Big Data

Problems and Opportunities created by having too much data, and what to do about them There is rarely an instance of business that you can encounter that does not involve the processing of data on information systems these days. Businesses and organizations use information systems in a majority of their functions, and as a result, are creating mass amounts of data. Because data is so crucial to business operations, it is being gathered, stored, and utilized in exponential amounts compared to the previous decade.
These data stores can be extremely valuable, but can also be equally as expensive, creating both problems and opportunities for those data owners. I believe that having vast amounts of data is more beneficial than it is harmful. Data is used in many ways and for many things. The benefits of having this data are evident in companies such as Google, Facebook, and even with the federal government. Their success in business comes from having the capability to store and access great amounts of data quickly and efficiently. This comes from the right combination of hardware, process, governance, and application.
Knowing what data to gather, how to utilize it, and having the equipment and technology to utilize it appropriately puts these businesses and others like them, ahead of the game. Companies that cannot gather the data and handle it appropriately, tend to fall by the wayside in this information and information technology driven world we live in today. Having vast stores of data can be overwhelming when it isn’t managed and utilized appropriately. However, when it is, that data can enable the owner to have the advantage over its competitors.

Data is used for market analysis, streamlining business processes and functions, and much more. If you know what data is valuable, and how to utilize it, the more data you have the more of an advantage you have as well. As George Shen stated in his article on business intelligence and business analytics, “the “big data” era introduced an astronomical amount of data, the wealth of information that companies can potentially unlock and the depth and breadth in which organizations can perform analysis, enable technology and apply analytical methods of the 21st century” (Shen, 2011).
It’s not a race to see who can gather the most data, but it is a race to see who can gather the most useful data, and use it the best. As Shen pointed out, this data presented opportunities to companies that would otherwise be impossible for them. Simply the amount of knowledge that can be gathered about their consumers in a short amount of time would have taken so long to gather that the analysis would no longer be valid, if it was possible to gather that information at all. Their shopping habits, their entertainment interest, and so much more, all gathered within minutes of them utilizing a search engine.
Not all data is equally as valuable, so making the right decisions as to what data to keep and what data to purge through prioritization is paramount. Gathering, storing, and utilizing data can be quite expensive, particularly with very large amounts of data. That data must also be secured, which can also be costly. There are several different solutions for data storage, and those solutions can either be in house or cloud storage. Choosing the right data storage and processing solutions is just as important as the data itself.
While cloud solutions tend to cost less, they are also less secure and less robust than available in house solutions. “This is why the primary hope for securely storing critical information should and must lie with technologies that increase capacity and access times without requiring that the data leave the enterprise”; also suggesting that prioritizing data, using a cloud solution for less valuable data, might be beneficial when the decisions are made wise about the prioritization” (Trembly, 2010). With the right prioritization, data that is stored, processed, and secured appropriately can be invaluable to a company and its success.
The more of this valuable data there is, the better a business analysis can be. Although these mass amounts of data can be beneficial, it can also be very damaging to business. The hardware and manpower required to manage large amounts of data is not cheap. A company can easily find themselves in a situation where they are paying to store data that is not offering any benefit to business or to business strategy. Those situations can easily consume a huge portion of an IT department’s budget, and leave gaps in other places where the money could be more wisely spent, such as security.
Not only is it expensive to store and manage mass amounts of data, but storing the wrong data can also slow other processes down. Applications and processes that require the use of stored data have a slower response time because it takes longer to process through data that is not relevant. Time is a critical factor in IT, particularly when it comes to maintaining a competitive advantage. Too much data can also cause issues with the reports being generated from the data stores. “The rich lode of Web data, experts warn, has its perils. Its sheer volume can easily overwhelm statistical models.
Statisticians also caution that strong correlations of data do not necessarily prove a cause-and-effect link” (Lohr, 2009). If the wrong or irrelevant data is being reported, it can skew the information provided in reports, and in turn cause decisions to be made based on inaccurate information. Many people view cloud computing as a way to minimize the issues that come with big data. Cloud computing can offer other benefits such as web based access to the data by customers through application, making the process of recalling information from databases storing larger amounts of data more expedient.
Unfortunately, even cloud computing, at a reduced cost than in house data storage, comes with its own issues when it comes to big data. “Yet despite advances in capacity and access speed, the flood of data today threatens to overwhelm our ability to control it. And the more we trust the Internet to help with storage needs, the less control we have and the more risk we take” (Trembly, 2010). When relying on cloud computing to resolve big data issues, the security of the data is then also reliant upon the service provider of the cloud.
With data being so valuable to business, losing control due to overwhelming quantities, or handing over control to an outside storage and service provider can have some terrible consequences. Even though there are solutions to dealing with the issues related to big data, they come with inherent risk that may simply not be worth the possible cost. Regardless of the possible negatives associated with big data, it is undeniable that the benefits of it are tremendous when managed appropriately. Our accessibility to data has increased exponentially, and with it, so have the opportunities associated with it. It is the size of the data sets on the Web that opens new worlds of discovery” (Lohr, 2009). Businesses can gather and access data that can mean the difference between success and failure, between remaining competitive or becoming irrelevant. The key is to manage big data effectively, alleviating excesses, and utilizing it appropriately. Big data is a benefit, so long as it can be managed and not be overwhelming. Works Cited Shen, G. (2011). Unplugged: the disconnect of intelligence and analytics. Information Management, 21(1), 14.
Retrieved on November 28, 2012, from http://www. information-management. com/issues/21_1/unplugged-10019478-1. html Trembly, A. C. (2010). The problem with data storage: way too much information. Information Management. Retrieved on November 28, 2012, from http://www. information-management. com/news/data_storage-10016887-1. html Lohr, S. (2009). For today’s graduate, just one word: statistics. NYTimes. com. Retrieved on November 28, 2012, from http://www. nytimes. com/2009/08/06/technology/06stats. html? _r=2;em

The post Big Data appeared first on Essay Bishops.

Order a unique copy of this paper
(550 words)

Approximate price: $22

Basic Guarantees
  • Free title page and bibliography
  • Free unlimited revisions
  • Plagiarism-free papers
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Progressive delivery
  • Plagiarism report
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double or single line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Writing quality papers is a TOP priority. One expert takes one order at a time.
The service package includes topic brainstorm, research, drafting, proofreading, plagiarism check, citation formatting, and revisions.

Money-back guarantee

We appreciate how valuable your time is. Hence, we make sure all custom papers are 100% original and delivered within the agreed time frame

Read more

Zero-plagiarism guarantee

Each paper is written from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

We see it as our duty to follow all instruction the client provides. If you feel the completed paper does not meet your exact requirements, we will revise the paper if you let us know about the problem within 14 business days from the date of delivery.

Read more

Privacy policy

Your email is safe, we use your personal data for legal purposes only and in accordance with personal data protection law. Your payment details are also secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

You can easily contact us with any question or issues you need to be addressed. Also, you have the opportunity to communicate directly with assigned writer, e-mail us, submit revision requests, chat with us online, or call our toll-free on our site. We are always available to our customers.

Read more

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
The price is based on these factors:
Academic level
Number of pages