Database Essentials

• In this course, you will learn to:
• Define the concept of data entry including manual and automated methods.
• Identify the essential skills required to become a proficient data entry operator.
• Organize various job opportunities available for data entry professionals and categorize different types of data entry jobs.
• Summarize the importance of efficient typing techniques and rate the effectiveness of different keyboard layouts.
• Compare and differentiate between various font types and categorize font settings for data entry applications.
• Diagnose typing speed improvement using different techniques and tools, such as finger motions and home row usage.
• Explain the significance of mobile typing skills and predict the impact of predictive text and speech recognition on efficiency.
• Compare different password management techniques, including password managers and algorithms.
• Operate productivity shortcuts for data entry, such as keyboard shortcuts and application navigation techniques.
• Find efficient shortcuts for data entry tasks, including editing, file management, and application navigation.
• Report on the utilization of basic data entry tools like Google Forms and Microsoft Forms for efficient data collection and management.
• Differentiate between basic and smart Google Forms features and predict the impact of advanced form functionalities on data collection efficiency.
• Classify the importance of data cleaning and quality assurance in data management
• Recognize the significance of data accuracy, completeness, consistency, and reliability
• Describe data cleaning concepts to ensure accurate and reliable data
• Modify the impact of data cleaning and quality assurance on data management effectiveness in various applications
• Demonstrate practical data cleaning techniques and tools
• Classify techniques to identify and resolve data errors
• Discuss data cleaning techniques to improve data quality and reliability
• Organize proficiency by identifying and resolving data errors in real-world datasets
• Identify how to ensure data integrity through quality assurance measures
• Find validation techniques to check data against predefined criteria and standards
• Summarize quality assurance measures to maintain data reliability and credibility
• Discuss how data cleaning and quality assurance can enhance decision-making
• Describe the importance of high-quality and accurate data in analysis and insights
• Arrange data cleaning and quality assurance techniques for ensuring reliable data in decision-making
• Explain the impact of data cleaning and quality assurance on decision-making in different domains
• Identify the purpose and benefits of using databases for data storage, retrieval, and management
• Explain the effectiveness of databases in enhancing efficiency and organization in various applications
• Summarize the effectiveness of the database design in upholding data integrity and minimizing redundancy
• Demonstrate SQL skills for querying databases
• Examine proficiency by creating accurate and valuable reports through database querying
• Explain database security and administration practices
• Find techniques for managing user access and implementing security protocols
• Arrange the effectiveness of database security measures in data protection and administration practices
• Identify techniques for optimizing database performance (indexing, query analysis, and configuration)
• Differentiate non-relational databases from traditional relational databases, understanding their unique characteristics
• Reorganize knowledge of non-relational databases to make informed database selection decisions
• Describe data integration and migration techniques for transferring data between databases and systems
• Identify challenges in handling big data in distributed environments
• Demonstrate data governance principles and compliance requirements for database management
• Predict the importance of data privacy, ownership, and regulatory compliance
• Organize the ethical considerations of database management (data privacy, confidentiality, and responsible data handling)
• Categorize ethical considerations in real-world database management to ensure data privacy and confidentiality principles are upheld

• At the end of this course, learners will be able to:
• Interpret the historical evolution of data entry methods and their significance in modern data management.
• Illustrate the essential skills and mindset required to excel as a data entry operator.
• Paraphrase the various types of data entry jobs available, including remote and in-house positions, and estimate the expected salary range for data entry professionals.
• Defend the importance of efficient typing skills and keyboard techniques in data entry operations.
• Compare the role of fonts in data entry and evaluate techniques for font conversion and application settings.
• Review speed typing skills and productivity shortcuts for data entry operators.
• Construct efficient password management techniques and evaluate security measures to safeguard sensitive data in data entry operations.
• Estimate the impact of advanced keyboard shortcuts and productivity techniques on data entry efficiency.
• Predict the effectiveness of mobile typing skills and voice recognition techniques in enhancing data entry speed.
• Survey on various techniques for speeding up data entry tasks, examining their applicability and efficiency in different scenarios.
• Assess the importance of basic data entry principles and productivity shortcuts in enhancing data entry accuracy.
• Create Google Forms and Microsoft Forms for efficient data collection, formulating clear and concise questions and analyzing response data effectively.
• Develop smart Google Forms and Microsoft Forms for specialized purposes such as quizzes, feedback collection and more.
• Review the significance of data cleaning and quality assurance in data management
• Examine the importance of accurate, complete, consistent, and reliable data in various applications
• Prepare practical data-cleaning skills and techniques
• Verify various tools to resolve common data errors (missing values, duplicates, outliers, inconsistent formats)
• Construct data-cleaning techniques into practice for data cleanliness and accuracy
• Devise skills to ensure data integrity through quality assurance measures
• Formulate validation techniques to assess data against predefined criteria and standards
• Prepare quality assurance measures for generating reliable and credible data in different contexts
• Review how data cleaning and quality assurance affect decision-making
• Illustrate the value of high-quality and accurate data for better analysis and insight
• Transform data cleaning and quality assurance to support informed decision-making in various domains
• Interpret the impact of data quality on achieving effective and reliable decision outcomes in real-world situations
• Illustrate fundamental database concepts for data storage, retrieval, and management
• Compare the importance of databases in various applications
• Review skills to design relational databases with data integrity and minimal repetition
• Construct the significance of table structures, primary keys, foreign keys, and normalization for effective database design
• Examine skills in writing and using SQL statements for various database tasks
• Utilize SQL queries to retrieve, insert, update, and delete data
• Create meaningful reports from databases using SQL
• Modify knowledge of database security and administration practices
• Review the importance of managing user access and implementing security protocols
• Construct techniques to optimize database performance (indexing, query analysis, configuration)
• Formulate these techniques for faster and more efficient data processing
• Prepare the concepts of non-relational databases like NoSQL and document-oriented databases
• Develop skills in data integration and migration between databases and systems
• Utilize the skills to integrate and migrate data while ensuring data integrity and consistency
• Interpret big data concepts and distributed databases
• Differentiate challenges in managing large-scale data in distributed environments
• Assess data backups efficiently to protect against data loss
• Manage the importance of data privacy, ownership, and regulatory compliance
• Formulate principles for responsible and ethical database management
• Prepare practical experience in designing, implementing, and managing databases in real-world projects
• Construct data privacy, confidentiality, and responsible data handling

The academic approach of the courses focuses on the “work-centric” education i.e. begin with work (and not from a book!), derive knowledge from work and apply that knowledge to make the work more wholesome, useful and delightful. The ultimate objective is to empower the Learner to engage in socially useful and productive work. It aims at leading the learner to his/her rewarding career as an employee or entrepreneur as well as development of the community to which s/he belongs. Learning methodology:

• Step -1: Learners are given an overview of the course and its connection to life and work.
• Step -2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Step -3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Step -4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
• Step -5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
• Step -6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
• Step -7: Learners are engaged in appreciation of real-life case studies developed by the experts.
• Step -8: Learners are encouraged to proceed from appreciation to imitation of the experts.
• Step -9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Step-10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
• Step-11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
• Step-12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!

Evaluation Pattern of KLiC Courses consists of 4 Sections as per below table:

YCMOU Mark Sheet

Printed Mark Sheet will be issued by YCMOU on successful completion of Section 1, Section 2 and Section 3 and will be delivered to the learner by MKCL.
YCMOU Mark Sheet will be available only for Maharashtra jurisdiction learners

MKCL's KLiC Certificate

The certificate will be provided to the learner who will satisfy the below criteria:

1. Learners who have successfully completed above mentioned 3 Sections i.e. Section 1, Section 2 and Section 3
2. Additionally, learner should have completed Section 4 (i.e. Section 4 will comprise of SUPWs i.e. Socially Useful and Productive Work in form of Assignments)
   • Learner has to complete and upload minimum 2 out of 5 Assignments