Comptia Data Plus Certification Preparation Crash Course

Prepare yourself to pass the rewarding CompTIA Data+ (DA0-001) exam on the first try with this course/practice exam!

What you'll learn

Understand the importance of the CompTIA Data Plus exam and its objectives.

You'll learn to how to collect, analyze, and report on various types of commonly used data

Y ou’ll learn about how to transform raw data into usable information for your stakeholders.

Learn about database types, data structures, data schemes and other important aspects of data management.

Understand how ETL and ELT processes work, how APIs connect us to the cloud and learn about profiling datasets.

Learn about data manipulation techniques and important concepts around data transposition and normalization.

Learn about descriptive statistics, inferential statistics, and various analytic techniques.

Identify common analytics tools used in data analysis

Learn about the importance of Structured Query Language (SQL) and its main components.

Describe the importance of data governance, data stewardship and quality controls to ensure compliance and data consistency.

Identify the compliance requirements, security controls and privacy.

Requirements

No requirements or experience needed for the course.

The CompTIA Data plus exam does have specific recommendations for experience so please review

Description

The demand for data professionals has been exponentially growing year over year and becoming CompTIA Data Plus (DAO-001) Certified can really elevate your career opportunities in the world of data and business analytics.Data is the foundation for many organizations and offers the potential for growth in almost any industry. Data analysts collect, store, transform, maintain, analyze, and secure data for use in their organizations.A CompTIA Data Plus certified professional is proficient at the collection, analysis, and visualization of data that provides value so that their organizations achieve goals and can make complex business decisions.The Data+ exam is designed to be a vendor-neutral certification for data professionals and those seeking to enter the data fields.Did you know in Oct 2023, the average salary for a Data Analyst is $74,753 dollars per year in United States according to Glassdoor.Entry level business analysts in the United States can start at $64,026 per year while the most sought-after solutions architects can make over $154,000 per year.Once you complete this CompTIA Data Plus Certification Crash Course you will truly be prepared to take your place amongst the highly sought-after data professionals in your organization.About the CourseIn this course we focus on preparing you for a successful sitting for the challenging CompTIA Data Plus DA0-001 exam.This course provides full content, free practice questions and study eBook as well optional demonstration and exercises.An important aspect that data professional must know is focused on data mining, data manipulation as well as visualizing and reporting data to stakeholders.So, whether applying basic statistical methods or analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle a data professional is an important role to enterprises.All of the exam objectives are covered as specified by CompTIA for the exam in these domains.Data Concepts and EnvironmentsData MiningData AnalysisData VisualizationData Governance, Quality, and ControlsABOUT THE COMPTIA DATA+ CERTIFICATIONCompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. The certification validates the data analytics skills and competencies that are needed to organize, understand, and act on relevant data.This course covers 100% of the DA0-001 objective domains and also provides exam test tips, topic focused demonstrations and over 100 practice questions along with a free downloadable study guide.What will you learn in the course?Understand the importance of the CompTIA Data Plus exam and its objectives.You'll learn to how to collect, analyze, and report on various types of commonly used data.You’ll learn about how to transform raw data into usable information for your stakeholders.Learn about database types, data structures, data schemes and other important aspects of data management.Understand how JSON data, HTML data, and XML data is used with data professionals.Understand how ETL and ELT processes work, how APIs connect us to the cloud and learn about profiling datasets.Learn about data manipulation techniques and important concepts around data transposition and normalization.Learn about descriptive statistics, inferential statistics, and various analytic techniques.Identify common analytics tools used in data analysis.Learn about the importance of Structured Query Language (SQL) and its main components.Learn about reporting, reporting dashboards and the various visualization types.Describe the importance of data governance, data stewardship and quality controls to ensure compliance and data consistency.Identify the compliance requirements, security controls and privacy.Course Content CoveredCourse WelcomeCourse OverviewInstructor IntroductionWhat is the CompTIA Data Plus ExamExam ObjectivesExam Acronym ListData Roles to KnowThe Importance of DataDownload Course ResourcesData Concepts and EnvironmentsData SchemesData DimensionsDatabasesDemonstration - Google Cloud SQLData Warehouses and Data LakesOnline transactional processing (OLTP)Demonstration - AWS RedshiftOnline Analytical Processing (OLAP)What is a Schema?Importance of DimensionsDemonstration - Google Cloud Big Query (OLAP)Data TypesDemonstration - File TypesDemonstration - Deploy SQL Demo BenchData StructuresWhat is a Data StructureStructuredUnstructuredSemi StructuredData File FormatsBig Data File FormatsWhat is Columnar FormatData CompressionModule Summary ReviewModule Review QuestionsData MiningUnderstanding Data AcquisitionIntegration ConceptsWhat is An API?Demonstration - APIsData Collection Method OptionsDemonstration - Google Big Query Sample DataWhiteboard Discussion - Data CollectionData Cleansing and ProfilingWhiteboard Discussion - Data Cleansing/ProfilingDemonstration - Excel Data Cleansing and ProfilingData OutliersUnderstanding Data Manipulation TechniquesRecoding DataMerge DataEliminate RedundancyData NormalizationETLScenario - Data ManipulationCommon techniques for data manipulation and query optimizationData Manipulation WorkflowData Manipulation TechniquesQuery OptimizationDemonstration - Query OptimizationModule Summary ReviewModule Review QuestionsData AnalysisUnderstanding Descriptive Statistical MethodsMeasures of TendencyMeasures of DispersionUnderstanding PercentagesUnderstanding Inferential Statistical MethodsHypothesis TestingLinear Regression and CorrelationSummarize types of analysis and key analysis techniquesDefine Exploratory Data AnalysisPerformance AnalysisLink AnalysisCommon Data Tool SetsDemonstration - MS ExcelDemonstration - Power BIDemonstration - AWS QuicksightModule Summary ReviewModule Review QuestionsData VisualizationModule OverviewTranslate Business Requirements to ReportsDesign ComponentsDemonstration - Reports and ComponentsDashboard DesignDashboard ComponentsDemonstration - Dashboard ComponentsData Sources and AttributesConsumersDelivery and DevelopmentVisualization TypesUnderstanding Chart TypesUnderstanding Plot TypesUnderstanding MappingDemonstration - VisualizationCompare and Contrast ReportsReports Type OverviewRecurring Report TypesStatic and Dynamic ReportsDemonstration - ComplianceModule Summary ReviewModule Review QuestionsData Governance, Quality and ControlsModule OverviewData GovernanceRequirementsData ClassificationData PrivacyData BreachesData Quality ControlData ChecksData TransformationData ValidationData QualityData Quality DimensionsRules and MetricsMaster Data Management (MDM)Module Summary ReviewModule Review QuestionsExam Preparation and Practice ExamsExam ExperienceCertification CPE RequirementsCourse Content ReviewTop Ten Things to Know for the ExamPractice Questions Pool 1Practice Questions Pool 2Additional ResourcesCourse CloseoutWho should take this course (Target Audience)?Beginners looking for an entry point into the data world.Data Engineers, Data Analysts with some experience working with data.Software professionals, Database professionals looking to boost their knowledge and skillsetsWhat are the Couse Pre Requirements?There are no course pre-requirements.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Course Welcome

Lecture 3 Instructor Introduction

Lecture 4 What is the CompTIA Data Plus Exam

Lecture 5 Roles that should consider the exam

Lecture 6 Exam Objectives

Lecture 7 Discussion - The Importance of Data

Lecture 8 DoD Data Decrees

Section 2: Module Data Concepts and Environments

Lecture 9 Module Overview

Lecture 10 Understanding Data Schemes

Lecture 11 What is a Database?

Lecture 12 Demonstration - Google Cloud SQL

Lecture 13 What is a Data Lake and Data Warehouse?

Lecture 14 Comparing OLTP and OLAP Processing

Lecture 15 Demonstration - AWS Redshift

Lecture 16 Demonstration - Deploy SQL DemoBench

Lecture 17 What is Column Database

Lecture 18 Data Structures, Files and Types

Lecture 19 Module Summary Review

Lecture 20 Module Review Questions

Section 3: Module Data Mining

Lecture 21 Module Overiew

Lecture 22 Data Acquisition and Integration

Lecture 23 Demonstration - Data Integration Techniques

Lecture 24 API Fundamentals

Lecture 25 Demo - Vision API

Lecture 26 Data Profiling and Cleansing

Lecture 27 Data Collection Method Options

Lecture 28 What is a Data Outlier

Lecture 29 Understanding ETL and ELT

Lecture 30 Query Optimization

Lecture 31 Understanding Data Manipulation Techniques

Lecture 32 Module Summary Review

Lecture 33 Module Review Questions

Section 4: Data Analysis

Lecture 34 Module Overview

Lecture 35 Descriptive Statistical Methods

Lecture 36 Measures of Tendency and Dispersion

Lecture 37 Understanding Percentages

Lecture 38 Inferential Statistical Methods

Lecture 39 Hypothesis Testing with Excel

Lecture 40 Whiteboard - Linear Regression and Correlation

Lecture 41 Whiteboard - Analysis Testing

Lecture 42 Module Summary Review

Lecture 43 Module Review Questions

Section 5: Module Data Visualization

Lecture 44 Module Overview

Lecture 45 Translate Business Requirements to Reports

Lecture 46 Whiteboard - Translate Business Requirements

Lecture 47 Dashboard Fundamentals

Lecture 48 Demonstration - Dashboard Components

Lecture 49 Data Sources and Attributes

Lecture 50 Understanding Chart and Graphs

Lecture 51 Reports Type and Elements

Lecture 52 Module Summary Review

Lecture 53 Module Review Questions

Section 6: Module Data Governance, Quality and Controls

Lecture 54 Module Overview

Lecture 55 Introduction to Data Governance

Lecture 56 Methods to Validate Quality

Lecture 57 Setting Data Quality Control

Lecture 58 Data Transformation Tools

Lecture 59 Data Security Fundamentals

Lecture 60 Master Data Management (MDM)

Lecture 61 Course Summary Review

Lecture 62 Data Plus Exam Experience

Lecture 63 Certification CPE Requirements

Lecture 64 Consider CYSA Exam

Lecture 65 Additional Resources

Lecture 66 Course Closeout

Beginners looking for an entry point into the data world.,Data Engineers, Data Analysts with some experience working with data.,Software professionals, Datababase professionals, IT professionals looking to obtain a data focused certification