Course description
Data is an asset that must be understood and used effectively for a company to succeed. As data volumes and complexities increase, data professionals must be able to understand the business needs of their organizations. The data professional is a key member of the data analytics workforce with significant influence on the effectiveness of a data-driven organization. With data analytics at the center of the Information Age, data management professionals can make a difference in their organizations by providing strategic insight and business intelligence.
What are the duties of a data management professional?
The data manager’s role is to oversee the development and use of a company’s data systems and networks, which includes maintaining the security of customer information and ensuring that company data is stored, processed, and analyzed professionally. They also need to have a strong knowledge of data management techniques and practices, such as data cleansing and profiling. Data professionals must be able to identify and solve problems that arise when data isn’t being used effectively, such as when data is being duplicated or when there isn’t enough data to make an informed decision. The professionals must identify when data needs to be retrieved from an external source, such as a database, and ensure that the data is being accessed reliably. They are required to effectively identify potential issues with data security and ensure that measures are in place to secure the same.
Upcoming start dates
Suitability - Who should attend?
Who should attend?
The course is a pre-requisite for individuals looking to shape themselves as an asset for their data-centric organizations:
- Data analysts
- Chief Data Officers
- Data Governance managers
- Data Scientists
- Data administrators
- Business analysts
- Managers and professionals from different walks of life
- Financial analysts/financial statement analysts
- Quantitative analysts
- Finance managers/strategic managers
- Entrepreneurs
Outcome / Qualification etc.
The course objective is to build the capacity and knowledge of Data Management Professionals in the field:
- Gain relevant knowledge, capabilities, and experience sought greatly in the field
- Learn the fundamentals of data management and the way data is collected, stored, organized and utilized in the organization
- Get familiar with the data and identify creative solutions for how to use it to reach your goals
- Understand ways to effectively navigate through the latest database software
- Learn to develop data reports and build-in forms
- Gain an understanding of the interrelation of different database components
- Learn to identify how data collected caters to the need of the organization
- Get acquainted with concepts of data ethics and data governance and how it affects organizations in modern times
Training Course Content
Module 1: Overview of data management
- What is data?
- Creating a data management strategy
- Need for data management in modern organizations
- Treating data capital as business capital
- Data management platforms
- Skills Needed for data management professionals
Module 2: Database Management Systems
- Relational databases
- Database architecture
- Role of a database administrator
- Types of database systems
- File vs database approach to data management
- Elements of database systems
Module 3: Hot Skills for Data Management Professionals
- Identifying patterns
- Analyzing data
- Navigating through database software
- Maintaining data integrity
- Database designing and planning
Module 4: Best Data Management Practices Followed by Professionals
- Creating a discovery layer
- Developing a data science environment
- Use of AI and machine learning
- Converged database
- Using a common query layer
Module 5: Types of Data Management
- Master Data Management
- Data Stewardship
- Data Quality Management
- Big Data Management
Module 6: Data Security
- Methods of securing data
- Visualizing security data
- Data security technologies: data encryption, data masking
- Data resilience
Module 7: Data Governance
- Need for Data Governance in businesses
- Data Governance delivery framework
- Case study on data Governance
Module 8: Data Management Processes
- Cloud data management
- Data Analytics and data visualization
- Extract, transform and load
- Data Integration
- Reference data management
- Data warehousing (OLAP) and Data Mining
Module 9: Data Management Platforms
- Document databases
- ER model databases
- Network databases
- Graph databases
- Utility of DMPs (Data management platforms)
Module 10: Data Management Challenges
- Lack of data insight
- Maintaining performance levels of data management
- Compliance regulations
- Unstructured to structured data
- Fostering data culture in the organization
Module 11: Fostering Data Science Environment
- Communicating with stakeholders
- Incorporating data management activities
- Developing data preservation strategies
Module 12: Organisational Aspect of Data Management
- Metadata modeling
- Data quality data quality dimensions
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