CIW

CIW: Data Analyst (1D0-622)

Numbers don’t lie, but they sure need a good interpreter. That’s why you’re here.

(1D0-622-v1.2) / XXXX : 978-1-64459-235-9
Lessons
Lab (Xxxxxx)
TestPrep
AI Tutor (Xxxxxx)
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This CIW: Data Analyst course aligns with the 1D0-622 exam objectives, equipping you with the knowledge and skills to earn the certification. 

You’ll begin with fundamentals, covering data types, structures, quality data, and protection policies. Next, you’ll encounter big data and IT data management, learning when to migrate data to the cloud, database options, and how to leverage data for business decisions. 

Explore essential analytics tools like Tableau, Google BigQuery, and Hadoop, capturing and transforming data. Finally, learn to report your findings visually! 

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  • Understand data types, structures, and sources 
  • Evaluate data quality and protection policies 
  • Identify when to migrate data to the cloud 
  • Collaborate with departments using CRM for unified data insights
  • Capture and transform data using Tableau and BigQuery 
  • Analyze big data in cloud and Hadoop environments 
  • Create effective dashboards, charts, and reports 
  • Present data insights using polished presentations 
  • Apply statistical methods for accurate data interpretation
  • Manage data life cycles for optimal organization and accessibility
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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
A

Appendix A: Data Analyst Objectives and Locations

B

Appendix B: Works Consulted

1

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
2

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
3

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
4

Tools for Capturing and Analyzing Data

  • Creating a Stacked Bar Chart
  • Using RStudio
5

Analyzing and Reporting Data

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

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Explore more details about our 1D0-622 Data Analyst Exam guide.

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The CIW Data Analyst certification is designed for professionals looking to gain hands-on skills in data analysis, data interpretation, and data-driven decision-making. It’s ideal for beginners.

While a background in IT or data is helpful, our CIW Data Analyst Study Guide is structured to cover data fundamentals, making it suitable for beginners with a basic understanding of computers and the internet.

CIW Data Analyst focuses on data analysis foundations, data management, and essential tools, making it accessible to beginners. Certifications like Microsoft DP-900 or CompTIA Data+ may offer similar entry-level knowledge but with different specializations.

Jobs like junior data analyst, business analyst, data technician, and CRM analyst are common entry-level roles for CIW data analyst certification holders.

The cost varies by location and CIW pricing at the time of registration. It is generally between $150 and $200, though discounts or bundles with other courses may be available.

To start a data analyst career, begin by enrolling in our certification course to learn data manipulation, analysis, and visualization. Gain hands-on experience in tools like Excel, SQL, and Tableau and practice with real-world job scenarios.

Analyze, Interpret, and Present Data

  Join our Online CIW Data Analyst Training to learn how you can master the skills that drive business decisions. 

$249.00

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