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CompTIA Data+ gives you the confidence to bring data analysis to life.  \nAs the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making.  \nWho Should Attend The CompTIA Data+ course is ideal for professionals aiming to  \ncultivate foundational data analytics skills. This course is particularly well-suited for individuals in roles such as business analysts, marketing professionals, data analysts, and IT professionals who are responsible for managing data insights within their organizations. Additionally, it serves as an excellent starting point for those looking to transition into data-centric roles or enhance their understanding of data analysis and interpretation. This certification can be a stepping stone for anyone seeking to improve their data fluency and support data-driven  \ndecision-making processes in their career.  \nCourse Prerequisites There are no prerequisites for this course.  \nCourse Objectives Upon successful completion of this course, students will be able  \nto:  \nMining data  \nManipulating data  \nVisualizing and reporting data  \nApplying basic statistical methods  \nAnalyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle  \nAgenda 1 – Identifying Basic Concepts of Data Schemas  \nIdentify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization  \n2 – Understanding Different Data Systems  \nDescribe Types of Data Processing and Storage Systems Explain How Data Changes  \n3 – Understanding Types and Characteristics of Data  \nUnderstand Types of Data  \nBreak Down the Field Data Types  \n4 – Comparing and Contrasting Different Data Structures, Formats, and Markup Languages  \nDifferentiate between Structured Data and Unstructured Data Recognize Different File Formats  \nUnderstand the Different Code Languages Used for Data  \n5 – Explaining Data Integration and Collection Methods  \nUnderstand the Processes of Extracting, Transforming, and Loading Data  \nExplain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data  \nUse and Collect Survey Data  \n6 – Identifying Common Reasons for Cleansing and Profiling Data  \nLearn to Profile Data  \nAddress Redundant, Duplicated, and Unnecessary Data Work with Missing Value  \nAddress Invalid Data  \nDSDT 888-688-4234 [info@dsdt.edu](info@dsdt.edu)  \nConvert Data to Meet Specifications  \n7 – Executing Different Data Manipulation Techniques  \nManipulate Field Data and Create Variables Transpose and Append Data  \nQuery Data  \n8 – Explaining Common Techniques for Data Manipulation and Optimization  \nUse Functions to Manipulate Data  \nUse Common Techniques for Query Optimization  \n9 – Applying Descriptive Statistical Methods  \nUse Measures of Central Tendency Use Measures of Dispersion  \nUse Frequency and Percentages  \n10 – Describing Key Analysis Techniques Get Started with Analysis  \nRecognize Types of Analysis  \n11 – Understanding the Use of Different Statistical Methods  \nUnderstand the Importance of Statistical Tests Break Down the Hypothesis Test  \nUnderstand Tests and Methods to Determine Relationships Between Variables  \n12 – Using the Appropriate Type of Visualization  \nUse Basic Visuals  \nBuild Advanced Visuals  \nBuild Maps with Geographical Data Use Visuals to Tell a Story  \n13 – Expressing Business Requirements in a Report Format  \nConsider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting  \nDescribe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards  \nUnderstand Ways to Sort and Filter Data  \n14 – ","cbCailXYx4AA0AtP","https://ap.wps.com/l/cbCailXYx4AA0AtP","pdf",115516,"English","# Agenda\n## Identifying Basic Concepts of Data Schemas\n## Understanding Different Data Systems\n## Understanding Types and Characteristics of Data\n## Comparing and Contrasting Data Structures and Formats\n## Explaining Data Integration and Collection Methods\n## Identifying Common Reasons for Cleansing and Profiling Data\n## Executing Data Manipulation Techniques\n## Data Manipulation and Optimization\n## Descriptive Statistical Methods\n## Key Analysis Techniques\n## Statistical Methods and Hypothesis Testing\n## Data Visualization Techniques\n## Reporting and Dashboard Requirements\n## Designing Report and Dashboard Components\n## Deployment Considerations\n## Data Governance\n## Applying Quality Control to Data\n## Master Data Management Concepts","[{\"question\":\"Who is the CompTIA Data+ course designed for?\",\"answer\":\"It is ideal for professionals building foundational data analytics skills, including business analysts, marketing professionals, data analysts, and IT professionals managing data insights. It also supports people transitioning into data-centric roles or improving data analysis understanding.\"},{\"question\":\"Are there any prerequisites for the course?\",\"answer\":\"The course has no prerequisites.\"},{\"question\":\"What will learners be able to do after completing the course?\",\"answer\":\"Learners can mine, manipulate, visualize, and report data, apply basic statistical methods, and analyze complex datasets while following governance and quality standards across the full data life cycle.\"}]","CAREER SKILLS™ Course Outline - Data+ - CompTIA Data+ | PDF",1789882044]