CompTIA Data+
The CompTIA Data+ Course is designed to provide participants with the skills and knowledge needed to work with data and analytics in a wide variety of business and technology contexts. The course focuses on acquiring skills for collecting, processing, analyzing and visualizing data, as well as techniques for using data and information to improve decision making and solve business problems. During the course, participants will learn to work with data management tools and technologies, including databases, data warehouses, data lakes and analytics platforms. The course also covers the main methodologies for data analysis, such as statistics, machine learning and artificial intelligence. Additionally, participants will be trained on how to interpret and communicate analysis results clearly and effectively to various business stakeholders. The course contributes to the preparation of the CompTIA Data+ Certification exam .
Course Objectives
The main objectives of the CompTIA Data+ are:
- Acquire skills in data collection and processing.
- Analyze and visualize data to support decision making.
- Learn the use of data management tools and technologies.
- Understand key methodologies for data analysis.
- Interpret and communicate analysis results to various stakeholders.
- Learn best practices and techniques for ensuring data security and privacy throughout the data collection, processing, and analysis stages.
- Explore strategies to optimize data storage, retrieval, and processing performance to ensure efficient data handling and analysis workflows.
- Understand ethical considerations and compliance requirements related to data usage, including data governance, regulatory compliance, and ethical handling of sensitive information.
Upon completion of the course, individuals should be able to take Security+ (SY0-701) Exam to achieve the CompTIA Server+ Certification.
Course Certification
This course helps you prepare to take the:
DA0-001 CompTIA Data+ exam
Course Outline
Introduction to Data Concepts
- The data landscape and its importance
- Types of data: structured, unstructured, and semi-structured
- Data lifecycle and management
Data Storage and Management
- Database systems: relational, NoSQL, and graph databases
- Data warehousing and data lakes
- Data storage formats and technologies
Data Processing and Transformation
- Data extraction, transformation, and loading (ETL) processes
- Data cleaning and preprocessing techniques
- Data integration and consolidation
Data Analysis and Exploration
- Descriptive, diagnostic, predictive, and prescriptive analytics
- Statistical analysis methods and techniques
- Data visualization tools and techniques
Machine Learning and Artificial Intelligence
- Supervised, unsupervised, and reinforcement learning algorithms
- Model evaluation and selection
- Feature engineering and selection
Big Data Technologies and Frameworks
- Distributed data storage and processing systems
- Hadoop ecosystem and Spark framework
- Real-time data processing and streaming analytics
Data Privacy and Security
- Data governance and compliance
- Data privacy and protection principles
- Security measures for data storage and processing
Data Quality and Governance
- Data quality dimensions and assessment
- Data cataloging and metadata management
- Data lineage and traceability
Cloud-based Data Solutions
- Cloud-based data storage and processing services
- Data analytics platforms in the cloud
- Cloud data security and best practices
Data-driven Decision Making and Communication
- Interpreting and presenting data analysis results
- Communicating insights to various stakeholders
- Data-driven decision making and problem solving
Laboratory Activities
- Exploring the Lab Environment
- Navigating and Understanding Database Design
- Understanding Data Types and Conversion
- Working with Different File Formats
- Understanding Data Structure and Types and Using Basic Statements
- Using Public Data
- Profiling Data Sets
- Addressing Redundant and Duplicated Data
- Addressing Missing Values
- Preparing Data for Use
- Recoding Data
- Working with Queries and Join Types
- Building Queries and Transforming Data
- Using the Measures of Central Tendency
- Using the Measures of Variability
- Analyzing Data
- Building Basic Visuals to Make Visual Impact
- Building Maps with Geographical Data
- Using Visuals to Tell a Story
- Filtering Data
- Designing Elements for Dashboards
- Building an Ad Hoc Report
- Visualizing Data
- Understanding Security Requirements for Protecting Information
Course Mode
Instructor-Led Remote Live Classroom Training;
Trainers
Trainers are CompTIA Official Instructors and certified in other IT technologies, with years of hands-on experience in the industry and in Training.
Lab Topology
For all types of delivery, the student can access the equipment and systems present in our laboratories or directly at the data centers of the Vendor or its authorized providers remotely 24 hours a day . Each participant has access to implement the various configurations thus having practical and immediate feedback on the theory addressed.
Course Details
Course Prerequisites
There are no prerequisites.
Course Duration
Intensive duration 5 days
Course Frequency
Course Duration: 5 days (9.00 to 17.00) - Ask for other types of attendance.
Course Date
- CompTIA Data+ Course (Intensive Formula) – On request – 09:00 – 17:00
Steps to Enroll
Registration takes place by asking to be contacted from the following link, or by contacting the office at the international number +355 45 301 313 or by sending a request to the email info@hadartraining.com
