NURS 655 Data Mining And Data Visualization Essay
NURS 655 Data Mining And Data Visualization Essay
Write a four- to
five-page paper that demonstrates comprehension of data mining and data
following using a data set from https://www.healthdata.gov/ Click for more options
Clean and prepare the data.
Use any data mining model to extract meaningful data.
Create two data visualizations in Tableau that show data in
a meaningful way without information overload.
Explain your data set and describe your data mining model
and data visualization technique (two-page maximum).
Submit your data files, links to your visualizations, and
your written assignment.
Include the URL of the data set that you downloaded.
Examples of scholarly sources include professional journal
articles and books obtained from library databases, national guidelines, and
informatics organizations, published within the last five years
Key Differences Between Data Mining and Data Visualization
Following are the key differences between Data Mining and Data Visualization:
- Data Mining is the process of sorting out some large data sets and extracting some data out of them and extracting patterns out of the extracted data whereas Data Visualization is the process of visualizing or displaying the data extracted in the form of different graphical or visual formats such as statistical representations, pie charts, bar graphs, graphical images etc.
- Data Mining processes include sequences analysis, classifications, path analysis, clustering and forecasting whereas In Data Visualization contains processing, analyzing, communicating the data etc.
- In Data Mining, the data will be displayed automatically in search process which will be displayed by the system analysis itself whereas Data Visualization, gives a clear view of the data and will be easy for the human brain to remember and memorize large chunks of data at a single glance.
- In Data Mining, there are four stages which are Data Sources, Data gathering or data exploring, data modeling and deploying the data models whereas In Data Visualization has seven stages which are acquiring process, parsing, filtering, mining, representing, refining and interacting.
- Data Mining is a group of different activities to extract different patterns out of the large data sets in which data sets will be retrieved from different data sources whereas Data Visualization is a process of converting numerical data into graphical images like meaningful 3D pictures which will be used to analyze complex data easily.
- The applications of Data Mining include Customer Relationship Management which is a software application that provides advantages to data mining whereas the applications of Data Visualization include sonar measurements, satellite photos, computer simulations and surveys etc.
- The different techniques available in Data Mining are Classification, Cluster, Sequence, Association etc. Data Visualization has originated from statistics and sciences which give clear visualization at a glance which means a picture gives 100 words at its sight.
- In Data Mining, classification is the process of identifying the rule of the data whether it belongs to a particular class of data or not and its’ sub-processes include building a data model and predicting the classifications whereas In Data Visualization the main application include geographical information systems where the important geographical information can be represented as visual images that represent complex information as simple as possible.
- Data mining technologies also include neural networks, statistical analysis, decision trees, genetic algorithms, fuzzy logic, text mining, web mining etc., whereas the Data Visualization has different applications such as retail, government, medicine and healthcare, transportation, telecommunication, insurance, capital markets and asset management.
- The limitations in Data Mining are such as even it is being new technology but it is still underdeveloped one because of many companies using legacy systems and also the existing systems are not data warehouse friendly Data Visualization has significant disadvantages in its tools are such as it shows different visuals rather than explaining, no guidelines, different users with multiple insights and also provides poor security.
- Data Mining is an analytical process that identifies different patterns from the data sets which can help in dealing with the flood of information and Data Visualization provides a lot of visualization techniques which have been developed for the past decades those support the exploration of large data sets.
- The benefit of Data Mining is that the relationship will be unhidden among different data sets and variables whereas Data Visualization defines as it is the visual object by representing the data in the form of graphs and charts.
Data Mining and Data Visualization Comparison Table
Below is the comparison table between Data Mining and Data Visualization.
|Data Mining||Data Visualization|
|Definition||Searches and produces a suitable result from large data chunks||Gives a simple overview of complex data|
|Preference||This has different applications and preferred for web search engines||Preferred for data forecasting and predictions|
|Area||Comes under data science||Comes under the area of data science|
|Platform||Operated with web software systems or applications||Supports and works better in complex data analyses and applications|
|Generality||New technology but underdeveloped||More useful in real time data forecasting|
|Algorithm||Many algorithms exist in using data mining||No need of using any algorithms|
|Integration||Runs on any web-enabled platform or with any applications||Irrespective of hardware or software, it provides visual information|