Chat with us, powered by LiveChat Question:? peer response. At least 250 words. use 2 citations, READ entire instructions The response should consist of no le | Wridemy

Question:? peer response. At least 250 words. use 2 citations, READ entire instructions The response should consist of no le

 

peer response. At least 250 words. use 2 citations, READ entire instructions

The response should consist of no less than 250 words and should incorporate at least one outside from a library database search, APA formatted reference at the end of the post. Your responses should ask a pertinent question, contribute significantly to your classmate’s posting and foster further discussion in order to receive the full points per response

To make a knowledgeable posting, it would be a good idea to review the supplemental material before writing your response I have attached the assignment for you to read:

Managing change in practice 4.1: Mick Yates: The implications of big data

Hayes, J. (2014). Theory and Practice of Change Management. S.L.: Palgrave Macmillan.

This is the discussion I want you to respond to:

Big data is described as a massive volume of both structured and unstructured data that is too large for traditional databases and software to process (Galetto, 2017). Essentially the data is too big and sometimes too fast moving for the organizations current processing capacity. Big data analytics offers organizations many opportunities to enhance company value and productivity (The Implications of Big Data Analytics on Business Intelligence). Yates makes a known that big data has changed the way an enterprise makes decisions, how departments talk to each other and how business interact with their customers. There both positive and negative aspects to big data, but this is something that can assist companies in their efforts to improve operations which can ultimately lead to them making faster more intelligent/effective business decisions, and assist in increasing revenues (Galetto, 2017). Companies struggle at times to manage large amounts of data as they are not always equipped with the right tools and resources that are able to analyze these massive datasets (Galetto, 2017). Over the last few years there has been a big boom in big data because of the growth in the social media sector. Companies now have an even larger amount of data and it is up to them to harness this information and extract what is most useful for their organization. This boom is what has led many companies to big data management solutions to solve issues and capitalize on all the unstructured data (Galetto, 2017). It may seem daunting at times but if utilized, big data analytics and big data management solutions can help organizations set themselves up for future success for a lifetime.

As mentioned above, there are many benefits to utilizing big data management solutions and turning to big data analytics. Some of these benefits include, but are not limited to (Galetto, 2017):

-Identifying the root cause of issues in real time

– Fully understanding the potential of data-driven marketing.

– Generating customer offers based on their trends.

– Reevaluating risk portfolios quickly.

– Having the ability to aggregate a variety of data from various sauces in real time.

– Helps eliminate data silos.

Implications of big data

Although big data can be very beneficial to companies and help them gain a competitive edge in their respective markets, there are some challenges and implications involved. One of the biggest challenges is the requirement of infrastructure as this is very expensive. Companies lack the scalable real-time analytics capabilities, the availability network resources and the lack of big data sources to name a few. There are also major concerns in regards to data privacy and dealing with information security regulations and not to mention the sheer expense associate with big data management (The Implications of Big Data Analytics on Business Intelligence).

Yates explains two important strategies associated with big data, customer centricity and innovation networks. Customer centricity which allows you to learn about your customers but customers also learn more about the business. The implication here is that the balance of power has shifted to where the company used to have all the information and now the customers have all the information. The second strategy is innovation networks. With the amount of information and ideas around the world is now brought together by networks that are very complex and this is fueled by big data. However, these strategies create difficulties in embracing big data for many in the organization. People may resist the change with big data due to its complexity but this where management plays a key role in helping team members across the organization prepare for the change (Yates, 2014).

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