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How Can the use of Big Data Analytics Help an Organization Adapt to a Changing Environment?:

How Can the use of Big Data Analytics Help an Organization Adapt to a Changing Environment? Emily Grimm

A Competitive Edge:

A Competitive Edge The environment is constantly changing and organizations must find ways to adapt in order to survive (Daft, 2015). In order to stay ahead of competition, organizations must maintain a competitive edge. Many organizations are pursuing big data and advanced analytics in order to keep up with environmental changes.

Big Data Analytics and the Open Systems Model:

Big Data Analytics and the Open Systems Model The way big data analytics works can be represented by the Open Systems Model. Data is both the original input, and the feedback.

What is Big Data?:

What is Big Data? Big Data is defined as the increasing ability in relation to technology to gather, combine and process data of increasing size, speed, and variety ( Angellutti , 2014) Big data sets are “large, diverse, complex, longitudinal and/or distributed datasets generated from instruments, sensors, internet transactions, email, video, click streams and/or all other digital sources available today and in the future” ( Angellutti , 2014) Daft (2015) defines big data analytics as “technologies, skills, and processes for searching and examining massive, complex sets of data that traditional data processing applications cannot handle to uncover hidden patterns and correlations.”

Issues with Big Data :

Issues with Big Data I nvestments in big data analytics are lower than they should be, possibly because companies are hesitant to invest on a large scale because organizations are still skeptical about the magnitude and timing of the returns on their investments ( ( Bughin , 2016). A nother substantial challenge that has been recognized by many sources is the issue of privacy in big data. The process of de-identification is supposed to pull pieces of data apart so that it can no longer be linked to an individual, however the effectiveness of this process is limited. There are apparent methods of re-identification that present the risk of compromising confidentiality. ( Agnellutti , 2014).

Conclusion:

Conclusion Although there are some complications involving the use of big data, the benefits of investing in big data analytics seem to outweigh the risks. T he use of analytics is becoming increasingly necessary for an organization to keep up with competition. Big data analytics helps organizations to be continuously aware of their environment, and make necessary changes in order to adapt.

OD Tool: Strategic Questions. :

OD Tool: Strategic Questions. This tool involves analyzing patterns in data and finding trends over time. Some questions asked considered in these categories include: What data has been gathered? What data should be gathered? Are we utilizing all appropriate data sources? Is the data we are gathering complete? Is there a trend? What is the meaning of the trend? How can we use this to anticipate the future? Source: Tools for Strategic Planning. ( n.d. ). Retrieved February 26, 2017, from http://www.tasha-harmon.com/pdf/Strategic_Questions_Handout.pdf

Connection to my career:

Connection to my career Upon graduating, I plan to pursue a career in Big Data Analytics. It’s important to understand the benefits of data analytics, but also to be aware of the potential obstacles. As someone who will be looking for a job in this field, I’ve learned through my research the importance of choosing a company who is not afraid to invest adequately in this department. There is a big future for big data and researching this has only strengthened my feelings about the pursuit of a career in this field.

References:

References Agnellutti , C (2014). Big Data : An Exploration of Opportunities, Values, and Privacy Issues New York: Nova Science Publishers, Inc  .   Baniasad , R. (2012, July 22).  You need strategy for Your Organization Prof. Michael Porter.  Retrieved from https:// youtu.be /DViVtgD0xwE   Bughin , J. (2016). BIG DATA: GETTING A BETTER READ ON PERFORMANCE. Mckinsey Quarterly, (1), 8-11.   Daft, R. (2015). Organization Theory and Design (12th Ed.).  Boston, MA: Cengage Learning. From Exhibit 4.7   Manyika , J., Chui, M., Brown, B., Bughin , J., Dobbs, R., Roxburgh , C., Byers, A., Big data: The next frontier for innovation, competition, and productivity   Metcalf, J. (2016). Big Data Analytics and Revision of the Common Rule.  Communications of the ACM. 59 (7).   indent

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