microsoft face issues such as incompatibility of information or data (Edwards et al, 2011). As such, the adoption of Windows 10 to a large extent has helped prepare Microsoft for the Big Data era, and this owed to the fact that it is built with compatibility in mind, and it also works with a variety of programs, an insinuation that traffic of data will be minimal.
Management recommendations for Big Data
Davenport and Dyché (2013) mention that every organization, including Microsoft while preparing for the new era of Big Data must give consideration to the need to upgrade existing technologies to allow integration of new ones. Besides, organizations must give consideration to changes in various sectors such as processing, employee skills, as well as management improvements (Minelli et al, 2012, p 25). From a management point of view, it is important for organizations such as Microsoft to be ready and prepared for the Big Data era, and as such, the implementation of various management recommendations is important. For Microsoft, one of the management recommendations for Big Data is that old technologies should be integrated with new technologies or they should embrace innovation as this will pave the way for or accommodate Big Data technologies (Fuller, 2015). Another management recommendation for Big Data at Microsoft is that attempts should be made to augment the ability of staff to manipulate Big Data technologies as well as integrating existing analytical staffs with other data scientists with greater levels of IT capabilities.
Evaluation and analysis of Big Data to be adopted by Microsoft
As already mentioned, the new era of Big Data will see the enterprise, Microsoft included, will make significant strides in terms of revenue generation and profitability. The achievement of these objectives by Microsoft depends on the Big Data tools that will be adopted by Microsoft. Other than the already mentioned network adoptions such as Windows 10 and the cloud system, one of the Big Data tools in line at Microsoft is Apache Hadoop, which is a renowned platform for open-source data processing. Microsoft’s adoption of Apache Hadoop, which has in the past been adopted by giant companies such as Facebook and Yahoo, will see Microsoft enhance its capability of organizing its rack of servers and NoSQL databases, which play a crucial role in the storage of data in the racks. Mohanty et al (2013) believe that Microsoft’s adoption of Apache Hadoop will increase its chances of tackling Big Data, to which the enterprise is headed.
Impact of Big Data on Microsoft’s network infrastructure
Microsoft’s network infrastructure can be impacted in various ways, either positively or negatively by the new era of Big Data. First, big data can help in the cost reduction of Microsoft’s network infrastructure. For instance, the adoption of Hadoop clusters by Microsoft can play an integral role in the reduction of the cost of terabyte storage for structured data. In the real sense, the cost of storing one terabyte for a traditional relational database for one year in the previous years was around $37,000, although the same can cost up to a mere $2,000 for a Hadoop cluster (Pearson and Wegener, 2013, p 23). Second, big data can diminish risks on Microsoft’s network infrastructure, and this objective can be achieved because the adoption of big data helps in the optimization of the complex decisions that are often involved in events or business decisions that are often unplanned.
Inspirage: http://www.inspirage.com
Values, vision, mission statement
Inspirage is one of the leading integrated supply chain specialists known for its operational excellence when it comes to giving solutions to critical business challenges ranging from design to delivery. It provides services such as cloud services, project and portfolio management, management consulting, business intelligence and analytics, enterprise data management, as well as business applications implementation. Its value is that critical business challenges that cross-functional domains should be solved and that clients should be provided with the highest value. Its mission is to bring industry-specific experience as well as solutions that are proven in a bid to help clients or customers to solve problems they experience and build a supply chain that is effective and responsive. The vision of Inspirage is to ensure the delivery of business processes, enabling technologies, outsourcing services, and infrastructure, which in the long run will enable clients to be successful with on-premise solutions and in the cloud.
Identification and description of new network adoptions
As with Microsoft, Inspirage’s new network adoption is the cloud system, which has helped address possible challenges accompanying big data by breaking down barriers as well as identifying opportunities for continuously improved performance. In fact, Inspirage’s cloud system has paved the way for the adoption of big data, and this, according to Fairhurst (2014), has addressed problems experienced in the supply chain process.
Management recommendations for Big Data
As with the case of Microsoft, there are various perspectives that Inspirage ought to take into consideration in its preparation for the new era of big data. Essentially, it is imperative for Inspirage’s top management to ensure that some existing technologies are upgraded as this will allow for the integration of new technologies. Most importantly, the management of Inspirage, as in the case of Microsoft, should consider making changes in sectors such as processing, employee skills, and management improvements, all of which are crucial for the adoption of big data (Jewell et al, 2014, p 16). A key management recommendation for big data at Inspirage is that the existing staff should be trained on how to handle big data as it is through this that their ability to manipulate big data will be augmented.
Evaluation and analysis of Big Data to be adopted by Inspirage
To speed up the achievement of its set objectives such as increased revenue generation and profitability, Inspirage seeks to adopt big data tools, and in particular, the Tableau Desktop and Server, which enables organizations to look at a wide range of data in new ways, after which it helps to break down large data and look at it in a different way (Demchenko et al, 2013, p 24). Through this big data platform, Inspirage will enjoy an interactive mechanism where the possibility of slicing and dicing data repeatedly will be made easier.
Impact of Big Data on Inspirage’s network infrastructure
The new era of big data can impact on Inspirage’s infrastructure in numerous ways. According to Schmarzo (2013), one of the adverse impacts of big data on Inspirage’s network infrastructure is that it can lead to increased network traffic, presumably as a result of the backup of big data repositories as well as the continuous collection of data. Ohlhorst (2013) reaffirms that big data can lead to the collection and storage of large amounts of data, which in the long run can jeopardize Inspirage’s network structure.
Conclusion
In a nutshell, as discussed above, as organizations are headed to a new era of new data, the fact that their network infrastructures will be in jeopardy cannot be ruled out. Organizations such as Microsoft and Inspirage have new network adoptions and big data tools. However, as seen above, the network infrastructure of the two organizations can be impacted by the era of big data. At Microsoft for instance, the new era of big data can result in the reduction of the cost of terabyte storage for structured data as well as diminishing risks on Microsoft’s network infrastructure. On the other hand, at Inspirage, the new era of big data can lead to increased network traffic, presumably as a result of the backup of big data repositories and the continuous collection of data.
References
Akerkar, R. ed., 2013. Big data computing. Boca Raton, FL: CRC Press.
Cain, N., Luescher, M., Flynn, D., Morales, A. and Tulloch, M., 2015. Microsoft System Center Building a Virtualized Network Solution. Indianapolis, IN: Sams Publishing.
Chaskin, R.J., 2001. Organizational infrastructure and community capacity: The role of broker organizations. In S.W. Hartwell and R.K. Schutt eds.,, The organizational response to social problems (pp. 143-166). Bradford, UK: Emerald Group Publishing Limited.
Davenport, T.H. and Dyché, J., 2013. Big data in big companies. International Institute for Analytics, May.
Demchenko, Y., Ngo, C. and Membrey, P., 2013. Architecture framework and components for the big data ecosystem. Journal of System and Network Engineering, pp.1-31.
Edwards, W.K., Grinter, R.E., Mahajan, R. and Wetherall, D., 2011. Advancing the state of home networking. Communications of the ACM, 54(6), pp. 62-71.
Fairhurst, P., 2014. Big data and HR analytics. IES Perspect. HR, 7, p.2014.
Fuller, M. 2015. Big data: New science, new challenges, new dialogical opportunities. Zygon®, 50(3), 569-582.
Jewell, D., et al., 2014. Performance and capacity implications for big data. New York: IBM Redbooks.
Minelli, M., Chambers, M. and Dhiraj, A., 2012. Big data, big analytics: emerging business intelligence and analytic trends for today’s businesses. Hoboken, NJ: John Wiley & Sons.
Mohanty, S., Jagadeesh, M. and Srivatsa, H., 2013. Big Data imperatives: enterprise Big Data warehouse, BI implementations and analytics. New York: Apress.
Ohlhorst, F. 2013. Big data analytics: Turning big data into big money. Hoboken, NJ: Wiley.
Pearson, T. and Wegener, R., 2013. Big data: the organizational challenge. Bain Co.
Schmarzo, B., 2013. Big Data: Understanding how data powers big business. Hoboken, NJ: John Wiley & Sons.
Thomas, R. and McSharry, P., 2015. Big data revolution: What farmers, doctors and insurance agents teach us about discovering big data patterns. Hoboken, NJ: Wiley.