Comptia Data+ (Da0-001) Complete Course & Practice Exam

CompTIA Data+ (DA0-001) exam on your 1st attempt, includes full-length practice exam!

What you'll learn
Take and pass the CompTIA Data+ (DA0-001) certification exam
Understand data concepts and environments
Understand how to conduct data mining
Understand how to conduct data analysis
Understand how to create and interpret visualizations
Understand how to conduct data governance, ensure data quality, and uphold data controls
Requirements
Basic understanding of office productivity tools, such as Word and Excel
Understand basic mathematics and how to read graphs
Description
*** Taught by TWO Best Selling Certification Instructors ***This course provides everything you need in order to study for the CompTIA Data+ (DA0-001) exam, including a downloadable Study Guide (PDF), quizzes to check your knowledge as you progress through the videos, and a full-length practice exam to test your knowledge before test day!Jason Dion is an expert in information technology and cybersecurity with over 20 years of experience, and he has designed this course to be a fun way to learn what you need to know to pass the CompTIA Data+ (DA0-001) exam or to better prepare yourself to serve as a data analyst in your organization's data analysis or business intelligence divisions.Frank Kane is a data analytics subject matter expert who has developed and managed technology that automatically delivers product and movie recommendations to hundreds of millions of customers during his tenure at Amazon and IMDb. In this course, he is going to share his extensive experience in distributed computing, data mining, and machine learning and how it applies to your work as a data analyst. The CompTIA Data+ (DA0-001) certification is a vendor-neutral certification that validates your knowledge and ability to conduct data analytics to develop and promote data-driven business decision-making in your organization. This certification tests your ability to better analyze and interpret data, communicate insights, and demonstrate competency in the world of data analytics. The CompTIA Data+ exam is designed for early-career data analysts with the equivalent of 12-24 months of on-the-job knowledge. The CompTIA Data+ exam is focused on data analytics in order to validate and communicate vital business intelligence by collecting, analyzing, and reporting on data that can drive the organization's priorities and drive their business decisions. CompTIA Data+ (DA0-001) is an early-career data analytics certification covering the theory and technical skills required to mine, manipulate, visualize, and report on data using basic statistical methods and complex dataset analysis while adhering to the governance and quality standards for the data throughout its entire life cycle. To help you practice for the CompTIA Data+ (DA0-001) exam, this course even comes with a realistic practice exam containing 90 multiple-choice questions spread across the five domains tested by the CompTIA Data+ (DA0-001) certification exam!        This course will provide you with full coverage of the five domains of the CompTIA Data+ (DA0-001) exam:    Data Concepts and Environments (15%)Data Mining (25%)Data Analysis (23%)Visualization (23%)Data Governance, Quality, & Controls (14%)This course stays current and up-to-date with the latest release of the CompTIA Data+ exam (DA0-001), and also provides a 30-day money-back guarantee if you are not satisfied with the quality of this course for any reason!This course is brought to you by Dion Training Solutions, a CompTIA Platinum Delivery Partner, and aligns directly with the OFFICIAL CompTIA Data+ (DA0-001) Certification Study Guide.What Other Students Are Saying About Our Courses:Jason Dion always has some of the best courses. This is the third CYSA+ course I bought from different vendors to see which one would help me more and like always this has already caught my attention and kept me focused the entire time. Other courses have too many distracting factors, unlike this one. I will always recommend Jason Dion. (Luis, 5 stars)Great course, very detailed. Passed the exam on the first try. I have recommended this course to everyone I know in the security industry trying to pass the CySA+ exam. (Jose D., 5 stars)I have really enjoyed and learned a lot from this course. I used Jason's course to pass the Network + on my first attempt, I am expecting that this course will enable me to pass the CySA+, too! (Leone W., 5 stars)

Overview

Section 1: Introduction to CompTIA Data+ (DA0-001)

Lecture 1 Welcome

Lecture 2 Download Your Free Study Guide

Lecture 3 Exam Tips

Section 2: Data Schemas

Lecture 4 Data Schemas (OBJ 1.1)

Lecture 5 Relational Databases (OBJ 1.1)

Lecture 6 Non-Relational Databases (OBJ 1.1)

Lecture 7 Comparing Database Types (OBJ 1.1)

Lecture 8 Data Normalization (OBJ 1.1)

Lecture 9 Database Relationships (OBJ 1.1)

Lecture 10 Referential Integrity (OBJ 1.1)

Lecture 11 Data Denormalization (OBJ 1.1)

Lecture 12 Hands-on with Data Schemas (OBJ 1.1)

Section 3: Data Systems

Lecture 13 Data Systems (OBJ 1.1)

Lecture 14 Data Processing Types (OBJ 1.1)

Lecture 15 Data Warehouse (OBJ 1.1)

Lecture 16 Data Warehouse Schemas (OBJ 1.1)

Lecture 17 Data Lakes (OBJ 1.1)

Lecture 18 Changing Dimensional Data (OBJ 1.1)

Lecture 19 Hands-on with Data Systems (OBJ 1.1)

Section 4: Data Types

Lecture 20 Data Types (OBJ 1.2 and1.3)

Lecture 21 Quantitative & Qualitative (OBJ 1.2)

Lecture 22 Data Field Types (OBJ 1.2)

Lecture 23 Converting Data (OBJ 1.2)

Lecture 24 Data Structures (OBJ 1.3)

Lecture 25 Data File Formats (OBJ 1.3)

Lecture 26 Data Languages (OBJ 1.3)

Lecture 27 Hands-on with Data Types (OBJ 1.3)

Section 5: Data Acquisition

Lecture 28 Data Acquisition (OBJ 2.1)

Lecture 29 Extracting Data (OBJ 2.1)

Lecture 30 Transforming Data (OBJ 2.1)

Lecture 31 Loading Data (OBJ 2.1)

Lecture 32 Application Programming Interface (API) (OBJ 2.1)

Lecture 33 Web Scraping (OBJ 2.1)

Lecture 34 Machine Data (OBJ 2.1)

Lecture 35 Public Databases (OBJ 2.1)

Lecture 36 Survey Data (OBJ 2.1)

Lecture 37 Sampling and Observation (OBJ 2.1)

Lecture 38 Hands-on with Data Acquisition (OBJ 2.1)

Section 6: Cleansing and Profiling Data

Lecture 39 Cleansing and Profiling Data (OBJ 2.2)

Lecture 40 Data Profiling Steps (OBJ 2.2)

Lecture 41 Data Profiling Tools (OBJ 2.2)

Lecture 42 Redundant and Duplicated Data (OBJ 2.2)

Lecture 43 Unnecessary Data (OBJ 2.2)

Lecture 44 Missing Values (OBJ 2.2)

Lecture 45 Invalid Data (OBJ 2.2)

Lecture 46 Meeting Specifications (OBJ 2.2)

Lecture 47 Data Outliers (OBJ 2.2)

Lecture 48 Hands-on with Cleaning and Profiling Data (OBJ 2.2)

Section 7: Data Manipulation

Lecture 49 Data Manipulation (OBJ 2.3)

Lecture 50 Recoding Data (OBJ 2.3)

Lecture 51 Derived Variables (OBJ 2.3)

Lecture 52 Value Imputation (OBJ 2.3)

Lecture 53 Aggregation and Reduction (OBJ 2.3)

Lecture 54 Data Masking (OBJ 2.3)

Lecture 55 Transposing Data (OBJ 2.3)

Lecture 56 Appending Data (OBJ 2.3)

Lecture 57 Hands-on with Data Manipulation (OBJ 2.3)

Section 8: Performing Data Manipulation

Lecture 58 Performing Data Manipulation (OBJ 2.3 and 2.4)

Lecture 59 Data Blending (OBJ 2.3 and 2.4)

Lecture 60 Parsing Strings (OBJ 2.3 and 2.4)

Lecture 61 Date Manipulation (OBJ 2.3 and 2.4)

Lecture 62 Conditional Logic (OBJ 2.3 and 2.4)

Lecture 63 Aggregation Functions (OBJ 2.3 and 2.4)

Lecture 64 System Functions (OBJ 2.3 and 2.4)

Lecture 65 Hands-on with Performing Data Manipulation (OBJ 2.3 and 2.4)

Section 9: Querying & Filtering Data

Lecture 66 Querying & Filtering Data (OBJ 2.4)

Lecture 67 Querying Data (OBJ 2.4)

Lecture 68 Join Types (OBJ 2.4)

Lecture 69 Filtering Data (OBJ 2.4)

Lecture 70 Parameterization (OBJ 2.4)

Lecture 71 Indexing Data (OBJ 2.4)

Lecture 72 Temporary Tables (OBJ 2.4)

Lecture 73 Subsets of Records (OBJ 2.4)

Lecture 74 Query Execution Plan (OBJ 2.4)

Lecture 75 Hands-on with Querying & Filtering Data (OBJ 2.4)

Section 10: Types of Analysis

Lecture 76 Types of Analysis (OBJ 3.3)

Lecture 77 Determining the Analysis Type (OBJ 3.3)

Lecture 78 Exploratory Analysis (OBJ 3.3)

Lecture 79 Performance Analysis (OBJ 3.3)

Lecture 80 Gap Analysis (OBJ 3.3)

Lecture 81 Trend Analysis (OBJ 3.3)

Lecture 82 Link Analysis (OBJ 3.3)

Lecture 83 Hands-on with Analysis (OBJ 3.3)

Section 11: Descriptive Statistical Methods

Lecture 84 Descriptive Statistical Methods (OBJ 3.1 and 2)

Lecture 85 Central Tendency (OBJ 3.1)

Lecture 86 Dispersion (OBJ 3.1)

Lecture 87 Standard Deviation (OBJ 3.1)

Lecture 88 Z-score (OBJ 3.2)

Lecture 89 Distribution (OBJ 3.1)

Lecture 90 Frequency (OBJ 3.1)

Lecture 91 Percentages (OBJ 3.1)

Lecture 92 Confidence Interval (OBJ 3.1)

Lecture 93 Hands-on with Descriptive Statistical Methods (OBJ 3.1)

Section 12: Inferential Statistical Methods

Lecture 94 Inferential Statistical Methods (OBJ 3.2)

Lecture 95 T-Tests and P-Values (OBJ 3.2)

Lecture 96 Hypothesis Testing (OBJ 3.2)

Lecture 97 Chi-Square (OBJ 3.2)

Lecture 98 Regression Analysis (OBJ 3.2)

Lecture 99 Correlation (OBJ 3.2)

Lecture 100 Hands-on with Inferential Statistical Methods (OBJ 3.2)

Section 13: Visualization Types

Lecture 101 Visualization Types (OBJ 4.4)

Lecture 102 Pie Chart (OBJ 4.4)

Lecture 103 Tree Map (OBJ 4.4)

Lecture 104 Column and Bar Charts (OBJ 4.4)

Lecture 105 Line Chart (OBJ 4.4)

Lecture 106 Combining Charts (OBJ 4.4)

Lecture 107 Scatter Plot and Bubble Chart (OBJ 4.4)

Lecture 108 Histogram (OBJ 4.4)

Lecture 109 Waterfall (OBJ 4.4)

Lecture 110 Geographic Maps (OBJ 4.4)

Lecture 111 Heat Maps (OBJ 4.4)

Lecture 112 Word Clouds and Infographics (OBJ 4.4)

Lecture 113 Hands-on with Visualization (OBJ 4.4)

Section 14: Creating Reports

Lecture 114 Creating Reports (OBJ 4.1, 4.3, and 4.5)

Lecture 115 The Audience (OBJ 4.1 and 4.3)

Lecture 116 Data Sources (OBJ 4.3)

Lecture 117 Data Models (OBJ 4.3)

Lecture 118 Data Fields (OBJ 4.3)

Lecture 119 Data Delivery (OBJ 4.3)

Lecture 120 Reporting Frequency (OBJ 4.1)

Lecture 121 Report Types (OBJ 4.5)

Lecture 122 Hands-on with Creating Reports (OBJ 4.1, 4.3, and 4.5)

Section 15: Creating Dashboards

Lecture 123 Dashboard Development (OBJ 4.1, 4.2, and 4.3)

Lecture 124 Data Filtering (OBJ 4.1 and 4.3)

Lecture 125 Data Tables (OBJ 4.3)

Lecture 126 Dashboard Design (OBJ 4.2)

Lecture 127 Documenting Dashboards (OBJ 4.2)

Lecture 128 Documentation Elements (OBJ 4.2)

Lecture 129 Report Elements (OBJ 4.2)

Lecture 130 Dashboard Optimization (OBJ 4.3)

Lecture 131 Deploying Dashboards (OBJ 4.3)

Lecture 132 Hands-on with Creating Dashboards (OBJ 4.1, 4.2, and 4.3)

Section 16: Data Governance

Lecture 133 Data Governance (OBJ 5.1)

Lecture 134 Data Lifecycle (OBJ 5.1)

Lecture 135 Data Roles (OBJ 5.1)

Lecture 136 Regulations and Compliance (OBJ 5.1)

Lecture 137 Data Classification (OBJ 5.1)

Lecture 138 Access Requirements (OBJ 5.1)

Lecture 139 Data Retention and Destruction (OBJ 5.1)

Lecture 140 Data Processing (OBJ 5.1)

Lecture 141 Data Security (OBJ 5.1)

Lecture 142 Data Access (OBJ 5.1)

Lecture 143 Data Storage (OBJ 5.1)

Lecture 144 Entity Relationships (OBJ 5.1)

Lecture 145 Hands-on with Data Governance (OBJ 5.1)

Section 17: Data Quality

Lecture 146 Data Quality (OBJ 5.2 and 5.3)

Lecture 147 Quality Checks (OBJ 5.2)

Lecture 148 Quality Dimensions (OBJ 5.2)

Lecture 149 Quality Rules and Metrics (OBJ 5.2)

Lecture 150 Data Validation (OBJ 5.2)

Lecture 151 Automated Validation (OBJ 5.2)

Lecture 152 Data Verification (OBJ 5.2)

Lecture 153 Master Data Management (MDM) (OBJ 5.3)

Lecture 154 Streamlining Data Access (OBJ 5.3)

Lecture 155 Hands-on with Data Quality (OBJ 5.3)

Section 18: Data Analytics Tools

Lecture 156 Data Analytics Tools (OBJ 3.4)

Lecture 157 Data Languages (OBJ 3.4)

Lecture 158 Data Transformation Tools (OBJ 3.4)

Lecture 159 Data Visualization Tools (OBJ 3.4)

Lecture 160 Statistical Tools (OBJ 3.4)

Lecture 161 Reporting Tools (OBJ 3.4)

Lecture 162 Platform Tools (OBJ 3.4)

Section 19: Conclusion

Lecture 163 Conclusion

Students preparing for the CompTIA Data+ (DA0-001) Certification Exam,Data Analysts,Database Engineers,Data Scientists,Cybersecurity Professionals,Information Technology Professionals