1. Which emerging technology has made it possible for every enterprise to have access to limitless storage and high performance computing?
A) Cloud computing
2. Which of the data roles is responsible for extracting, integrating and organizing data into data reponsitories?
A) Data Engineer
3. When you analyze historical data to predict future outcomes what type of Data analytics are you performing?
A) Predictive Analytics
Graded Quiz Task-1
1. A modern data ecosystem includes a network of continually evolving entities. it includes:
A) Data sources, enterprise data repository business stakeholders, and tools application, and infrasturcture to manage data.
2. Data Analysts work within the data ecosystem to:
A) Gaither,clean,mine, and analyze data for derving insights
3. When we analyze data in order to understand why an event took place, which of the four types of data analytics are we performing?
A) Diagnostic Analysis
4. The first step in the data analysis process is to gain an in-depth understanding of the perfrom and the desired outcome. What are you seeking answers to at this stage of the data analysis process?
A) Where you are and where you need to be
5. From the provided list, select the three emerging technologies that are shaping today’s data ecosystem.
A) Cloud computing, machine learning, and big data
WEEK-1 TASK -2 PRACTICE QUIZ
1. Which of these skills is essential to the role of a Data Analyst?
A) Statistics
2. What, according to Sivaram Jaladi, goes a long way in lending credibility to your data analysis findings?
A) Sharing your process of arriving at the findings with your stakeholder
WEEK -1 TASK-2 GRADED QUIZ
1. Why is proficiency in Statistics an important skill for a Data Analyst?
A) For identifying patterns and correlations in data
2. Which of these is one of the soft skills required to be a successful Data Analyst?
A) Work collaboratively with cross-functional teams
3. Which of the data analyst functional skills helps research and interpret data, theorize, and make forecasts?
A) Analytical skills
4. In “A day in the life of a Data Analyst”, what according to Sivaram Jaladi forms a large part of a Data Analyst’s job?
A) Cleaning and preparing data
5. In “A day in the life of a Data Analyst”, what are some of the data points that were useful in analyzing the use case. (Select all that apply)
Serial number of the meters
Average billing amount of complainants
Week-2
TASK-1-PRACTICE QUIZ
1. what data type is typically found in databases and spreeadsheets?
A) Structured Data
2. Which of these data sources is an example of semi-structured data?
A) Emails
3.Which one of the provided file formats is commonly used by APis and web services to return data?
A) JSON
4. What is one example of the relational databases discussed in the video?
A) SQL sever
5.Which of the following languages is one of the most popular querying languages in use today?
A) SQl
TASK-1 GRADE QUIZ
1. in the data analyst’s ecosystem, languages are classified by type. what are shell and scripting languages most commonly used for?
A) Automatic repetitive operational tasks
2. Which of the following is an example of unstructured data?
A) Video and audio files
3. A) PDF
4. Which dat source can return data in plain textn, XML, HTML, or JSON among others?
A) APl
5. Accoridng to the video “Languages for data professionals” which of the progaramming languages supports multiple programming paradigms, such as object oriented,imperative, functional, and procedural, making it suitable for a wide variety of use cases?
A) Python
TASK-2-PRACTICE QUIZ
1. Structured Query Language, or SQL, is the standard querying language for what type of data repository?
A) RDBMS
2. In use cases for RDBMS, what is one of the reasons that relational databases are so well suited for OLTP application?
A) Support the abililty to insert, update, or delete small amounts of data
3. Which NOSQL, database type stores each record and its associated data within a single document and also works well with analytics platform?
A) Document-based
4. What type of data repository is used to isolate a subset of data for a particular, purpose or community of users?
A) Data Mart
5. What does the attribute ” Velocity” imply in the context of Big Data?
A) The speed at which data accumulates
6. Which of the Big Data processing tools provides distributed storage and processing of Big Data?
A)Hadoop
TASK-2-GRADED QUIZ
1. Data marts and data warehouses have typically been relational, but the emergence of what technology has helped to let these be used for non- relational data?
A) NoSQL
2. what is one of the most significant advantages of an RDBMS?
A) is ACID-compliant
3. Which one of the SQL database types uses a graphical model to represent and store data and is particularly useful for visualizing, analyzing and finding conncetion between different pieces of data ?
A)Graph-Based
4. which of the data repositories serves as a pool of raw data and stores large amounts of structured semi structured and unstrutured data in their native formats?
A) Data Lakes
5. What does the attribute “Veracity” imply in the context of big data?
A) Accuracy an conformity of data to facts
6. Apache spark is a general-purpose data processing engine designed to extract and process big data for a wide range applications. What is one of its key use cases?
A) Perform complex analytics in real-time
WEEK-3-PRACTICE QUIZ
1. What are the requirements in order for data to be reliable? (select that apply)
A) data should be free of all errors
Data should be relevant
2. What type of data is produced by wearable devices, smart buildings, and medical devices?
A) Sensor Data
3. What type of data is semi-structured and has some organizational properties but not a rigid schema?
A) Emails
WEEK -3 GRADED QUIZ
1. what are some of the steps in the process of “identifying data”?
determine the information you want to colletct
define a plan for collecting data
2. what type of data when refers to information obtained directly formsource?
primary data
3. web scraping is used to extract what type of data?
A) text,Videos,and images
4. Data obtained from an organization’s internal CRM,HR and workflow applications is classfied as:
A) primary data
5. which of the provided options offers simple commands to specify what is to be retrieved from a relational database?
A) SQL
WEEK-3TASK-2-PRACTCE QUIZ
1. what is one of the common structural transformation used for combining data from one or more tablets?
A) joins
2. What tool allows you to discover, cleanse, and transform data with built in operations?
A) watson studio refinery
3. what is data called the does not fit within the context of the use case?
A) irrelevant data
WEEK3-TASK-2-GRADED-QUIZ
1. What does a typical data wrangling workflow include?
A) validating the quality of the transformed data
2. openrefine is an open-source tool that allows you to:
A) transform data into a variety of formats such TSV, CSV,XLS,XML, and JSON
3. what is one of the steps in a typical data cleaning workflow?
A) inspecting data to detect issue an errors
4. when you’ re combining rows of data from multiple source tables into a single tasble, what kind of data transformation are you performing?
A) Unions
5. when you detect a value in your data set that is vastly different from other observations in the same data set, what would you report that as?
A) Outlier
WEEK-4 PRACTICE QUIZ
1. what is one of the common measures of Central Tendency?
A) mean
2. what technique is used to help identify that nature of the relationship between two variables?
A) Regression
3. what python libraries are commonly used for data mining?
A) Numpy
Pandas
WEEK 4 GRADED QUIZ
1.what is a branch of mathematics dealing with the collection, analysis, interpretation. and presentation of numerical or quantitative data ?
A) statistics
2. Data mining is defined as the process of:
A) Extracting knowledge from data
3. what type of data mining operations was R specifically built to handle?
A) Classification of data
4. When you ‘ re calculating the middel value of a data field in a data set, what are you really calculating?
A) median
5. what is the general tendency of a set of data to change over time called?
A) Trend
WEEK4-TASK2 PRACTICE QIUIZ
1. Data visualization such as graphs and charts are a great way to bring data to life.
A) True
2. you can use dashboards to present operational data such as daily progress data. as well as analytical data. such as the overall health of a business function.
A) True
3. What spreadsheet software is preferred when multiple users need to collaborate?
A) Google Sheets
WEEK-4 TASK-2 GRADED QUIZ
1. ” A presentation is not a data dump”. what is the one thing you would do to ensure your presentation is not a data dump?
A) include only that information as needed to address the business problem
2. what is the discipline of communicating information through the use of visual elements?
A) data visualization
3. matplotlib is a widely used python data visualization library.
A) True
4. what is the goal of data visualization?
A) make information easy to comprehend, interpret and retain
5. what can you do to help your audience trust you?
A) share your data sources, hypotheses, and validations
WEEK-5-PRACTICE QUIZ
1.on the data analyst specialist path, you could be starting your career as associate or junior data analyst and working your way up to a principal role. What are some of the factors that influence your growth on this path?
A) the experience and exposure you gain in the different areas within Data Analysis
2. Skills such as problems-solving communication, and storytelling are critical to the role of a data analyst. and like most soft skills, you re either good at a them, or your’re not’; these skills cannot be acquired over time.
A) False
WEEK-5 GRADED QUIZ
1.Which of the following statement describes data analyst specialist roles?
A) Analysts who advance technical, statistical, and analytical skills, over time, to expert levsls
2. A principal data analyst is responsible for:
A) Establishing processes in the team
3. Job roles such as Project Manager, Marketing Managers, and HR managers, can achieve greater efficiency and effectiveness in their current roles by acquiring data analysis skills, and are therefore known as analytics enabled job roles.
A) True
4. Which of these is essential for getting started and growing as a DataAnalyst?
A) Love for numbers, a curious mind, and openness to learn
5. what data analysis roles may be best suited for people with little or no technical training?
A) Functional Analyst
PRACTICE QUIZZ Week-1
1. Of the following, which one would be considered a core capability of spreadsheets?
A) statisical analysis
2. When you open an Excel workbook or spreadsheet, what kind of file is it?
A) .xlsx
3. According to this video, on the excel home tab what groups are listed?
A) font, alignment, number, styles
GRADED QUIZZ
3. In a box plot, in which quartile does 50% of the sorted data fall below?
A) Second Quartile
WEEK-2 TASK (2) PRACTICE QUIZ
1. Which functions can you use to change the title of a plot? Select two answers
A) ggtitle()
B) labs()
2. What can you add to a plot if you want to emphasize important elements, such as outliers or spikes in your data?
A) Annotation
3. You want to divide a plot into subplots based on a categorical variable called “quarters”. Which function should you add to ggplot() to do this?
A) facet_wrap(~quarters)
4. What information do you need to provide to create a visualization using the Leaflet library?
A) The latitude and longitude of each data point.
WEEK-2 TASK (2) GRADED QUIZ
1. You added text labels to the data points on your plot, but now the plot looks messy because there are so many of them. What should you do?
A) Set the check_overlap parameter of geom_text() to TRUE
2. If you do not specify a theme when creating a plot with ggplot2, which theme does it use by default ?
A) THEME_GRAY()
3. Using themes, you can change the colors and styles of the borders, backgrounds, lines, and text on a plot. What should you do if you want to completely remove one of these elements from the theme?
A) Assign the element.blank() function to the element
4. In a Leaflet map, which two statements describe the difference between the addCircles() and addCircleMarkers() functions?
A) Markers created with addcircles() can be rescaled
B) Markers created with addcircleMarkers() remain a constant size
WEEK-3 TASK (1) PRACTICE QUIZ
1. Which two components of a dashboard happen on the back end?
A) Serve
B) Analyze
2. Which is the preferred method for creating a Shiny app?
A) Separate code into server.R and ui.R files.
3. True or False: You must include the shinyApp() function in the code for all Shiny apps.
A) True
4. Which function creates an empty layout?
A) fluidPage
WEEK-3 TASK (1) GRADED QUIZ
1. True or False: A Shiny app consists of two parts, the server that the user interacts with and the UI that powers the app.
A) False
2. Which two components of a dashboard happen on the front end?
A) Interact
B) Visualize
3. Complete the sentence: You use the Layout functions to organize ____________________ containing user interface elements in the application.
A) Panels
4. When defining the server logic for a Shiny app, you define a function that includes which of the following parameters?
A) input, output
1. If you have the command plotOutput(“plot_histogram”) in the UI-side code in your Shiny application, what is the name of the variable that you assign the plot to in the server-side code?
A) output$plot_histogram
2. Can you publish a Shiny app to your shinyapps.io account from RStudio?
A) Yes, but only if you install the rsconnect package first.
3. What is the process to convert an R Markdown file to an HTML, PDF, or Microsoft Word document?
A) Knit
WEEK-3 TASK (2) GRADED QUIZ
1. In a Shiny application, where do you add input widgets?
A) A panel.
2. Which deployment method should you select for your Shiny app if you do not want to run your own server?
A) shinyapps.io
3. What are the two main differences between an R Markdown document and a Shiny dashboard?
A) A dashboard can be interactive, while an R Markdown document is static.
B) A dashboard always reflects current data, while an R Markdown document produces a snapshot of the data at the time the report is generated
BAN 5013 WEEK -08
Week -1 Check point
1. Have you web scraped and extracted bike-sharing systems as a data frame from the global Bike-sharing Systems Wiki page?
A) Yes
2. Have you collected weather forecast data for a list of cities using OpenWeather API?
A) Yes
3. Have you downloaded other relevant data sets from cloud storage?
A) Yes
Week-2 Checkpoints
1. Have you standardized column names o be all uppercase and use underscore to separate words?
A) Yes
2. Have you removed undesired Wiki reference links ‘[]’?
A) Yes
3. Have you extracted only the numeric bike count?
A) Yes
4. Have you handled missing values for *RENTED_BIKE_COUNT” and TEMPERATURE ” variables?
A) Yes
5. have you created indicator (dummy) variables for all categorical variables?
A) Yes
6. have you normalized all numeric variables with min-max scaling?
A) Yes
Week-3 Checkpoints
1. Have you created a Db2 database asset in your IBM Watson Studio project?
A) Yes
2. Have you loaded four datasets into Db2 Tables?
A) Yes
3. Have you used SQL queries with the RODBC R package to perform EDA?
A) Yes
4. Have you loaded the SEOUL BIKE SHARING dataset in R and cast some datatypes?
A) Yes
5. Have you used TidyVerse to perform statistical analysis on the data?
A) Yes
6. Have you used geplot to discover patterns in your data through visualization?
A) Yes
Week-4 checkpoints
1. Have you built a baseline regression model with only weather-related variables?
A) Yes
2. Have you built a baseline regression model with all variables?
A) Yes
3. Have you evaluated and compared model performance using RMSE and R-squared metrics?
A) Yes
4. Have you built at least five refined models using polynomial terms, interaction terms, and regularization?
A) Yes
5. Have you evaluated and visualized their RMSE and R-squared metrics using a grouped bar chart?
A) Yes
6. Have you selected the best-performing model and visualized its Q-Q plot?
A) Yes
Week-5 checkpoints
1. Have you created an R Shiny app with a basic max bike prediction overview map using leaflet?
A) Yes
2. Have you added a select input (dropdown) to select a specific city to the R Shiny app?
A) Yes
3. Have you added a static temperature trend line to the R Shiny app?
A) Yes
4. Have you added an interactive bike-sharing demand prediction trend line to the R Shiny app?
A) Yes
5. Have you added a static humidity and bike-sharing demand prediction correlation plot to the R Shiny app?
A) Yes
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