DATA ANALYSIS AND MANAGEMENT

TRAINING OVERVIEW

TRAINING TOPICS

• Audits and compliance
• Governing the data life-cycle — from datum to intelligence
• Data analytical methods and programs overview
• Data classification
• Access control
• Risk management: 
• Data protection
• Data quality and integrity
• Mining and reporting
• Data retention
• Technology, tools and achieving results

By the end of this training course, delegates will be able to

• Recognize the significance of ISO standards, particularly ISO 27001 and ISO 8000, for robust data management practices.
• Conduct regular internal and external audits and ensure alignment with ISO 27001 requirements to enhance data governance effectiveness
• Govern the data life-cycle effectively, ensuring security, confidentiality, and integrity of data from Datum to Intelligence.
• Implement data classification based on sensitivity and importance, ensuring compliance with ISO 27001 requirements and enhancing security measures.
• Identify and assess security risks, determine appropriate security measures, and ensure data value and sensitivity in risk management processes.
• Maintain data quality and integrity standards as part of risk management and mitigate risks associated with inaccurate data.
• Utilize data mining and reporting techniques, including data visualization and pattern discovery, to generate actionable insights.
• Implement data retention period policies and safe data retention and disposal methods to ensure regulatory compliance and mitigate risks of data security breaches.
• Utilize technology and tools for unstructured data analytics, database analytics, and project delivery management to achieve desired results in data management and analytics.

TRAINING IS TAILORED TO

• Senior leadership teams with varying levels of data knowledge.
• Business leaders who recognize the value of strong data management.
• Decision makers aiming to leverage business data effectively.
• Organizations seeking to implement robust data management practices.
• IT systems architects and security consultants.
• Professionals responsible for information security management and data quality management.

TRAINING METHODOLOGY

The “Data Analysis and Management” training program by DixonTech offers a dynamic and comprehensive approach to equipping participants with essential skills for effective data analysis and management. Through interactive lectures, workshops, case studies, and practical exercises, participants gain hands-on experience with various analytical methods and programs like the R Framework and Big Data Analytics. Instructors use real-world examples to foster critical thinking. Participants engage in exploratory data analysis, statistical evaluation, and advanced methods such as data clustering and regression analysis. By the training's end, participants are equipped to analyse and manage data effectively, facilitating informed decision-making and driving business success.

DAY 1:

Audits and Compliance:

• Regular internal and external audits
• Data governance alignment with ISO 27001 requirements
• Make audits smoother and more effective

Governing the data life-cycle — From Datum to Intelligence

• Governing the data life-cycle from Datum to Intelligence
• Implement ISO 27001 and ISO 8000 standards
• Continuous improvement exercise for organizations
• Increase effective data governance to the High-level
• Ensuring security, confidentiality, and integrity of data

DAY 2:

DATA ANALYTICAL METHODS AND PROGRAMS OVERVIEW

• Overview of R Framework
• Overview of Big Data Analytics
• Exploratory Data Analysis
• Statistical methods of Evaluation
• Advanced Methods of Clustering
• Advanced Theory and Methods of Association Rules
• Advanced Theory and Methods of Regression
• Case Study and Summary

Data Classification:

• Data governance and data classification
• Classification based on sensitivity and importance
• Crucial for security measures
• Compliance with ISO 27001 requirements
• Different levels of protection for different data types

DAY 3:

Access Control:

• Data governance systems for effective data access
• Permitted procedures and access conditions
• Foundations and procedures for enforcing the implementation of access control
• Permissions to access and modify data

Risk Management:

• Security risk identification and assessment
• Data value and sensitivity
• Risk assessment
• Determine appropriate security measures

DAY 4:

Data Protection:

• Framework for protecting information assets, ISO 27001
• Defining policies, procedures, and controls
• Data protection
• Secure data management

Data Quality and Integrity:

• Fundamentals of maintaining accuracy and reliability of data
• Identifying inaccurate data that lead to security incidents
• Defining data quality and integrity standards as part of risk management

DAY 5:

MINING, Retention:

MINING AND REPORTING

• Data Visualization
• Pattern Discovery in Data Mining
• Data Mining Project
• Generate Reporting Skills

Data Retention:

• Data retention period policies
• Safe data retention and disposal methods
• Vital regulatory compliance
• Risks of data security breaches