Comptia Data+ (Da0-001) | Comptia Data Certification Course

CompTIA Data - Learn Data Concepts, Data Visualization, Data Analysis & Statistics and pass the Data+ certification exam

What you'll learn

Comptia Data+ gives you the confidence to bring data analysis to life.

Take and pass the CompTIA Data+ (DA0-001) certification exam

Data Mining

Data Analysis

Data Visualization

Data Governance, Quality, & Controls

Data Schemas

Relational Databases Schemas

Non-Relational Databases

Comparing Databases

Data Processing(OLTP & OLAP)

Data Warehouse, Data Mart

Schema Consepts (Snowflake & Star)

Data Lake

Slowly changing dimensions

Quantitative Data, Qualitative Data

Data Types

Can we convert data types?

Data Structures

Data File Formats-Text/Flat File

Review Data Languages

Explain data acquisition concepts

Extracting Data

Transforming Data

Loading Data(Full Load & Delta Load)

Application programming interfaces (APIs)

Web Scraping

Machine Data

Public Data

Survey Data

Sampling & Observation

Cleansing and Profiling Datasets

Data Profiling Steps

Tools that Simplify The Data Profiling Process

Redundant Data

Dublicate Data

Missing Values

Invalid Data

Non-parametric Data

Data Outliers

Specification mismatch

Data Manipulation Techniques.

Recording Data

Derived Variables

Data Blending

Concatenation

Data Append

Value İmputation

Reduction/Aggregation

Filtering

Data Sorting

Date Functions

Logical functions

Aggregate Functions

System Functions

Query Optimization

Parameterization

Indexing

Temporary table in the query set

Subset of records

Execution Plan

Data Analysis

Exploratory Data Analysis(EDA)

Sentiment Analysis

Perfomance Analysis

Diagnostic Analysis

Gap Analysis

Trend Analysis

Link Anlysis

Descriptive Statistical Methods

Measures of Central Tendency (Mean, Median, Mode)

Why is Central Tendency Important?

Measures of dispersion

Frequencies/Percentages

Percent change / Percent Difference

Confidence intervals

Inferential Statistical Methods

T-tests

P-Values

Z-Score

Chi-squared

Hypothesis Testing

Linear Regression

Correlation

Data Analytics Tools

Excel-Tableau

Power BI ve Rapid Mine

Data Visualization Tools(Qlik, AWS QuickSight, ArcGIS)

Statistical Tools

SAS, IBMSPSS

Stata, Minitab

Reporting Tools

SSRS, Crystal Reports ve Power BI

Platform Tools

Business Objects, MicroStrategy

Oracles Apex, Dataroma

Cognos, Rapid Miner

Oracle Analytics, Domo ve Microsoft Power platform

Creating Reports

Data Content

Data Filtering

Data Sorting

Views

Data Range

Frequency

Audience for Report

Creating Dashboards

Report cover page

Design Elements

Documentation Elements

Dashboard Considerations

Data sources and attributes

Continuous/live Data Feed vs. Static Data

Development Process

Mockup/wireframe

Approval granted

Develop Dashboard

Deploy to production

Subscription and Scheduled delivery

Interactive

Static & Web interface

Dashboard optimization & Access permissions

Visualization Type

Line Chart

Pie Chart – Bubble Chart

Scatter Plot-Bar Chart

Histogram-Waterfall

Heat map - Geographic map

Tree map - Stacked chart

Infographic - Word cloud

Compare and contrast types of reports.

Static vs. dynamic reports

Ad-hoc/one-time report

Self-service/on demand

Recurring Reports

Tactical/Research report

Data Governance, Quality, and Controls

Data Lifecycle

Data Roles

Access Requirements

Security Requirements

Storage environment requirements

Use Requirements

Data Process

Data Retention

Entity Relationship Requirements

Data Classification

Jurisdiction Requirements

Data Breach Reporting

Data Quality Control Concepts

Circumstances to check for quality

Automated Validation

Data Quality Dimensions

Data quality rule and metrics

Cross validation & Sample/Spot Check

Reasonable expectations & Data profiling

Data audits & Peer Review

Explain master data management (MDM) concepts.

Processes

Circumstances for MDM

Data Concepts and Environments

Requirements

Basic Knowledge of Mathematics

Any device where you can watch the lesson, such as a mobile phone, computer or tablet.

Internet Connection

Understand how to read graphs

Learning determination and patience.

Watch the course videos completely and in order.

Description

comptia data+, comptia data, comptia, data+, comptia data, comptia data certification course, comptia data certification, da0-001, data analytics, data analyst, data analysis, statistics, data science, data visualizationEXPLANATIONHello there,Welcome to the " CompTIA Data+ (DA0-001) | CompTIA Data Certification Course " CourseCompTIA Data - Learn Data Concepts, Data Visualization, Data Analysis & Statistics and pass the Data+ certification examData analytics is now central to the day-to-day operations of so many businesses. In all sectors, companies and institutions are using data analytics tools to more efficiently manage supply chains, customer relations and manufacturing, and more.It’s not just businesses that are making an investment in improving their data management capabilities. Educational institutions like school districts and universities are collecting more data than ever before to provide effective and equitable services to a diverse student population. The healthcare sector is no different, looking for ways to manage patient data to improve outcomes and allocate resources.It’s no surprise that finding qualified and highly competent data analysts is a top priority for the principal stakeholders of these companies and institutions. If you are looking to advance in your career or find a more challenging and rewarding job role, the CompTIA Data + Certification is something you’ll want to add to your resume.The CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making.This certification tests your ability to better analyze and interpret data, communicate insights, and demonstrate competency in the world of data analytics.COMPTIA DATA+ GIVES YOU THE CONFIDENCE TO BRING DATA ANALYSIS TO LIFE.Differentiate yourself with Comptia Data+, better analyze and interpret Data.Better highlight what’s important in reports that persuade, not confuse. Make better data-driven decisions.Data literacy increases your competence and makes you more employable.COMPTIA DATA+ PROVES YOU HAVE THE SKILLS REQUIRED TO FACILITATE DATA-DRIVEN BUSINESS DECISIONS.What Skills Will You Learn?Data Concepts and Environments: Boost your knowledge in identifying basic concepts of data schemas and dimensions while understanding the difference between common data structures and file formatsData Mining: Grow your skills to explain data acquisition concepts, reasons for cleansing and profiling datasets, executing data manipulation, and understanding techniques for data manipulationData Analysis: Gain the ability to apply the appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniquesVisualization: Learn how to translate business requirements to create the appropriate visualization in the form of a report or dashboard with the proper design componentsData Governance, Quality, & Controls: Increase your ability to summarize important data governance concepts and apply data quality control conceptsJobs You Can Land With CompTIA Data+ :Data ArchitectData AnalystData ScientistBusiness Analyst ReportingAnalyst Operations AnalystThe CompTIA Data+ exam will certify the successful candidate has the knowledge and skills required to transform business requirements in support of data-driven decisions through mining and manipulating data, applying basic statistical methods, and analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle.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.This course will provide you with full coverage of the five domains of the CompTIA Data+ (DA0-001) Certification exam:Data Concepts and Environments (15%)Data Mining (25%)Data Analysis (23%Visualization (23%)Data Governance, Quality, & Controls (14%)FAQs about CompTIA Data+What is CompTIA Data+?CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making.What is the difference between Data+ and DataSys+?While both certifications are in the field of data management, the CompTIA DataSys+ is designed for database administrators, and the CompTIA Data+ is tailored for data analysts.How difficult is the CompTIA Data+ exam?If you are considering a career in data, the CompTIA Data+ certification is a great way to get started. It is a challenging exam, but it is well worth the effort. By passing the CompTIA Data+ exam, you will demonstrate your skills and knowledge to employers and set yourself up for success in a growing field.Is CompTIA data Plus worth IT?Acquiring the CompTIA Data+ certification positions you as a valuable asset for prospective employers. Across diverse sectors, including technology, healthcare, finance, and marketing, there is a demand for individuals capable of deciphering extensive data and transforming it into actionable business insights.Why do you want to take this Course?Our answer is simple: The quality of teaching.London-based OAK Academy is an online training company. OAK Academy provides IT, Software, Design, and development training in English, Portuguese, Spanish, Turkish, and many languages on the Udemy platform, with over 1000 hours of video training courses.OAK Academy not only increases the number of training series by publishing new courses but also updates its students about all the innovations of the previously published courses.When you sign up, you will feel the expertise of OAK Academy's experienced developers. Our instructors answer questions sent by students to our instructors within 48 hours at the latest.Quality of Video and Audio ProductionAll our videos are created/produced in high-quality video and audio to provide you with the best learning experience.In this course, you will have the following:• Lifetime Access to the Course• Quick and Answer in the Q&A Easy Support• Udemy Certificate of Completion Available for Download• We offer full support by answering any questions.Now dive into the " CompTIA Data+ (DA0-001) | CompTIA Data Certification Course " CourseCompTIA Data - Learn Data Concepts, Data Visualization, Data Analysis & Statistics and pass the Data+ certification examWe offer full support by answering any questions.See you at the Course!

Overview

Section 1: Identify basic concepts of data schemas and dimensions

Lecture 1 Data Schemas

Lecture 2 Relational Databases Schemas

Lecture 3 Non-Relational Databases

Lecture 4 Comparing Databases

Lecture 5 Data Processing(OLTP & OLAP)

Lecture 6 Data Warehouse

Lecture 7 Data Mart

Lecture 8 Schema Concepts(Snowflake & Star)

Lecture 9 Data Lake

Lecture 10 Slowly changing dimensions

Section 2: Compare and contrast different data types

Lecture 11 Quantitative Data

Lecture 12 Qualitative Data

Lecture 13 Data Types

Lecture 14 Can we convert data types?

Section 3: Compare and contrast common data structures and file formats

Lecture 15 Data Structures

Lecture 16 Data File Formats-Text/Flat File

Lecture 17 Review Data Languages: Lesson 1

Lecture 18 Review Data Languages: Lesson 2

Section 4: Explain data acquisition concepts

Lecture 19 Explain data acquisition concepts

Lecture 20 Extracting Data

Lecture 21 Transforming Data

Lecture 22 Loading Data(Full Load & Delta Load)

Lecture 23 Application programming interfaces (APIs)

Lecture 24 Web Scraping

Lecture 25 Machine Data

Lecture 26 Public Data

Lecture 27 Survey Data

Lecture 28 Sampling & Observation

Section 5: Cleansing and Profiling Datasets

Lecture 29 Cleansing and Profiling Datasets

Lecture 30 Data Profiling Steps

Lecture 31 Tools that Simplify The Data Profiling Process

Lecture 32 Redundant Data

Lecture 33 Dublicate Data

Lecture 34 Missing Values

Lecture 35 Invalid Data

Lecture 36 Non-parametric Data

Lecture 37 Data Outliers

Lecture 38 Specification mismatch

Section 6: Data Manipulation Techniques.

Lecture 39 Data Manipulation Techniques.

Lecture 40 Recording Data

Lecture 41 Derived Variables

Lecture 42 Data Merge

Lecture 43 Data Blending

Lecture 44 Concatenation

Lecture 45 Data Append

Lecture 46 Value İmputation

Lecture 47 Reduction/Aggregation

Section 7: Common Techniques for Data Manipulation

Lecture 48 Filtering

Lecture 49 Data Sorting

Lecture 50 Date Functions

Lecture 51 Logical functions

Lecture 52 Aggregate Functions

Lecture 53 System Functions

Lecture 54 Query OptimizationQuery Optimization

Lecture 55 Parameterization

Lecture 56 Indexing

Lecture 57 Temporary table in the query set

Lecture 58 Subset of records

Lecture 59 Execution Plan

Section 8: Summarize types of analysis and key analysis techniques.

Lecture 60 Data Analysis

Lecture 61 Exploratory Data Analysis(EDA)

Lecture 62 Sentiment Analysis

Lecture 63 Perfomance Analysis

Lecture 64 Diagnostic Analysis

Lecture 65 Gap Analysis

Lecture 66 Trend Analysis

Lecture 67 Link Anlysis

Section 9: Descriptive Statistical Methods

Lecture 68 Descriptive Statistical Methods

Lecture 69 Measures of Central Tendency(Mean, Median, Mode)

Lecture 70 Why is Central Tendency Important?

Lecture 71 Measures of dispersion

Lecture 72 Frequencies/Percentages

Lecture 73 Percent change / Percent Difference

Lecture 74 Confidence intervals

Section 10: Inferential Statistical Methods

Lecture 75 Inferential Statistical Methods

Lecture 76 T-tests

Lecture 77 Z-Score

Lecture 78 P-Values

Lecture 79 Chi-squared

Lecture 80 Hypothesis Testing

Lecture 81 Linear Regression

Lecture 82 Correlation

Section 11: Data Analytics Tools

Lecture 83 Data Analytics Tools

Lecture 84 Data Transformation Tools(Excel-Tableau)

Lecture 85 Data Transformation Tools(Power BI ve Rapid Miner)

Lecture 86 Data Visualization Tools(Tableau, Power BI)

Lecture 87 Data Visualization Tools(Qlik, AWS QuickSight, ArcGIS)

Lecture 88 Statistical Tools

Lecture 89 Statistical Tools(SAS, IBMSPSS)

Lecture 90 Statistical Tools(Stata, Minitab)

Lecture 91 Reporting Tools

Lecture 92 Reporting Tools(SSRS, Crystal Reports ve Power BI)

Lecture 93 Platform Tools

Lecture 94 Platform Tools(Business Objects, MicroStrategy)

Lecture 95 Platform Tools(Oracles Apex, Dataroma)

Lecture 96 Platform Tools(IBM Cognos, Rapid Miner)

Lecture 97 Platform Tools(Oracle Analytics, Domo ve Microsoft Power platform)

Section 12: Translate business requirements to form a report

Lecture 98 Creating Reports

Lecture 99 Data Content

Lecture 100 Data Filtering

Lecture 101 Data Sorting

Lecture 102 Views

Lecture 103 Data Range

Lecture 104 Frequency

Lecture 105 Audience for Report

Section 13: Use Appropriate Design Components For Reports And Dashboards.

Lecture 106 Creating Dashboards

Lecture 107 Report cover page

Lecture 108 Design Elements: Lesson 1

Lecture 109 Design Elements: Lesson 2

Lecture 110 Documentation Elements

Section 14: Use Appropriate Methods For Dashboard Development

Lecture 111 Dashboard Considerations

Lecture 112 Data sources and attributes

Lecture 113 Continuous/live Data Feed vs. Static Data

Lecture 114 Development Process

Lecture 115 Mockup/wireframe

Lecture 116 Approval granted

Lecture 117 Develop Dashboard

Lecture 118 Deploy to production

Lecture 119 Subscription and Scheduled delivery

Lecture 120 Interactive

Lecture 121 Static & Web interface

Lecture 122 Dashboard optimization & Access permissions

Section 15: Apply the appropriate type of visualization.

Lecture 123 Visualization Type

Lecture 124 Line Chart

Lecture 125 Pie Chart – Bubble Chart

Lecture 126 Scatter Plot-Bar Chart

Lecture 127 Histogram-Waterfall

Lecture 128 Heat map - Geographic map

Lecture 129 Tree map - Stacked chart

Lecture 130 Infographic - Word cloud

Section 16: Compare and contrast types of reports

Lecture 131 Compare and contrast types of reports.

Lecture 132 Static vs. dynamic reports

Lecture 133 Ad-hoc/one-time report

Lecture 134 Self-service/on demand

Lecture 135 Recurring Reports

Lecture 136 Tactical/Research report

Section 17: Data Governance, Quality, and Controls

Lecture 137 Data Governance, Quality, and Controls

Lecture 138 Data Lifecycle

Lecture 139 Data Roles

Section 18: Summarize important data governance concepts.

Lecture 140 Access Requirements

Lecture 141 Security Requirements

Lecture 142 Storage Environment Requirements

Lecture 143 Use Requirements

Lecture 144 Data Process

Lecture 145 Data Retention

Lecture 146 Entity Relationship Requirements

Lecture 147 Data Classification

Lecture 148 Jurisdiction Requirements

Lecture 149 Data Breach Reporting

Section 19: Apply data quality control concepts.

Lecture 150 Data Quality Control Concepts

Lecture 151 Circumstances to check for quality: Lesson 1

Lecture 152 Circumstances to check for quality: Lesson 2

Lecture 153 Circumstances to check for quality: Lesson 3

Lecture 154 Automated Validation

Lecture 155 Data Quality Dimensions

Lecture 156 Data quality rule and metrics

Lecture 157 Cross validation & Sample/Spot Check

Lecture 158 Reasonable expectations & Data profiling

Lecture 159 Data audits & Peer Review

Section 20: Explain Master Data Management (MDM) concepts.

Lecture 160 Explain master data management (MDM) concepts.

Lecture 161 Processes

Lecture 162 Circumstances for MDM

Section 21: CompTIA Data+ DA0-001 Practice Exam

Section 22: Extra

Lecture 163 CompTIA Data+ (DA0-001) | CompTIA Data Certification Course

Students preparing for the CompTIA Data+ (DA0-001) Certification,CompTIA Data+ is an ideal certification for not only data-specific careers, but also other career paths that benefit from analytics processes and data analytics knowledge.,Jobs like marketing specialists, financial analysts, human resource analysts or clinical health care analysts can optimize performance and make well-informed decisions when they use and evaluate data correctly with Comptia Data+,Data Scientists,Data Analysts,Data Manager,Data Specialist,Database Engineers,Information Technology Professionals