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CompTIA Data+ (DA0-001) exam on your 1st attempt, includes full-length practice exam!
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%)
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
Table of Contents
Introduction to CompTIA Data+ (DA0-001)
1 Welcome
2 Download Your Free Study Guide
3 Exam Tips
Data Schemas
4 Data Schemas (OBJ 1.1)
5 Relational Databases (OBJ 1.1)
6 Non-Relational Databases (OBJ 1.1)
7 Comparing Database Types (OBJ 1.1)
8 Data Normalization (OBJ 1.1)
9 Database Relationships (OBJ 1.1)
10 Referential Integrity (OBJ 1.1)
11 Data Denormalization (OBJ 1.1)
12 Hands-on with Data Schemas (OBJ 1.1)
Data Systems
13 Data Systems (OBJ 1.1)
14 Data Processing Types (OBJ 1.1)
15 Data Warehouse (OBJ 1.1)
16 Data Warehouse Schemas (OBJ 1.1)
17 Data Lakes (OBJ 1.1)
18 Changing Dimensional Data (OBJ 1.1)
19 Hands-on with Data Systems (OBJ 1.1)
Data Types
20 Data Types (OBJ 1.2 and1.3)
21 Quantitative & Qualitative (OBJ 1.2)
22 Data Field Types (OBJ 1.2)
23 Converting Data (OBJ 1.2)
24 Data Structures (OBJ 1.3)
25 Data File Formats (OBJ 1.3)
26 Data Languages (OBJ 1.3)
27 Hands-on with Data Types (OBJ 1.3)
Data Acquisition
28 Data Acquisition (OBJ 2.1)
29 Extracting Data (OBJ 2.1)
30 Transforming Data (OBJ 2.1)
31 Loading Data (OBJ 2.1)
32 Application Programming Interface (API) (OBJ 2.1)
33 Web Scraping (OBJ 2.1)
34 Machine Data (OBJ 2.1)
35 Public Databases (OBJ 2.1)
36 Survey Data (OBJ 2.1)
37 Sampling and Observation (OBJ 2.1)
38 Hands-on with Data Acquisition (OBJ 2.1)
Cleansing and Profiling Data
39 Cleansing and Profiling Data (OBJ 2.2)
40 Data Profiling Steps (OBJ 2.2)
41 Data Profiling Tools (OBJ 2.2)
42 Redundant and Duplicated Data (OBJ 2.2)
43 Unnecessary Data (OBJ 2.2)
44 Missing Values (OBJ 2.2)
45 Invalid Data (OBJ 2.2)
46 Meeting Specifications (OBJ 2.2)
47 Data Outliers (OBJ 2.2)
48 Hands-on with Cleaning and Profiling Data (OBJ 2.2)
Data Manipulation
49 Data Manipulation (OBJ 2.3)
50 Recoding Data (OBJ 2.3)
51 Derived Variables (OBJ 2.3)
52 Value Imputation (OBJ 2.3)
53 Aggregation and Reduction (OBJ 2.3)
54 Data Masking (OBJ 2.3)
55 Transposing Data (OBJ 2.3)
56 Appending Data (OBJ 2.3)
57 Hands-on with Data Manipulation (OBJ 2.3)
Performing Data Manipulation
58 Performing Data Manipulation (OBJ 2.3 and 2.4)
59 Data Blending (OBJ 2.3 and 2.4)
60 Parsing Strings (OBJ 2.3 and 2.4)
61 Date Manipulation (OBJ 2.3 and 2.4)
62 Conditional Logic (OBJ 2.3 and 2.4)
63 Aggregation Functions (OBJ 2.3 and 2.4)
64 System Functions (OBJ 2.3 and 2.4)
65 Hands-on with Performing Data Manipulation (OBJ 2.3 and 2.4)
Querying & Filtering Data
66 Querying & Filtering Data (OBJ 2.4)
67 Querying Data (OBJ 2.4)
68 Join Types (OBJ 2.4)
69 Filtering Data (OBJ 2.4)
70 Parameterization (OBJ 2.4)
71 Indexing Data (OBJ 2.4)
72 Temporary Tables (OBJ 2.4)
73 Subsets of Records (OBJ 2.4)
74 Query Execution Plan (OBJ 2.4)
75 Hands-on with Querying & Filtering Data (OBJ 2.4)
Types of Analysis
76 Types of Analysis (OBJ 3.3)
77 Determining the Analysis Type (OBJ 3.3)
78 Exploratory Analysis (OBJ 3.3)
79 Performance Analysis (OBJ 3.3)
80 Gap Analysis (OBJ 3.3)
81 Trend Analysis (OBJ 3.3)
82 Link Analysis (OBJ 3.3)
83 Hands-on with Analysis (OBJ 3.3)
Descriptive Statistical Methods
84 Descriptive Statistical Methods (OBJ 3.1 and 2)
85 Central Tendency (OBJ 3.1)
86 Dispersion (OBJ 3.1)
87 Standard Deviation (OBJ 3.1)
88 Z-score (OBJ 3.2)
89 Distribution (OBJ 3.1)
90 Frequency (OBJ 3.1)
91 Percentages (OBJ 3.1)
92 Confidence Interval (OBJ 3.1)
93 Hands-on with Descriptive Statistical Methods (OBJ 3.1)
Inferential Statistical Methods
94 Inferential Statistical Methods (OBJ 3.2)
95 T-Tests and P-Values (OBJ 3.2)
96 Hypothesis Testing (OBJ 3.2)
97 Chi-Square (OBJ 3.2)
98 Regression Analysis (OBJ 3.2)
99 Correlation (OBJ 3.2)
100 Hands-on with Inferential Statistical Methods (OBJ 3.2)
Visualization Types
101 Visualization Types (OBJ 4.4)
102 Pie Chart (OBJ 4.4)
103 Tree Map (OBJ 4.4)
104 Column and Bar Charts (OBJ 4.4)
105 Line Chart (OBJ 4.4)
106 Combining Charts (OBJ 4.4)
107 Scatter Plot and Bubble Chart (OBJ 4.4)
108 Histogram (OBJ 4.4)
109 Waterfall (OBJ 4.4)
110 Geographic Maps (OBJ 4.4)
111 Heat Maps (OBJ 4.4)
112 Word Clouds and Infographics (OBJ 4.4)
113 Hands-on with Visualization (OBJ 4.4)
Creating Reports
114 Creating Reports (OBJ 4.1, 4.3, and 4.5)
115 The Audience (OBJ 4.1 and 4.3)
116 Data Sources (OBJ 4.3)
117 Data Models (OBJ 4.3)
118 Data Fields (OBJ 4.3)
119 Data Delivery (OBJ 4.3)
120 Reporting Frequency (OBJ 4.1)
121 Report Types (OBJ 4.5)
122 Hands-on with Creating Reports (OBJ 4.1, 4.3, and 4.5)
Creating Dashboards
123 Dashboard Development (OBJ 4.1, 4.2, and 4.3)
124 Data Filtering (OBJ 4.1 and 4.3)
125 Data Tables (OBJ 4.3)
126 Dashboard Design (OBJ 4.2)
127 Documenting Dashboards (OBJ 4.2)
128 Documentation Elements (OBJ 4.2)
129 Report Elements (OBJ 4.2)
130 Dashboard Optimization (OBJ 4.3)
131 Deploying Dashboards (OBJ 4.3)
132 Hands-on with Creating Dashboards (OBJ 4.1, 4.2, and 4.3)
Data Governance
133 Data Governance (OBJ 5.1)
134 Data Lifecycle (OBJ 5.1)
135 Data Roles (OBJ 5.1)
136 Regulations and Compliance (OBJ 5.1)
137 Data Classification (OBJ 5.1)
138 Access Requirements (OBJ 5.1)
139 Data Retention and Destruction (OBJ 5.1)
140 Data Processing (OBJ 5.1)
141 Data Security (OBJ 5.1)
142 Data Access (OBJ 5.1)
143 Data Storage (OBJ 5.1)
144 Entity Relationships (OBJ 5.1)
145 Hands-on with Data Governance (OBJ 5.1)
Data Quality
146 Data Quality (OBJ 5.2 and 5.3)
147 Quality Checks (OBJ 5.2)
148 Quality Dimensions (OBJ 5.2)
149 Quality Rules and Metrics (OBJ 5.2)
150 Data Validation (OBJ 5.2)
151 Automated Validation (OBJ 5.2)
152 Data Verification (OBJ 5.2)
153 Master Data Management (MDM) (OBJ 5.3)
154 Streamlining Data Access (OBJ 5.3)
155 Hands-on with Data Quality (OBJ 5.3)
Data Analytics Tools
156 Data Analytics Tools (OBJ 3.4)
157 Data Languages (OBJ 3.4)
158 Data Transformation Tools (OBJ 3.4)
159 Data Visualization Tools (OBJ 3.4)
160 Statistical Tools (OBJ 3.4)
161 Reporting Tools (OBJ 3.4)
162 Platform Tools (OBJ 3.4)
Conclusion
163 Conclusion
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