Analyzing and Visualing Data
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Data Examination
Data examination is a process, in which, you would examine and understand the data that one has gathered. It is really important to know that when working with information, you should study the data before making any further decisions. Data investigation is to confirm our outcomes whether it is substantial, reproducible and verifiable. Data examination is also a procedure of investigating, purging, changing, and demonstrating information with the objective of finding valuable data, illuminating conclusions, and supporting basic leadership (Kirk; 2016) .Data examination has various aspects and methodologies, incorporating assorted systems under an assortment of names, while being utilized as a part of various business, science, and sociology spaces. There are cases, for example at leading information organizations, for example, Amazon and Google, where information is utilized as a part in which examined data, comes about themselves to settle on the choices, for instance with respect to proposal engines , PageRank, and request anticipating frameworks.So, it is important to examine data before making decisions regarding business (Rosenthal, Robert; Rosnow, Ralph L; 1991).
References:-
Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design (p. 50). SAGE Publications.
Rosenthal, R., & Rosnow, R. L. (1991). Essentials of behavioral research: Methods and data analysis. Boston, MA.
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Student post 2
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Data exploration: Using exploratory analysis and research techniques to learn
Data exploration is the first step in data analysis and typically involves summarizing the main characteristics of a dataset. It is about describing the data by means of statistical and visualization techniques. We explore data to bring important aspects of that data into focus for further analysis. Before a formal data analysis can be conducted, the analyst must know how many cases are in the dataset, what variables are included, how many missing observations there are and what general hypotheses the data is likely to support. An initial exploration of the dataset helps answer these questions by familiarizing analysts about the data with which they are working (Rouse, 2015). Analysts commonly use data visualization software for data exploration because it allows users to quickly and simply view most of the relevant features of their dataset(Kirk, 2016).
References:
Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. Thousand Oaks, CA: Sage Publications, Ltd.
Rouse, M. (2015, May 19). Data Exploration. Retrieved from
https://searchbusinessanalytics.techtarget.com/definition/data-exploration
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