Key Functions in Organizational Leadership

Key Functions in Organizational Leadership Essay

Instructions/Descriptions

Key Functions in Organizational Leadership Essay

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Discussion Response

Respond to listed statement in at least 170 words. Do you agree or disagree with the statement.

Criminal Justice Leadership in any organization is related to the outmost success that organization can expect to see. Leadership in any organization is certainly no exception. The main strategy is having strong leaders in place really promotes organization, management, productivity, motivation and even creativity in a criminal justice setting.

Leadership requires that a person have a strong desire to be an influential part of the organization and want to play a key role in moving towards a common goal.  Leaders are primarily concerned with motivating and inspiring their followers to remain productive and to maintain the drive and ability to reach organization goals (Study Moose, 2016). The role of a leader in a criminal justice organization should not be under appreciated.

A leader plays has an immensely influential role within the organization. First, leaders must have a strong working knowledge in the assignment they wish to lead. Leaders must realize their strengths and weakness in order to develop their own style of leadership. Due to the fact that people are motivated by different things, a leader must realize what motivates each subordinate individually (Study Moose, 2016).

The most accomplished leaders comprehend the necessity of setting the tone for employees to be successful.  A good leader wants their employees to enjoy coming to work and they will take the necessary action to create this atmosphere.  This is done by establishing mechanisms to stay informed with what their employees are doing.

Leaders should embrace every opportunity to recognize their employees for positive performance and often it may be a simple “thank you.”  Creating an environment to help your officers feel they are a part of a team and a family will encourage them to not want to let down their team members (Weisskopf, 2012).  (Katz, 2020)

The role of the leadership in criminal justice organization in the motivation of their team members is to make their team members feel wanted. The leader should ensure that they have an open-door policy with their team members, so that if an employee is ever feeling uncomfortable, unappreciated, underpaid and overworked, they can express themselves.

It is the job of the leader to ask the employee, “What can I do for you? What would you like to see change?’ Ensure that the employee recognizes that they matter, too and the organization could not run without them. Think of an organization as a human body. The employer is the head, but the employees are the neck. Both need each other and the head will not and cannot move without the neck.

Identify the challenges associated with the use of Big Data Analytics in the e-Healthcare industry

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Data Gathering

Big data is challenging to deal with due to the challenges in collection, representation, and transmission. Big data presents with complex structures and various dimensions that make it challenging to represent (Dash, et al., 2019). Also, transmitting large volumes of data to the storage infrastructures is inefficient because of high bandwidth consumptions and energy efficiency associated with big data, making the data gathering difficult.

Storage and Integration

The storage of large volumes of data poses a primary challenge in organizations, where the onsite server’s maintenance is difficult and expensive. The organization is required to implement cloud-based storage following the decreased cost and increased reliability of cloud storage.

However, it may not be a flexible and workable approach in some organizations. Also, the integration of big data is challenging due to the variety of data; important information is obtained from various sources, including enterprise applications, social media, systems of email, and documents created by employees, among other relevant sources (Dash, et al., 2019).

Data Analysis

Increased data growth has negative implications when it comes to analyzing all the information. Considerably, the information in the digital universe in IT systems is doubling within two years, making it difficult to explain the data. For successful big data analytics, the organizations must overcome all the other challenges associated with big data.

However, dealing with such problems is costly to the organization in terms of time, finance, and commitments (Dash, et al., 2019). Believably, implementing the big data analytic in healthcare settings reduces costs by about 25% per year.

Knowledge Discovery and Information Interpretation

The big data in health care industries come with possession of massive sets of data originating from heterogeneous sources. Unfortunately, conventional analytics hardly manage the vast volumes of data. Therefore, designing a high-performance platform for computing that can handle big data analytics is a challenge. The big data, as a result, remains unhelpful since no information is translated, not knowledge discovered.

Reference

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 54.

By definition, Big Data analytics is the use of advanced tools to collect, clean, store, and retrieve data to derive insights from large volumes of data that help to support healthcare professionals to make better and informed decisions. The ultimate aim here is to draw correlations and conclusions from data that were previously unmanageable and incomprehensible when using traditional tools like spreadsheets or file storage format.

But, despite the enormous benefits of Big Data analytics and its associate platforms, the road towards drawing meaningful insights from Big Data Analytics is filled with some challenges. As a consequence, the complexity of Big Data requires a close look at the methods and approaches when it comes to collecting, storing, analyzing, visualizing, and presenting the data to stakeholders. In this regard, data gathering is one of the typical challenges that face health organizations.

Usually, capturing quality data that is clean, consistent, accurate, and formatted correctly is an ever-ending process for health organizations. In some cases, clinical data are captured in various systems and often not well integrated (Adibuzzaman et al., 2017). Similarly, poor collection of data may lead to poor EHR usability, hinder workflows, and eventually contribute to quality issues throughout the life cycle of data.

A typical example of constraints that associate with gathering Big Data include missing data attributes or incorrect data records, ambiguous, puzzling, or contradictory variables (Ayani et al., 2019).

The second challenge entails the storage and integration of biomedical and healthcare data. As the volume of Big Data continues to pile up at an exponential rate, the costs of storage of Electronic Health Record (EHR) data also continue to increase (McDonald, 2016).

For example, an on-site server network or data center can be expensive to manage and maintain. This accumulation of data over time may cause the central data storage to serve as data silos, thus affecting the interoperability of data across the healthcare organization while preventing analytics tools from accessing and retrieving the primary database.

The third challenge is that the voluminous and highly heterogeneous nature of big data in healthcare may be rendered relatively less informative, especially when using a low manual intervention approach to process and analyzed the data. Therefore, common platforms such as Hadoop and Apache Spark, as well as advanced algorithms of Artificial Intelligence (AI), Machine learning is required to assist in the analysis of Big Data analysis in healthcare (Dash et al., 2019).

In regard to knowledge discovery in healthcare, however, Big Data analytics plays a major role in managing and finding potentially useful patterns of information. Data mining techniques such as classification can be used in knowledge discovery to uncover the hidden patterns and relationships that buried within the Big Data.

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However, the success of such mining technique sometimes faces many challenges (Baitharu & Pani, 2016). To name a few, developing a unified framework of data mining in healthcare require algorithms with high accuracy. In part, this is because knowledge discovery in healthcare deals with diverse and complex issues of life or death. Plus, knowledge in healthcare discipline keeps changing continuously, which means previous research knowledge experience must be taken into account when searching for new Knowledge discovery in databases (KDD).

References:

Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2017). Big data in healthcare–the promises, challenges and opportunities from a research perspective: A case study with a model database. In AMIA Annual Symposium Proceedings (Vol. 2017, p. 384). American Medical Informatics Association.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977694/

Ayani, S., Moulaei, K., Khanehsari, S. D., Jahanbakhsh, M., & Sadeghi, F. (2019). A Systematic Review of big data potential to make synergies between sciences for achieving sustainable health: Challenges and solutions. Applied Medical Informatics., 41(2), 53-64.

https://ami.info.umfcluj.ro/index.php/AMI/article/view/642/638

McDonald, C. (2016). The motivation for big data

https://mapr.com/blog/reduce-costs-and-improve-health-care-with-big-data/

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data, 6(1), 54.

https://link.springer.com/article/10.1186/s40537-019-0217-0

Baitharu, T. R., & Pani, S. K. (2016). Analysis of data mining techniques for healthcare decision support system using liver disorder dataset. Procedia Computer Science, 85, 862-870.

https://www.sciencedirect.com/science/article/pii/S1877050916306263

Key Functions in Organizational Leadership Essay

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