CompTIA Data+ E-learning with Exam

Algemene omschrijving

In dit CompTIA Data+ zelfstudiepakket zit het officiële cursusmateriaal: CertMaster Learn for Data+ (DA0-001) + CertMaster Labs en een CompTIA Data+ DA0-001-examenvoucher. Zodra je dit CompTIA Data+ zelfstudiepakket hebt geactiveerd, zijn het cursusmateriaal en de examenvoucher een jaar geldig.

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making.

Tell the Full Story with Data+:

• Better Analyze and Interpret Data - Mine data more effectively. Analyze with rigor. Avoid confounding results.
• Communicate Insights - Highlight what’s important. Produce reports that persuade, not confuse. Make better data-driven decisions.
• Recruit and Train - Know what data skills to recruit for. Train your team with confidence.

Train with Data+:
CompTIA Data+ gives your team members the confidence to bring data analysis to life.
As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive your organization’s priorities and lead business decision-making.

Doelgroep

• Data Analyst.
• Business Intelligence Analyst.
• Reporting Analyst.
• Marketing Analyst.
• Clinical Analyst.
• Business Data Analyst.
• Operations Analyst.

Leerdoelen

CompTIA Data+ validates your team members have the skills required to facilitate data-driven business decisions, including:

• Mining data.
• Manipulating data.
• Visualizing and reporting data.
• Applying basic statistical methods.
• Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle.

Voorkennis

CompTIA recommends 18–24 months of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience.

Onderwerpen

• Lesson 1: Identifying Basic Concepts of Data Schemas.
• Lesson 2: Understanding Different Data Systems.
• Lesson 3: Understanding Types and Characteristics of Data.
• Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages.
• Lesson 5: Explaining Data Integration and Collection Methods.
• Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data.
• Lesson 7: Executing Different Data Manipulation Techniques.
• Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization.
• Lesson 9: Applying Descriptive Statistical Methods.
• Lesson 10: Describing Key Analysis Techniques.
• Lesson 11: Understanding the Use of Different Statistical Methods.
• Lesson 12: Using the Appropriate Type of Visualization.
• Lesson 13: Expressing Business Requirements in a Report Format.
• Lesson 14: Designing Components for Reports and Dashboards.
• Lesson 15: Distinguishing Different Report Types.
• Lesson 16: Summarizing the Importance of Data Governance.
• Lesson 17: Applying Quality Control to Data.
• Lesson 18: Explaining Master Data Management Concepts.

Labs Available

• Assisted Lab: Navigating and Understanding Database Design.
• Assisted Lab: Understanding Data Types and Conversion.
• Assisted Lab: Working with Different File Formats.
• APPLIED LAB: Understanding Data Structure and Types and Using Basic Statements.
• Assisted Lab: Using Public Data.
• Assisted Lab: Profiling Data Sets.
• Assisted Lab: Addressing Redundant and Duplicated Data.
• Assisted Lab: Addressing Missing Values.
• APPLIED LAB: Preparing Data for Use.
• Assisted Lab: Recoding Data.
• Assisted Lab: Working with Queries and Join Types.
• APPLIED LAB: Building Queries and Transforming Data.
• Assisted Lab: Using the Measures of Central Tendency.
• Assisted Lab: Using the Measures of Variability.
• APPLIED LAB: Analyzing Data.
• Assisted Lab: Building Basic Visuals to Make Visual Impact.
• Assisted Lab: Building Maps with Geographical Data.
• Assisted Lab: Using Visuals to Tell a Story.
• Assisted Lab: Filtering Data.
• Assisted Lab: Designing Elements for Dashboards.
• Assisted Lab: Building an Ad Hoc Report.
• APPLIED LAB: Visualizing Data.
• Assisted Lab: Understanding Security Requirements for Protecting Information.