Vyas_Project3_Report

Large volumes of ungrouped data were often organized into intervals of our choice in the past. We are faced with colossal and formidable difficulties, just as in the real world. Do the advantages and disadvantages of working in a group outweigh working alone?

Computer Science Analyze the titanic dataset by applying the various relevant techniques taught in class starting from cleaning the data, imputing data, and finally visualizing the data. Provide justification as to why you are using a technique. To receive full points, you should have appropriate cleaning and/or data transformation steps, charts/plots should be meaningful with no overlapping labels. I should see at least 5 different types (bar, line, pie, etc) of charts. You should have a conclusion by highlighting the most important insight you derived from the dataset

In Business Intelligence and Data Science, what are the advantages and disadvantages of using tools like Tableau for visualization versus using Data Science options such as Python libraries such as Matplotlib/Seaborn or R libraries such as Ggplot2/Plotly?

Imagine you are part of a research team tasked with creating a new educational mobile application aimed at enhancing online learning experiences. In this context, answer the following four questions. First, for understanding how users interact with a newly developed mobile application, your goal is to gather data to evaluate the usability and user satisfaction of the application. Using the concepts and methodologies discussed in Module 8 of the Human Computer Interaction:   Design a Data Gathering plan for data gathering, specifying the methods you would use (e.g., interviews, questionnaires, observations) and justify your choices based on the nature of the study. Discuss how the data gathered from each method can be analyzed to provide insights into the usability and user satisfaction of the mobile application. Note: Your answer should demonstrate a clear understanding of the different data gathering techniques, their appropriate application, and the importance of ethical…

Analytical data is the fundamental distinction between BI and adalytic data.

Distinguish between a tabular and a virtual analysis of data?

The question is in the image attached

Data Preparation Describe what you did with the data prior to the modelling process (data cleaning). Show histograms of the one example variable before and after any pre-processing that you carried out. If you corrected any mis- typed entries in the data, report what you changed. Carry out descriptive analysis and explain each what they represent, use as many graph as possible and provide the descriptions

Predictive modeling: Task: Ambulance Demand Data Generating Process: for New York City   Dates of Coverage {Please identify the specific dates that will be used for this dataset in your modeling effort other than the City Health Department's Emergency Medical Services Division.   }   Frequency of data collection {how often is the data collected?  After every incident? Daily? Yearly?}   Agency / Organization collecting the data {who specifically is collecting the data?  Please avoid using general references like “government” or “police}   Original Unit of Analysis {What is the original unit of analysis for the data as provided?  Calls for service?  Census tracts? Cities?}   Transformed Unit of Analysis{i.e. are you modifying the call data to support your model? Hint: if you are doing “demand” model you will be aggregating the data.}   Data Generation Description{here, I want you in your own words to describe how you think the data was generated.  Think 2-3 sentences.}   Data…

Predictive modeling: Task: Ambulance Demand Data Generating Process:   Dates of Coverage {Please identify the specific dates that will be used for this dataset in your modeling effort}   Frequency of data collection {how often is the data collected?  After every incident? Daily? Yearly?}   Agency / Organization collecting the data {who specifically is collecting the data?  Please avoid using general references like “government” or “police}   Original Unit of Analysis {What is the original unit of analysis for the data as provided?  Calls for service?  Census tracts? Cities?}   Transformed Unit of Analysis{i.e. are you modifying the call data to support your model? Hint: if you are doing “demand” model you will be aggregating the data.}   Data Generation Description{here, I want you in your own words to describe how you think the data was generated.  Think 2-3 sentences.}   Data Collector{Who collects the data? A dispatcher?  A Census taker?}   Triggering Process{What triggers the data…

Data about the horses that have been awarded top places in events has already been captured ina spreadsheet (an extract from the spreadsheet is shown below). The data has been normalised tofirst normal form already – underlined column names indicate composite primary key columns.HorseID   Horse Name       BreedID     Breed Name       EventID      Event Name      Place1                 Speedy                1             Thoroughbred       15          Show Jumping       11                 Speedy                1             Thoroughbred        2              Dressage            52                 Candy Floss        2                Appaloosa          15          Show Jumping       23                 Getting Warmer   1             Thoroughbred        2              Dressage            44                 Mother’s Love      9               Arabian                3               Eventing            3 Normalise the above data to third normal form (3NF). Show all steps as well as the final…

PLEASE SHOW ALL WORK AND COMMENT ALL CODE The Objective of this coding problem is the prediction of a proposed metro ectension construction project based on the people'es opinion. There are three alternatives to choose they are as follows: Eglington-Pickering Line Airport-Vaughn Line Airposrt-Hamilton Line Each record is represented by 16 features. Task-1: Metro-Ext.xlsx is the training and test dataset; you will considerr 80% of the data for training and 20% for the test. Build (1) Logistic regression (2) KNN and (3) Naive Bayes model to predict on the test data set and compute the confusion matrix for each model and compare the result.  deliverables = coding files (.py and .ipynb), and a discussions of confusion matrix for both models   metro-EXT.xlsx (Please place chart in EXCEL) Feasibility and Constructability Slopes and Gradients Urban Realm Geology and Soil Stability Land Acquisition Work Opportunities Economy in Movement of People Revenue Generation Access to the Social,…

Urban data design is a company which designs digital products and concepts that make neighborhoods more sustainable and healthier place to live and do business in. This project focuses on a creation of a new app for Urban Data Design for one of their business problems. The app will make it easier for organizers to find the best suited open spaces according to their requirements for a potential event. Make it easier for everyday citizens to find and participate in interesting events happening in open spaces around them.  The purpose is to provide a platform for people in the community to get information regarding open spaces located in their area. The people will be able to organize events in these open spaces and list them on the app. People can get information regarding events which are happening in their areas in open spaces. Provide the community to participate in communal activities to build strong ties and belonging to its community. These events can promote physical activities…

A common practice was to aggregate large volumes of ungrouped data into intervals of our own design. As in the real world, we face vast and difficult obstacles. Are there any advantages or disadvantages to working in a group vs working alone?

What are the advantages of using a Dimensional Model?

Do you have any recommendations for the capturing of the data flow?

The presentation of quantitative information in a graphical form is Group of answer choices Data exploration Data visualization Data explanation Summary statistics

What are the advantages of data model?

The term "Hybrid Approach" in the context of data warehousing pertains to a methodology that combines elements of both traditional and modern approaches in order to optimize the storage, processing, and analysis of data.