Part One

DAT 430 Module One

Overview

Data analysts often need to review different approaches and explain to management what they need in order to successfully finish a task. In this journal assignment, discuss approaches to preprocessing based on the target data source for Projects One and Two, including discussing your choice of approach and why it would be in scope for meeting project needs. Reference the project rubrics for more detail on the data, scenario, and deliverable expectations for each.

Prompt

Discuss the different approaches to preprocessing data and relate how you think they might be useful or not useful in working on the projects for this course. Project One focuses on developing metrics for organizational initiatives in collaboration with stakeholders, and Project Two covers determining the likelihood of success of an organizational initiative and using data visualization tools to communicate results.

Specifically, you must address the following questions for each approach listed below:

• Aggregation
• Sampling
• Dimensionality reduction
• Feature subset selection
• Feature creation
• Discretization and binarization
• Variable transformation

1. What is this approach used for?
2. Why is it used?
3. Relate this approach to the projects: does this fit into the scope of the projects? Why or why not?

Then, choose an approach that you think best fits the projects and discuss why you think it is the most suitable approach for your work in the upcoming projects.

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Part two:

1-2 Journal: Approaches to Preprocessing Data

The first step in solving problems or answering questions in data analytics is to fully understand the goal of the analysis. A deep dive into the data of an organization is meaningless if you don't have a specific characteristic you are trying to show or a question you are trying to answer. For example, sometimes a stakeholder doesn't fully understand the data they are looking at, so they do not ask the analyst the right questions or give the proper direction. It is important to ask clarifying questions to get yourself in a frame of mind to be able to find the right answer and get the right data.

For your initial post, introduce yourself to your peers and then discuss the following:

• What are your goals for after you have completed this program?
• Read Chapter 2 of your textbook. https://docs.google.com/document/d/1mbrqod6gPogRsKxJpUsHvPMpUlcVRa52/edit?usp=sharing&ouid=102178126409409264531&rtpof=true&sd=true
• Pay special attention to the Big Picture, Specifics, and Related Scenarios, then describe why the Specifics and Related Scenarios are important in achieving the goal of the Big Picture. What additional questions could you ask your client to ensure your metric meets the need?
• How could you further clarify the questions to simplify future metrics?
• How could you ask the questions differently?