In this assignment, you will play the role of Analyst for a well-known venture capital firm.

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

 Background

This week, we began to familiarize ourselves with the common steps associated with data cleanup. Often, the principle challenge in beginning analytic work is the difficulty in breaking down the steps necessary to achieve a desired end-goal. Over time, patterns begin to emerge and your natural speed at cleaning up data will begin to accelerate. The key is to continue honing this pattern recognition.

 

 Your Task

In this assignment, you will play the role of Analyst for a well-known venture capital firm. The firm is currently investigating investment patterns across the United States — and is particularly interested in understanding whether certain regions behave differently with regard to Multi-Series Funding. The firm is particularly curious to understand whether companies based in large metropolitan cities outside the Bay Area see smaller rounds following their Series A.

 

You've been provided a dataset from Crunchbase with investment information related to companies across the globe. Your task is to clean the data such that you can quickly produce a Tableau visualizer that meets your firm's objective.

 

Part I: Sample Explorer

The firm has provided you with two screenshots as samples of what it's looking to re-produce. Take a few moments to study the samples to understand the end-goal.

 

Graph showing, by regional hub, the average total raised through series funding

 

Graph showing, by regional hub, the average total raised through series funding

 

 

In addition to these screenshots, the firm has provided this information:

 

The final visuals involve stacked bar charts. The stacks display the Average Funding by Investment Round for each of the regions. (i.e. According to Sample #2: Boston Startups in Cloud Computing raised an average of $9.3M in Round B Funding).

The final graphs filter out all companies that did NOT raise at least a Round B.

The final graphs filter out all companies not based in the United States.

The final Tableau workbook should involve NO custom calculated fields.

The final Tableau workbook should involve NO filtering other than Category in the workbook itself. All data should be pre-filtered in the CSV file.

Part II: Data Prep

Begin by opening the starter file provided. Investigate the fields to get a sense of the data fields included. Then proceed to create a workflow in Tableau Prep that generates the necessary data file to power and build your target visualization.

 

At minimum, your workflow will need do each of the following:

 

Removes any and all fields not necessary to the final visualization.

Assigns each company's category to be the first category in its category list.

Removes all Non-US based companies from the dataset.

Assigns all regions as being one of the following: SF Bay Area, New York City, Los Angeles, Boston, Austin, Seattle, or Other.

Removes all companies that have not raised at least a Round B.

Part III: Visualization Prep

Once you've generated your target visualization, re-create the visualization provided. Note, again, that your Tableau Workbook should not include any calculated fields or filters other than for Category.

 

Using your visualizer, capture screenshots of the hub patterns for each of the below categories:

 

Advertising

Biotechnology

Big Data

E-Commerce

Finance

Real Estate

Video Streaming

Part IV: Reporting

Generate a report that includes:

 

Your visualization screenshots

A screenshot of your workflow with 250 words of commentary summarizing the cleanup steps you took

A 250-500 word reflection on any observations you gleaned around investment patterns across the various hubs.

Your homework submission should include your Tableau Prep workflow file (.tlfx), cleaned CSV file, packaged Tableau workbook, and report file.

Attachments:

Expert's Answer

177 Times Downloaded

Related Questions

. The fundamental operations of create, read, update, and delete (CRUD) in either Python or Java

CS 340 Milestone One Guidelines and Rubric  Overview: For this assignment, you will implement the fundamental operations of create, read, update,

. Develop a program to emulate a purchase transaction at a retail store. This  program will have two classes, a LineItem class and a Transaction class

Retail Transaction Programming Project  Project Requirements:  Develop a program to emulate a purchase transaction at a retail store. This

. The following program contains five errors. Identify the errors and fix them

7COM1028   Secure Systems Programming   Referral Coursework: Secure

. Accepts the following from a user: Item Name Item Quantity Item Price Allows the user to create a file to store the sales receipt contents

Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip

. The final project will encompass developing a web service using a software stack and implementing an industry-standard interface. Regardless of whether you choose to pursue application development goals as a pure developer or as a software engineer

CS 340 Final Project Guidelines and Rubric  Overview The final project will encompass developing a web service using a software stack and impleme