CIW: Data Analyst (1D0-622)

(1D0-622-v1.2) / ISBN : 978-1-64459-235-9
This course includes
Lessons
TestPrep
Hands-On Labs (Add-on)
AI Tutor (Add-on)
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About This Course

Prepare for the CIW 1D0-622 exam with the latest CIW Data Analyst course. The data analyst training provides complete coverage of the 1D0-622 exam objectives and provides the skills in fundamentals of data analysis and big data, tools for capturing and analyzing data. It also teaches students how to analyze and report data and work with data sources. The 1D0-622 exam guide has the best learning resources and study materials to help you prepare for the exam.

Skills You’ll Get

The CIW Data Analyst certification is the fourth credential in the CIW Web and Mobile Design series. It covers using data to analyze all aspects of a company's operation and make appropriate business decisions, how to compare and contrast structured and unstructured data, and how to deploy tools for capturing and analyzing data, including Hadoop, R Project, and custom database solutions.

Get the support you need. Enroll in our Instructor-Led Course.

Lessons

7+ Lessons | 82+ Quizzes | 118+ Flashcards | 118+ Glossary of terms

TestPrep

48+ Pre Assessment Questions | 3+ Full Length Tests | 102+ Post Assessment Questions | 144+ Practice Test Questions

Hands-On Labs

17+ LiveLab | 17+ Video tutorials | 28+ Minutes

Video Lessons

8+ Videos | 29+ Minutes

1

Fundamentals of Data Analysis

  • The Importance of Quality Source Data
  • Data Structure Types
  • Centralized Data Benefits
  • Structured vs. Unstructured Data
  • Types of Data
  • Typical Sources of Business Data
  • Data Protection Policies
  • Search Engine Optimization
  • Data Life Cycle Management (DLM)
  • Data Analysis Process
  • Lesson Summary
2

Introduction to Big Data

  • Big Data
  • The Importance of IT Data Management
  • IT Business Environments
  • Cloud-Based Data
  • Cloud-Native Data
  • In-House Data
  • When to Migrate In-House Data to the Cloud
  • Variations of Cloud-Based Systems
  • Typical Databases Used for Data Analysis
  • Data-Driven Business Decisions
  • Impact of Data Errors
  • Importance of Organizational Strategy and Data Quality in Data Analytics
  • Data Modeling 
  • Importance of Data Maintenance and Data Backup
  • Lesson Summary
3

Working with Data Sources

  • Data E-Harmony: Working with Different Departments to Bring Data Together
  • The Purpose of Customer Relationship Management (CRM)
  • CRM Integration: A Banking Scenario
  • Obtaining Data from Email and User Forums
  • Obtaining Data from Other Knowledge Bases
  • Obtaining Data from CRM and Business-to-Business Frameworks
  • Transaction, Payment and Inventory Data
  • Using Multiple Data Sources
  • Lesson Summary
4

Tools for Capturing and Analyzing Data

  • Data Analytics Tools
  • Capturing Data: Tableau Public
  • Capturing Data: Google BigQuery
  • Capturing Data: OpenRefine
  • Overview: Hadoop-Based Environments
  • Capturing and Analyzing Data in Hadoop
  • The R Project
  • Additional Software for Data Capture
  • Lesson Summary
5

Analyzing and Reporting Data

  • Network Traffic
  • Data Integration
  • Why Testing is Important?
  • Statistical Computing and Programming
  • Organizational Efforts and Business Outcomes
  • Best Methods to Capture and Report Specific Data
  • Data Analysis and Reporting Dashboards
  • Create Reports and Charts
  • Create a Presentation for Reporting Data
  • Frequently Asked Questions for Presentations
  • Lesson Summary

Appendix A: Data Analyst Objectives and Locations

Appendix B: Works Consulted

0

Fundamentals of Data Analysis

  • Learning the Data Analysis Lingo
  • Learning Structured and Unstructured Data in the Real World
  • Analyzing the Metadata and Understanding Search Engine Optimization
  • Using the AdSense and AdWords Services
1

Introduction to Big Data

  • Analyzing and Utilizing Big Data
  • Adapting to Changing Data Requirements
  • Comparing Relational Database Management Systems
  • Analyzing DDDM and Data for Blanket Technology
2

Working with Data Sources

  • Calculating the Churn Rate
  • Analyzing Customer Relationship Management
  • Calculating Consumer Lifetime Value in Banking
  • Understanding the RFM Analysis for Customer Segmentation
3

Tools for Capturing and Analyzing Data

  • Creating a Stacked Bar Chart
  • Using RStudio
4

Analyzing and Reporting Data

  • Creating a Gantt Chart
  • Comparing Prezi and PowerPoint Presentations
  • Creating a PowerPoint Presentation

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Here are the pre-requisites:

  • CIW User Interface Designer or equivalent knowledge
  • CIW Internet Business Associate or equivalent knowledge
  • CIW Site Development Associate or equivalent knowledge
  • CIW Advanced HTML5 & CSS3 Specialist or equivalent knowledge
  • An understanding of spreadsheets, databases, business processes, web sites, and coding

USD 150

PSI

The exam consists of linear, multiple choice, fill in the blank, fact-based, and situational questions.

The exam contains 48 questions.

75 minutes

75%

Here are the retake policies:

  • A 24-hour waiting period is required between the first and second attempt exam.
  • If a candidate passes a CIW exam, he will not be allowed to retake that CIW exam.
  • 30 calendar days waiting period from the date of the previous sitting before any third or subsequent sitting exam.
  • There is no limit on the number of attempts a candidate may make on an exam, so long as the 30 day wait period is observed.

CIW certifications do not expire.

CIW: Data Analyst (1D0-622)

$249.00

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