WGU D204 Questions & Answers With Complete Solution

Business Understanding/ Discovery phase - Answer An analyst defines the major questions of interest that need to be answered, determines the needs of the stakeholders, and assesses the resource constraints of the project. Define project outcomes. Data Acquisition - Answer Collecting data phase. Data is collected and stored, for easy retrieval from a database, perhaps a component of a data warehouse, by using a language like SQL. Web scraping and surveys to acquire data. Data Cleaning - Answer Also known as data cleansing, data wrangling, data munging, and feature engineering. Analyst will use SQL, Python, R, or Excel to perform data modifications and transformations Data Exploration - Answer Analyst begins to understand the basic nature of data, the relationships within it (btw data variables), the structure of the dataset, the presence of outliers, and the distribution of data values. This phase uses data visualization tools and numerical summaries such as measures of central tendency and variability. Predictive Modeling - Answer Allows the analyst to move beyond describing the data to creating models that enable predictions of outcomes of interest. Python and R are used in automating the training and use of models. Data Mining - Answer Looks for patterns in large sets of data. Tools are Python and R. Also called Machine learning. A specialized segment of data mining techniques that continually update to improve modeling over time. Data Exploration - Answer An initial step to uncover initial patterns and using both manual and automated methods. Data Mining - Answer An in- depth step to discover patters using automated methods like machine learning. Data Reporting - Answer Analyst tells the story of the data and uses graphs or interactive dashboards to inform others of the findings from the analyses. Tools such as Tableau is used to spot trends and patterns. Goal is to give actionable insight to stakeholders. Descriptive Analytics - Answer What happened? - Observation/Describe event. It is the interpretation of historical data to better explain market developments. Diagnostic Analytics - Answer Why did it happen? - Explains the reason for the event. It enables the extraction of value from data by posing the right questions and conducting in-depth investigations into the problems. Predictive Analytics - Answer What will happen? - Correlation. Predicts what will happen in the future. It uses data, statistical algorithms, and machine learning techniques to determine the JS of potential outcomes. The aim is to have the best assessment of what will happen in the future, rather than simply understanding what has happened. Linear Regression - Answer Used to predict the value of variable based on the value of another variable. The variable to be predicted is called dependent variable and the variable used to predict the target variable is independent variable. Prescriptive Analytics - Answer How can we make it happen? - Keywords: Change/Action/Solution/Causality/Manipulation/Decision Making. It helps organizations make decisions. Predictive and Prescriptive analytics - Answer What are two forward-looking tools used by business leaders? ___________ analytics uses collected data to come up with future outcomes, and ____________ analytics takes that data and make decisions that cause future outcomes. Structured - Answer Which data type is numbered and labeled stored in an organized framework with columns and rows, e.g. Sql, databases, Excel, etc. Semi-Structured - Answer Which data type is loosely organized in categories using tags. e.g. Emails, CSV, XML, JSON doc., etc. Unstructured - Answer Which data type is text heavy, information not organized in clearly defined framework. e.g. text, videos, audios, etc. Quantitative - Answer Which data type is known as numerical, parametric, or interval data. Qualitative - Answer Which data type is known as nominal or ordinal. Describes the basic features of the data in a study. Relational Database - Answer What is a collection of data items with predefined relationships between them e.g. collection of tables. Data Sources - Answer In house, open Data, web server, data lake, data warehouse, self-generated are types of what? Python - Answer Which data analytics application/process is open-source general-purpose programming language. Python provides a more general approach and has several libraries that are useful to data science. Used by engineers and programmers. R - Answer Which data analytics application/process is an open-source programming languages with new libraries or tools added continuously. Tableau - Answer Which data analytics application/process is a visual analytics engine that makes it easier to create interactive visual analytics in the form of dashboards. Application Programming Interface (API) - Answer Which data analytics application/process is a software intermediary that allows two applications to talk to each other. In other words, it is the messenger that delivers your request to the provider that you are requesting it from and then delivers the response back to you e.g. pay with PayPal, SQL. XML - Answer Which data analytics language is a set of codes, or tags, that describes the text in a digital document. SQL - Answer Which data analytics application/process is a domain specific language used in programming and designed for managing data in relational database management systems. Helps pull data from databases. D (Data driven document) - Answer Which data analytics application/process is a JavaScript library for manipulating documents based on data. It helps bring data to life using HTML, SVG and CSS. Search Engine - Answer Which data analytics application/process is a program that searches for and identifies items in a database that correspond to keywords or character specified by the user. JSON (JavaScript Object Notation) - Answer Which data analytics application/process is a lightweight format for storing and transporting data on networks. Also an open standard file format, and data interchange format, that uses human-readable text to store and transmit data objects consisting of attribute-value pairs and array data types