Explain how you think data integration is important.

Explain how you think data integration is important.

Paper instructions: 

Data integration can be a very complex process because it involves the communication of various technologies, platforms, and networks. It can become particularly complex in organizations where sensitive or personal information is used, such as healthcare. Explain how you think data integration is important. Do you see it as a critical element in data analytics? Provide an example to support your thoughts.

Data integration is the consolidation of data from diverse sources into one dataset to

make it easy for users to access it for various purposes. Integrating data is essential in multiple

fields, including healthcare. Although data integration is a complex process, it is beneficial to

healthcare providers and their patients (Raghupathi & Raghupathi, 2014). For example,

clinicians can conduct searches across different healthcare systems to get all the patient

information, including medical history, allergies, and medications used. The ability to easily

access such information can play a crucial role in saving patients’ lives when quick decisions

need to be made by healthcare providers such as paramedics. They can immediately share this

information with the emergency department to prepare the receiving hospital well to provide

appropriate care to the patient.

Data analytics tools enable the integration of clinical data to generate new business

insights that help healthcare organizations serve their patients’ needs, leading to improved

quality of care and better financial performance (Wang, Kung, & Byrd, 2018). Data integration is

a critical part of data analytics as it allows analytics tools to promptly generate useful and

actionable information. Data gathered from different sources is integrated, and associations,

trends, and patterns identified through data analytics to lower costs, improve care, and save

patients’ lives (Raghupathi & Raghupathi, 2014). Integrating, synthesizing, and analyzing data

helps healthcare providers develop more insightful and thorough treatments and diagnoses,

leading to better care at lower costs.


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