assignment 4

Discussion 1

The information collected by the organization over a period of time can be effectively used to identify specific identification of aspects that can deliver better value to the understandings that can be created and used for effective delivery of activities to improve efficiency and identify new patterns and their contributing variables to be identified to develop a better understanding of the patterns identified.

Data analysis is a process of extracting the information from various sources, restructuring the data, transforming the information to create better datasets that can be used for analysis, model the data for specific usage, develop visualization capabilities to build a better understanding of the information in a systematic way that can be used to create a better association of information variables to identify patterns and derive conclusions on several aspects, help improve the understanding of patterns and develop possibilities of predicting the future recurrence of the patterns (Agarwal & Tayal, 2009).

Data Mining is of a subset of data analysis process wherein their meaning of the information with the minute details can be identified through the deeper exploration of the same information conducted to identify all the small details and develop a better understanding of the patterns, identify hidden patterns in the information with systematic approaches to explore the information accurately, develop an appropriate process for working with a huge amount of information consistently with a higher speed, used to develop machine learning capabilities where the inputs are consistently analyzed for creating better meaning that can be used to transform decision-making process with the on minute details of the information analyzed, compared with predefined conditions and identify the resolutions that are very likely to be implemented to implement automation in the process of request and response for specific use and industrial coverage of activities (EMC, 2015).

Discussion 2

With the volume of data produced yearly rapidly growing, so as the concepts and approaches to make sure the data is actually valuable and actionable. Data mining and data analytics are two of those new and trendy techniques. It is important to say that they do have many aspects in common, and some even consider these approaches to data as synonyms. However, experts suggest that there is a significant difference in the core of both tools. Bresnick (2017) explains that data mining essentially means finding valuable information in the large volume of data and recognizing the basic interconnections. Data analytics, on the other hand, is a broader concept and works on the ground of the information discovered during the data mining process. Data analytics is aimed to find and interpret complex interconnections between the known data (Bresnick, 2017).

Tarmizi et al. (2017) demonstrate in their study how both data mining and data analytics could be applied in a field of higher education in Malaysia to improve the education system and increase the number of graduates. By practicing data mining or Knowledge Discovery in Databases (KDD) and its tools, the researchers are able to identify particular socioeconomic trends on student attrition. Following that, through descriptive and prescriptive analytics, the researches could create future scenarios and define the current state of the education industry in the country (Tarmizi et al.,2017). This information is particularly valuable as it allows to take actions and introduce changes based on the actual data.

Both concepts are fascinating to me, and from a Business Analyst point of view, data analytics represents great opportunities in my future career. Data-driven decisions, in my opinion, are the future of the businesses. From project initiation to implementation, data analytics could bring more clarity, reduce misunderstanding, and essentially create an efficient process.

Please make sure two response posts to given discussions substantive. A substantive post will do at least TWO of the following:

1.Ask an interesting, thoughtful question pertaining to the topic

2.Answer a question (in detail) posted by another student or the instructor

3.Provide extensive additional information on the topic

4.Explain, define, or analyze the topic in detail

5.Share an applicable personal experience

6.Provide an outside source (for example, an article from the UC Library) that applies to the topic,

along with additional information about the topic or the source (please cite properly in APA)

7.Make an argument concerning the topic.

8.At least one scholarly source should be used in the initial discussion thread. Be sure to use information from your readings and other sources from the UC Library. Use proper citations and references in your post.