DAT690 Course Introduction

Students will be exposed to the latest research techniques used in data analytics. Through an integrative approach that draws upon traditional and cutting-edge applied research methods, the course will prepare students to be engaged, knowledgeable, and adept analytical thinkers. Through the use of a data-driven workflow that includes quantitative analysis, qualitative analysis, and visualization techniques, students will learn to synthesize and communicate insights from data analysis projects. You will acquire technical skills for designing robust data processes, developing analytical tools for building effective visualizations,

DAT690 Course Description

This course addresses important concepts in information security and threat modeling, developing a thorough understanding of the role of human factors in cybersecurity. The course covers risk analysis, conduct risk assessments, conduct incident response, provide guidance on policies and procedures for secure operations.

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Universities Offering the DAT690 Course

is offered by Colorado State University. The DAT690 – Capstone in Data Analytics (DAT690) is offered at Colorado State University’s online learning platform Canvas.

Learning Outcomes

This course provides a capstone for the Data Analytics specialization with topics covered in our three semester Data Analytics specialization and applicable to any major within CSU.

Course Content

Data analytics projects, data quality, data collection, analysis, visualization, data mining, predictive modeling and other topics covered in this course are applicable to any major

DAT690 Course Outline

Course Description: This course will be an immersive experience to help students develop the data analytics and information science skills necessary to become a successful professional in the field. The course will help students understand basic concepts of data mining, Big Data and data analytics and gain insights to how these concepts are applied in real-world settings.

This course will focus on theoretical, practical, and hands-on learning that incorporates data visualization, statistical analysis, machine learning, artificial intelligence, and advanced algorithms. Each class session will include tutorials on

DAT690 Course Objectives

DAT690 Course Objectives for DAT690 – Capstone in Data Analytics (DAT690) 1. Learn Data Analytics with a focus on how to design, build and implement data solutions. 2. Analyze data using algorithms and visualizations. 3. Engage in data visualization, predictive analytics and deep learning techniques using R, Python and Spark. 4. Apply metrics and metrics frameworks to analyze the real-world challenges of data science projects. Course Level: Undergraduate Prerequisites: Bachelor

DAT690 Course Pre-requisites

The course is pre-requisites for DAT690 – Capstone in Data Analytics (DAT690) course. This course will focus on the data science process, and it will teach you how to do different things with data. You will learn how to collect, transform, analyze and model data using the best tools available.

Advance Yourself through Advanced Data Science Projects & Personal Learning Experience of 4 months duration (April-September 2019)

Course Features

Employment Opportunities

Course Learning Outcomes

Ident

DAT690 Course Duration & Credits

Course Type Online Course Delivery Term – Duration 3 Months Class Timing Monday to Friday 8am-10am, Saturday, Sunday and Public Holidays OFF

Course Overview

The Capstone in Data Analytics (DAT690) is a study program that encompasses the practical application of data analytics in various industries. Students are exposed to data analytics tools such as Machine Learning, Deep Learning and Natural Language Processing to develop real-world solutions for the information collected from various sources.

In addition to this, students will be able

DAT690 Course Learning Outcomes

To be able to: Use basic analytical techniques to solve problems and develop ideas. Develop a model for the resolution of a business problem. Create visualizations with data. Communicate effectively about data. Assess the quality of data models, and compare models with each other. Work with time series data. Evaluate regression methods. Apply artificial intelligence methods for analyzing time series data. Build neural networks to process time series data.

* DAT690 Class Schedule may change due to factors outside of Mizzou’s control (

DAT690 Course Assessment & Grading Criteria

– Lab 1: Assignments (7% of final grade)

Students will be evaluated on their ability to apply technical concepts and principles learned in the DAT690 course to address business challenges. Students will also need to demonstrate an understanding of how analytics can be used as a means to manage data in a way that is both transparent and reliable.

a) Gather the data

b) Quantify the data

c) Analyze the data

d) Interpret the findings and communicate results

e) Apply

DAT690 Course Fact Sheet

from WGU

View the 2019-20 DAT690 Course Fact Sheet.

View the 2020-21 DAT690 Course Fact Sheet.

Cost and Payment Information

For information on course costs and payment, see the cost of tuition and fees page. You may also contact Student Accounts for cost and payment questions at 1.888.606.8578 or by email at studentaccounts@wgu.edu.

Apply Now!

Request more information about WGU Washington’s Data Analytics degree program today

DAT690 Course Delivery Modes

Coursework:

Total Duration of DAT690 Course : 4 Weeks

DAT690 – Capstone in Data Analytics (DAT690) Course Outline:

Unit 1: Introduction to Data Analytics

What is data analytics?

Defining what data is

Analyzing data using the power of machines

Characteristics of good data science and data analytics projects.

Unit 2: Cloud computing (CSCI301)

Objectives, terminology, architecture, and deployment of cloud infrastructure.

Infrastructure as code.

Infrastructure as a

DAT690 Course Faculty Qualifications

1. Have successfully completed the core courses in the undergraduate program for 15 credit hours, and 2. Have completed all applicable course work (i.e., no deficiency courses). Note: Courses requiring prerequisite(s) to satisfy these requirements will not be considered for transfer to the master’s degree program. A student who has not yet earned 15 credit hours of graduate coursework may be admitted with an undeclared major, but must complete a DAT690 course requirement (i.e., one semester in graduate

DAT690 Course Syllabus

Course Syllabus for DAT690 – Capstone in Data Analytics (DAT690) 1. What is the course about? The Capstone in Data Analytics (DAT690) program at the University of Washington is a two-semester, nine-course sequence designed to prepare students for data analytics careers. Students will learn to leverage the power of data and analytics to solve business problems with quantitative methods, from descriptive analytics, to exploratory analysis, to predictive modeling. Through taught lectures and tutorial sessions, students

Suggested DAT690 Course Resources/Books

– Business Analytics | 3-4 credits | Olin College of Engineering

<![CDATA[

Suggested DAT690 Course Resources/Books for DAT690 – Capstone in Data Analytics (DAT690) – Business Analytics | 3-4 credits | Olin College of Engineering

Course Schedule

Semester I – Fall 2021

Date Topic Assignment Due Week 1 Tuesday, September 7 Introductory Course Overview Readings Assignment Week 2 Monday, September 13 Introduction to Data Analytics</p>

DAT690 Course Practicum Journal

This is a practicum course designed to provide students with the opportunity to develop and refine data analytics skills. Students will work individually or in groups of two or three on a comprehensive final capstone project that applies data analytics skills and deep learning techniques to solve real-world problems. Project teams will work on both an individual and team basis, depending on student interest. The goal of this practicum is for students to apply their theoretical knowledge to real-world problem solving, gain experience in applying deep learning techniques, develop

Suggested DAT690 Course Resources (Websites, Books, Journal Articles, etc.)

Students have access to a wide variety of resources during their course work. Below is a partial list of the suggested resources for DAT690 – Capstone in Data Analytics (DAT690) and the resource which you should consider purchasing for your library.

Recommended Resources for DAT690 – Capstone in Data Analytics (DAT690)

Contact Course Resources:

Office Hours: TTh 1:00-2:00 PM, SF 2159

Email: DAT690Course@mit.edu

Phone: MIT Office

DAT690 Course Project Proposal

– 2017.6

Who should attend: This course is designed for those with a strong interest in Data Analytics and who want to build an understanding of the fundamental concepts of this exciting field.

Overview: The goal of this course is to help students gain a solid knowledge of the basic concepts of data analytics. Students will develop an awareness and understanding of the basic principles of data analysis, as well as an appreciation for the many different applications of analytical tools and techniques. Through hands-on exercises, students

DAT690 Course Practicum

Course Year: 2019

Course Code: 90782

Description:

Students will work on real-world data analytics and modeling problems using their own dataset and a sample of relevant data to create a final project. Students will work closely with faculty mentors, each of whom has knowledge and experience with the subject matter, to design a project that best meets their individual needs. They will also present their projects to an audience of industry leaders from Cornell University.

Prerequisites:

DAT690 Course Practicum for DAT

Related DAT690 Courses

at University of California – Davis 2019-2020

Course in Course Title Semester Credit Hours ANT691 Econometrics 3 ANT692 Econometrics 3 ANT693 Econometrics 3 ANT694 Econometrics 3 ECON592 Quantitative Economics & Data Analysis 3 PHED601 Introduction to Health Professions Education (PHED601) 1

Rank DAT690 Courses for DAT690 – Capstone in Data Analytics (DAT690) at University of California – Davis

The following DAT690

Midterm Exam

at Southern New Hampshire University (SNHU) – StudyBlue Flashcards

Next up

Resource summary

Question Answer

Chapter 8 Summary Explain why a company might want to have a data scientist. How does one go about choosing the right data scientist for the job?

Bookmark it to view later.
What students are saying

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An Introduction to Operations Management, International…

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What Should Students Expect to Be Tested from DAT690 Midterm Exam

at The University of Texas at Austin (UT Austin) in Fall 2019?

The DAT690 – Capstone in Data Analytics (DAT690) midterm exam will consist of approximately 75 multiple-choice questions. You will have approximately 90 minutes to complete the test.

How Do I Submit My DAT690 – Capstone in Data Analytics (DAT690) Exam?

You must submit your final paper by midnight, Sunday, December 15, 2019.

What Should I Bring for My DAT690

How to Prepare for DAT690 Midterm Exam

Course

Research paper writing is a most important part of every student’s academic career. It is the main form of communication between professors and students, as well as potential employers and future employees. Moreover, good research paper writing skills are needed to create a valuable document that will bring you good grades and good reputation in future.

In this course you are going to learn about all necessary aspects of research paper writing such as choosing a topic, conducting a literature review, creating an outline for the paper, choosing proper

Midterm Exam Questions Generated from Top 100 Pages on Bing

Courses

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Learn how to study for the DAT exam with our free, step-by-step guide to test prep. Our comprehensive overview covers everything you need to know about this test:.

DAT Preparation Resources | DAT Online Course | Kaplan Test Prep

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Midterm Exam Questions Generated from Top 100 Pages on Google

, 2018-2019

Last Updated: 2019-02-27T06:04:12.309. Most questions in DAT690 are modified from Top 100 DAT Supplemental Exam Questions Generated from Google – 2015 (DAT690) , 2014.

MATLAB for Data Analysis (MAT440) MATLAB for Data Analysis (MAT440) — This class will be taught using Matlab. The main content of the course will include:

1. Introduction to MATLAB and

Final Exam

expires on March 14, 2020. Students must finish their capstone project by this date. If you are not finished by the deadline, your certificate of completion will be revoked.

DAT690 Capstone in Data Analytics

Prerequisites: DAT690 – Capstone in Data Analytics (DAT690)

Instructor: Jon Miller

Course Description: This course provides an overview of data mining and its application to clinical trials, data driven design of clinical trials, descriptive statistics for clinical trials, laboratory testing

What Should Students Expect to Be Tested from DAT690 Final Exam

During DAT690 Final Exam students will be expected to answer 5 (five) questions that are worth 40% of the final course grade. Here is a list of the topics that you will be asked about:

Topic Weight Percentage 1. Data Modeling and Data Analysis

2. SQL, PL/SQL Programming

3. Big Data

4. Statistical & Machine Learning

5. Cloud Computing

6. Business Intelligence and Analytics 20%

If you want to get an idea on

How to Prepare for DAT690 Final Exam

| Study.com

Capstone in Data Analytics (DAT690) Capstone in Data Analytics (DAT690) – Study.com

In this lesson, you’ll learn what a capstone is, why some students have trouble completing the Capstone course and how you can prepare yourself to succeed. You’ll also learn about… Read More »
x
Visit our blog for more free lessons!

– 1. What is a capstone?
– 2. Why students have trouble with the Cap

Final Exam Questions Generated from Top 100 Pages on Bing

Capstone in Data Analytics (DAT690) – Last Date for Submission of Exam Questions: 26th April, 2018 View on GitHub

From the very beginning, students are expected to follow the accepted format and use the resources provided in the course materials. However, it is their responsibility to be aware of any changes or new resources that may affect your grade.

Quiz (1-3) Due Date: 5 May, 2018 Grade:

Question Mark

Your answer is not correct

Final Exam Questions Generated from Top 100 Pages on Google

– #1

Q. 27 (12 points)

In a typical hybrid support environment, the primary resource is an agent who monitors and maintains a database of data elements that are matched to standardized measurements of disease risk.

A. true B. false

Answer: TRUE

Q. 28 (12 points)

Which of the following statements about ETL tools are true?

A. They help with partitioning large datasets.

B. They help with choosing between different extraction methods

Week by Week Course Overview

DAT690 Week 1 Description

Week 1 Description for DAT690 – Capstone in Data Analytics (DAT690) Week 1 Description:

In this assignment, you are going to work on a real data set related to your current course. You will need to download the data set from the provided link and then follow these instructions. This task will take you at least one hour to complete.

You are also going to be evaluated on the following criteria:

I. Analyze a real data set using SQL

II. Provide a brief

DAT690 Week 1 Outline

– Course Hero https://www.coursehero.com/lit/DAT690/Week-1-Outline-for-DAT690-Capstone-in-Data-Analytics-DAT690-Course-Hero/ DAT690 Week 1 Outline for DAT690 – Capstone in Data Analytics (DAT690) DAT690 Week 1 Outline for DAT690 – Capstone in Data Analytics (DAT690) – Course Hero https://www.coursehero.com/lit/DAT690/Week-1-Outline-for-D

DAT690 Week 1 Objectives

Complete the week 1 Capstone Requirements and take the Quiz in Week 2.

Week 3

DAT690 Week 3 Capstone Requirements – Cognitive load in data analytics (DAT690) Complete the Capstone Requirements and take the Quiz in Week 3.

Week 4

DAT690 Week 4 Capstone Requirements – Knowledge transfer in data analytics (DAT690) Complete the Capstone Requirements and take the Quiz in Week 4.

Week 5

DAT690 Week 5 Capstone

DAT690 Week 1 Pre-requisites

Capstone in Data Analytics (DAT690) Week 1 Pre-requisites for DAT690 – Capstone in Data Analytics (DAT690)

Capstone in Data Analytics (DAT690) Week 2 The Type of Metrics Used in Decision Making and Case Study Week 2 The Type of Metrics Used in Decision Making and Case Study

Week 3 Big Data, Hadoop, and MapReduce Week 3 Big Data, Hadoop, and MapReduce

Week 4 Analyzing the Business Problems with

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DAT690 Week 1 Learning Outcomes

Week 1 Assignment – Questions

Week 2 Learning Outcomes for DAT690 – Capstone in Data Analytics (DAT690) Week 2 Assignment – Questions

Week 3 Learning Outcomes for DAT690 – Capstone in Data Analytics (DAT690) Week 3 Assignment – Questions

Week 4 Learning Outcomes for DAT690 – Capstone in Data Analytics (DAT690) Week 4 Assignment – Questions

Week 5 Learning Outcomes for DAT690 – Capstone in Data Analytics

DAT690 Week 1 Assessment & Grading

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DAT690 Week 2 Needs Assessment & Improvement Plan for NAS

DAT690 Week 1 Suggested Resources/Books

Week 1 Suggested Resources/Books for DAT690 – Capstone in Data Analytics (DAT690) You are required to use three resources/ books from the list below for your capstone project. Read and annotate each book. If a resource has an audio component, listen to the book and take notes as you read the text.

Week 1: Overview: The Six Principles of Data Analytics

Week 2: Using Data Analytics to Predict Consumer Behavior

Week 3: Utilizing High-

DAT690 Week 1 Assignment (20 Questions)

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DAT690 Week 1 Assignment Question (20 Questions)

1. (TCO A) Identify the appropriate data source(s) for use in a project and the type of information to be used. a. (TCO B) Explain how historical data or past performance can be used in decision making, and describe how these decisions may change over time. b. (TCO C) Describe how data from a variety of sources can be combined and analyzed to provide actionable insights that are useful in enhancing an organization’s decision-making process.

2. (TC

DAT690 Week 1 Discussion 1 (20 Questions)

DAT690 Week 1 DQ 1 (20 Questions)

Week 1 DQ 1 (20 Questions) for DAT690 – Capstone in Data Analytics (DAT690)

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DAT690 Week 1 Discussion 2 (20 Questions)

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Discuss the following in an essay: (25 points)

1. Explain why an organization should use predictive modeling to predict employee attendance.

2. Discuss the difference between regression analysis and predictive modeling.

3. Explain what a Customer Lifecyle Score is and how it is used to measure

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DAT690 Week 1 Quiz (20 Questions)

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DAT690 Week 1 MCQ’s (20 Multiple Choice Questions)

– Assignment Help

The following questions are in multiple choice format. Each correct answer will be awarded 4 points, each wrong answer will deduct 1 point.

1. In a segmentation of data based on customer needs and characteristics, which method would you use? (Points : 4)

A. Clustering

B. Hierarchical

C. Latent class analysis

D. Multidimensional scaling

2. Which of the following is NOT true about self-discovery? (Points :

DAT690 Week 2 Description

You are the director of a company that specializes in and data analytics. The task is to create a business case for a new product line to be launched into the market. The financials will include an income statement, balance sheet and cash flow statements.

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DAT690 Week 2 Discussion Question 1 (DT690) When you have finished working on this discussion question, read the posted response from instructor Savita regarding how you may want to address the questions as follows: 1

DAT690 Week 2 Outline

Capstone in Data Analytics (DAT690) Week 2 Outline for DAT690 – Capstone in Data Analytics (DAT690) ASSIGNMENT: CONDUCT A RESEARCH PAPER ON THE COMPETITION IN THE

BUSINESS ANALYTICS INDUSTRY

(30% of final grade)

You are a consultant hired to help a company with their business analytics strategy. You are asked to take the position of an independent consultant for at least one year. As you research the industry, you

DAT690 Week 2 Objectives

Capstone in Data Analytics (DAT690) Week 2 Objectives for DAT690 – Capstone in Data Analytics (DAT690)

Week 2 Background and Readings L. Sirkin, A. Stolow, E. Davis, and G. Golic. “Bayesian Nonparametric Likelihood Methods for Sequential Event History Data.” Biometrics 58.3 (2002): 1091-1101.

Baysian nonparametric methods provide a general framework for modeling

DAT690 Week 2 Pre-requisites

Individual Assignment Data Analytics Capstone Project (3p) 1.0 2.0 3.0 4.0 5.0 Total Available: 6.0 10.0 15.0 This is a new capstone project designed to allow students to build upon the theories and skills learned in previous courses and use them in a data analytics problem solving setting. Students will be exposed to the most up-to-date technology used in enterprise data analytics, as well as the

DAT690 Week 2 Duration

Week 2 Discussion 1

Description

solution

Question

Question;Week 2 – Discussion;1. There are numerous theories and patterns of thought on the topic of design. One is Pattern Driven Design (PDD), which focuses on creating user-centered designs for business applications. PDD has been proposed by many to be a good approach for designing business software, but what do you think? Please discuss and describe your thoughts and feelings about PDD.;2. What was one of the

DAT690 Week 2 Learning Outcomes

for week 2

Match the #1 team to the correct reason.

Match the #2 team to the correct reason.

Match the #3 team to the correct reason.

Match the #4 team to the correct reason.

DAT690 Week 2 Assessment & Grading

Week 2 Assessment & Grading for DAT690 – Capstone in Data Analytics (DAT690) Q:DQFinal Exam_Question.pdf

Capstone in Data Analytics – Week 4 Assignment: Capstone Project

Capstone in Data Analytics – Week 4 Assignment: Capstone Project A capstone project is a major final work that you complete while pursuing your degree. This project represents the culmination of your studies at UCF, and should highlight your expertise, skills, and intellectual capacity

DAT690 Week 2 Suggested Resources/Books

with Dr. Asif Alam

https://www.zoho.com/courses/real-world-data-analytics-dataschool-1449-dataschool-for-data-analytics.html

https://www.purdue.edu/~pagel/dat690-week-2-suggested-resources-books-for-dat690-capstone-in-data-analytics-dat690/

DAT690 Week 1 Suggested Resources/Books for DAT690 – Business Intelligence (DAT690) with Dr. Asif Alam

https://www.zoho.com/courses/business

DAT690 Week 2 Assignment (20 Questions)

You will submit this to Course Hero at https://www.coursehero.com/tutors-problems/DAT690/22673775-Week-2-Assignment-20-Questions-for-DAT690-Capstone-in-Data/ Incomplete paper without attachments received. This is a 20 point quiz (10 question) with 1 hour and 20 minutes to complete.

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DAT690 Week 2 Assignment Question (20 Questions)

Week 2 Assignment Question (20 Questions) for DAT690 – Capstone in Data Analytics (DAT690) $ 10.99

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Description

1. a) Write down a short explanation of what data analytics is and the types of data that can be analyzed using this methodology.

b) A small business needs a large amount of data every day. How would you collect and organize that data?

2. A small business uses statistical analysis to identify emerging trends, improve operational efficiency

DAT690 Week 2 Discussion 1 (20 Questions)

Discuss the types of data sets that should be captured as part of the application. The answer will be based on your knowledge of statistics and data analysis. Your analysis must include at least 5 examples of this class. Refer to the Capstone course materials and your textbook for more information.

View Answer Discuss

Answer & Explanation Solution: When using a pivoting method, you must determine whether you want to select all rows or only those with particular values in one or both of the columns, such as gender

DAT690 Week 2 DQ 1 (20 Questions)

– 60 points

Question: Data Analysis (How do you think you can use your knowledge of statistics and data to find patterns that would be useful in understanding the customer behavior on a company’s web site? )

Question: Data Analysis (How do you think you can use your knowledge of statistics and data to find patterns that would be useful in understanding the customer behavior on a company’s web site? ) QUESTION 2.1

Review the online Q&A session and complete part A. Using your

DAT690 Week 2 Discussion 2 (20 Questions)

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It is a common misconception that the data scientist must know at least some coding language in order to be successful in this field.

There are actually two types of coders:

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DAT690 Week 2 DQ 2 (20 Questions)

3. Understand the principles of human behavior and motivation. Business Analytics Certification & Online Courses. Over the past several years, there has been a dramatic increase in interest in Data Science and its potential to solve some of the world’s most challenging problems. This is the Course Modules Page for DAT690 – Data Analytics Capstone (DAT690). This course will introduce you to some of the tools you’ll need for your project, including text mining, classification algorithms, sentiment analysis and more. Another good reason

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DAT690 Week 2 MCQ’s (20 Multiple Choice Questions)

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DAT690 Week 3 Description

Week 3 Description for DAT690 – Capstone in Data Analytics (DAT690) This document provides the week three description of your Capstone in Data Analytics project. Use this document to help you complete all of the tasks and milestones required for your Capstone in Data Analytics project. DAT690 Week 3 Capstone Project Assignment Instructions In this assignment, you will prepare to capstone your Data Analytics course by completing a final project that aligns with the learning objectives, as well as the specific requirements from

DAT690 Week 3 Outline

Capstone in Data Analytics (DAT690) for Degree Plus students! Data Analytics (DAT690) – Capstone in Data Analytics Instructors: Dr. Hedy Kostanek and Dr. Timothy Fagan Students will become data scientists who understand the core functions of data analytics, which are to: 1. Collect and analyze a large volume of relevant information, 2. Extract hidden patterns or trends within that information, and 3. Present those new insights to business leaders to assist them

DAT690 Week 3 Objectives

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DAT690 Week 3 Pre-requisites

Week 3 Pre-requisites for DAT690 – Capstone in Data Analytics (DAT690) For more course tutorials visit www.uophelp.com Case study : Creating a new account: James creates an account by providing the following information: First name, last name, and email address. He then provides his social security number. After submitting the information, James receives a message from the IT department that he has an account with an invalid email address. The IT department then sends James a confirmation message with instructions

DAT690 Week 3 Duration

2. You need to be well versed in the subject matter of this course before attempting the quizzes and final assignment. There are a variety of activities you may choose from for this assignment. In order to get a “C” grade, you must have no less than a “B” average (this is what it takes