DAT 520 Module Two Lab Worksheet

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Southern New Hampshire University *

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520

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Industrial Engineering

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Apr 3, 2024

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docx

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DAT 520 Module Two Lab Worksheet Lessons 2 and 3 Labs Overview In these Module Two labs, you will explore connecting data sources to Power BI, creating relationships between various data sets, and shaping data for analysis. Instructions First, complete the following labs in the uCertify lab environment. Then, replace the bracketed text with the relevant information. Please note: This assignment will be submitted and graded in Brightspace. uCertify Labs 2.1.1 Creating Data Connections 2.2.1 Configuring and Managing Data Relationships 2.3.1 Saving Files in Power BI 3.1.1 Cleaning, Transforming, and Loading Connected Data 3.2.1 Profiling Data in Power BI 3.3.1 Shaping Data for Analysis Lab 2.1.1 Creating Data Connections 1. Navigate to the Data tab and take a screenshot of the two data sources you have brought into Power BI. Lab 2.2.1 Configuring and Managing Data Relationships 1. Take a screenshot of the relationships (found on the relationship view ) you have created between the two data sets and insert it below.
2. What does creating relationships between two data sets do for your future analysis? a. Creating relationships between two data sets allows you to compare against each other, use information in one table to bolster your data output on another. You don’t need to include category and subcategories they are now referenced by categoryID. Lab 3.1.1 Cleaning, Transforming, and Loading Connected Data 1. After completing Step 5, take a screenshot of the Query Editor you updated.
Lab 3.2.1 Profiling Data in Power BI 1. Within the Columns Profiles pane of the Transform Data Editor , select the Product Name column and ensure that the Column Profiles selection is checked. Take a screenshot of the graph displaying the distribution of the variables and insert it below.
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2. What is the total number of unique values? 44 3. What value has the largest representation? Soccer Ball Lab 3.3.1 Shaping Data for Analysis 1. Explain why it would be advantageous to be able to create new variables within your data set. In the example provided in the lab, creating a new column allowed us to see how many days it took for the company to ship the item after order date. This could be a very valuable number to know. This could help identify a problem with orders receiving, shipping or product inventory if those numbers are starting to rise. That new variable was natively supplied by the data set and being able to add new ones gives the ability to track new information from known information. 2. What is the importance of formatting your data properly? Just like in the example done in uCertify, before the new column was formatted with the proper data type it was showing as 2:00:00. This is looking like a “Time” data type, which is not what we needed. This could be confused as it only took 2 hours to ship, instead of days. So we format to “Whole numbers” so that numbers are shown properly.