Data Analysis

What are the important considerations for managers preparing to undertake big data analytics projects? Base on the case (Home depot case ) and the report uploaded write an update report. The report should contain your own thoughts. You are free to use outside resources. If you use external resources, you must cite them. Ps: no copy and paste!!!

For your final project in data analysis, you will use the GSS Data Explorer to analyze a set of variables of your choice and write up a brief research report. You will use the same methods you’ve used in previous GSS assignments to do this. To get started, follow these steps: 1. Once you’ve signed into GSS Data Explorer, choose to Create New Project and name it Final Project. 2. Invite me to your Final Project by choosing “Invite Others” and entering my email [email protected] 3. Starting from in your Final Project, click on User Searches to search through the GSS variables, and choose a set of variables that you’d like to analyze. You can do this using keyword or the modules or subjects as we’ve done previously.  This time, you can use your own interests to choose variables.  You will be performing both univariate (descriptives) and bivariate (associations) analyses, so keep this in mind when you choose your variables. You may want to propose a hypothesis that you can test, or you may want to look at the relationships between variables without predicting what you expect to find. You should choose several variables (at least four.) You may choose to look at the relationships between several possible independent variables on a single outcome (dependent variable), a single independent variable on several outcomes (dependent variables), or the relationships between several sets of variables. Once you’ve selected your variables, move them into your variable cart for the final project. Choose ONE YEAR to conduct all your analyses. (Make sure that it is a year in which all of your variables were measured.) 4.  Run the frequencies on all of your selected variables. Construct and percentage of tables to report your results. GSS Data Explorer doesn’t run measures of center and measures of dispersion, so instead of running them, simply write a note of which analyses you would run for both central tendency and dispersion (remember that these are chosen based on the level of measurement of each variable.) 5. From within your Final Project, run the bivariate analyses appropriate to your data set (either cross-tabulations or correlations.)  Run the appropriate analysis for each of your pairs of variables. If you mess up on analysis, you can delete that one and start over. Run all the appropriate bivariate analyses for all of your variable pairs (so at least two).  6. Write a brief research report in which you identify which variables you analyzed and report the results of your descriptive and inferential analysis. This should include the percentage frequency tables for each of your variables as well as a discussion of the findings of your cross-tabulations and/or correlations. Did you find any statistically significant relationships?  If you proposed a hypothesis, did you find the predicted relationship?  You do not need to reproduce the results of the bivariate analyses in your report because I can see them in the Final Project, although you should include the findings of each analysis in the report. You should write something like “A cross-tabulation analysis of Variable X and Variable Y resulted in a Chi-Square p-value of __: no significant relationship was found.” 7. Submit the research report here.  Leave your analyses and variable searches in your Final Project in GSS so I can review them.

Evaluate the extent to which big data analytics has contributed to an increase in online sales for e-commerce companies. What are the most important considerations for such companies before the adoption of this approach? I will add the file. Evaluate the extent to which big data analytics has contributed to an increase in online sales for e-commerce companies. What are the most important considerations for such companies before the adoption of this approach? (this is my title) , This is my final writing exam for my English school language class. I added a file . the document in pdf format is a requirement of my writing task 3. the word document is my feedback on writing task 2, writing task 3 according to the teacher’s comments on task 2. Be sure to check out the documentation.

In Units Three, Four, and Five, students used data charts that displayed several columns of information, to include ‘Valid Percent’ and ‘Cumulative Percent.’ For this discussion post, students will explain the difference between the two types of percents. Why are these statistical elements important to the data presented? Explain your rationale with a minimum of 250 words, supporting your discussion with two scholarly references and in-text citations.  Respond to this question with a minimum of 250 words and two scholarly sources from the Library For more information on Valid Percent read this: https://en.wikipedia.org/w/index.php?search=Valid+Percent&title=Special:Search&go=Go&ns0=1

Technology and Enterprise Resource Planning As an IT manager, discuss how your company will use Enterprise Resource Planning (ERP) to integrate the various functions of an entity. What are the advantages of using ERP? In your discussion, please be sure to provide a substantive explanation of what ERP is and give example(s) of ERP. Use APA throughout. Your main discussion should be at least 300 words or more. For more information read this:

 Discuss a Business Intelligence Tool. Provide examples. For more information read this:https://en.wikipedia.org/wiki/Business_intelligence

Discuss the importance of regular expressions in data analytics. As part of your discussion please include a specific use case for which a regular expression could be used with a dataset.  Also, discuss the differences between the types of regular expressions. (2-3 paragraphs) Choose two types of regular expressions… For example, [brackets] (Matches the enclosed characters in any order anywhere in a string) and * wildcards (Matches the preceding character 0 or more times) and discuss the differences between the two.  Please be sure to include two or three differences for each. Include how they help manipulate data (1-2 paragraphs). For more information read this: https://en.wikipedia.org/wiki/Regular_expression

In the Student Assignment File Week 1 tab, complete the problems, and submit your work in an Excel document. See Where Is Help Button in Microsoft Excel 2007, 2010, 2013 and 2016 (Links to an external site.), Descriptive Statistics (Links to an external site.), Load the Analysis ToolPak (Links to an external site.), and Use the Analysis ToolPak to Perform Complex Data Analysis (Links to an external site.) for more information on how to use the required technologies for the course. Be sure to show all of your work and clearly label all calculations.https://www.excel-easy.com/examples/descriptive-statistics.html. For more information read this:https://en.wikipedia.org/wiki/Problem_set

General Requirements: Use the following information to ensure successful completion of the assignment: Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center. This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance. Directions: Write a paper (1,500-1,750 words, not including title page and references) that addresses the following. The paper should begin with an executive summary of no more than one page. Structure your paper such that individual section titles are created to address each of the following topics: Introduction Analytics Methods and Tools Employed in Data Analytics. Spotlight: One large enterprise usage of analytic methods   What methods are used? Are there quantified benefits? Spotlight: One smaller enterprise usage of analytic methods   What methods are used? Are there quantified benefits? Applicability of Management Theories: Do identified management theories still work or should they be extended or modified to accommodate evolving business climate characterized with extensive use of data analytics? For more information read this: https://simple.wikipedia.org/wiki/Synthesis

Discussion: Why are the original/raw data not readily usable by analytics tasks? What are the main data preprocessing steps? List and explain their importance in analytics.