3-Day Instructor-Led Training
Hands-on Labs
After-Course Instructor Coaching Included
Available for Private Team Training
Mastering Data Stewardship: Hands-On
Course 1287
- Duration: 3 days
- Labs: Yes
- Language: English
- Level: Foundation
Unlock the power of data with our intensive 3-day Data Steward course. Designed for data professionals, this hands-on program covers essential topics such as Data Management, Data Governance, Data Analytics, Data Modelling, and Modern Data Architecture.
Gain practical experience through real-world exercises and learn to leverage industry standards, best practices, and cutting-edge technologies. This course will equip you with the skills and knowledge necessary to effectively manage and govern your organization's data assets.
Mastering Data Stewardship Training Delivery Methods
In-Person
Online
Upskill your whole team by bringing Private Team Training to your facility.
Mastering Data Stewardship Training Course Information
In this course, you will:
- Dive deep into data fundamentals, management, governance, analytics, modelling, and architecture.
- Apply your knowledge with practical exercises using common data storage, analytics, and modelling services.
- Learn the latest standards, processes, and technologies from experienced instructors.
- Enhance your skills and advance your career as a data professional with roles like Data Architect, Data Engineer, and Data Modeler.
- Understand the policies, procedures, and roles critical for managing data security, integrity, and compliance.
- Stay current with scalable data lakes, purpose-built analytics services, and unified data access and governance solutions.
Training Prerequisites
- Attendees should understand the basic concepts of data management, core data services and technologies, and how the cloud can be used for data management.
- Experience with Microsoft Azure Portal would be beneficial.
Mastering Data Stewardship Training Outline
Data Overview
Databases
Data Lakes
Data Warehouses
Data Analytics
Machine Learning and Artificial Intelligence
Business Insights
Data Management Overview
- Collecting, storing, securing, and using an organization’s data
- Data quality management
- Data distribution and consistency
- Big data management
- Data architecture and data modeling
Data Management Organizations
- Data Management Association (DAMA)
Data Management Roles and Responsibilities
- Data Architect
- Data Engineer
- Data Modeler
Data Management Processes
Data Management Workflow
- Data Collection
- Data Processing
- Data Distribution
- Data Discovery
- Data Analysis
- Data Archiving
- Repurposing
Data Management Services and Applications
Creating a Data Management Plan
Data Analytics Overview
Data Analytics Process
- Data collection
- Data storage
- Data processing
- Data cleansing
- Data analysis
Data collection
- Extract Transform Load (ETL)
- Extract Load Transform (ELT)
Data storage
- Data warehouses
- Data lakes
- Comparing data lakes and data warehouses
Data processing
- Centralized processing
- Distributed processing
- Batch processing
- Real-time processing
- Data cleansing
- Data analysis
Data Analytics
- Descriptive analytics
- Diagnostic analytics
- Predictive analytics
- Prescriptive analytics
Computing techniques used in data analytics
- Natural language processing
- Text mining
- Sensor data analysis
- Outlier analysis
Data Modelling Overview
Conceptual Data Models: Big picture view of data
- What data a system contains
- Data attributes and conditions or constraints on data
- What business rules data relates to
- How data is best organized
- Security and data integrity requirements
Logical Data Models: Mapping conceptual data classes to technical data structures
- Data types of various attributes
- Relationships between data entities
- Primary attributes or key fields in data
Physical Data Models: Mapping logical data models to a DBMS
- Data field types as represented in a DBMS
- Data relationships as represented in a DBMS
- Performance tuning
Data Modeling Techniques
- Hierarchical data modeling
- Graph data modeling
- Relational data modeling
- Entity-relationship data modeling
- Object-oriented data modeling
- Dimensional data modeling
Data Modeling Process
- Overview
- Identify entities and properties
- Identify relationships between entities
- Identify data modeling technique
- Optimize and iterate
Modern Data Architecture Overview
Scalable Data Lakes
Purpose-Built Analytics Services
Unified Data Access
Unified Data Governance
Data Governance Overview
- Policies and procedures an organization implements to manage data security, integrity, and responsible data use
- Regulatory compliance
- Data security and access control
Data Governance Organizations
- Data Governance Institute
Data Governance Roles and Responsibilities
- Data Governance Council/Data Administrator
- Data Steward
- Data Custodian
- Hands-on Exercise: Creating a Data Lake
- Hands-on Exercise: Collecting Data with Extract Transform Load (ETL)
- Hands-on Exercise: Performing Data Cleansing
- Hands-on Exercise: Performing Data Analytics
- Hands-on Exercise: Implementing the Data Modelling Process
- Hands-on Exercise: Creating Conceptual Data Models
- Hands-on Exercise: Creating Logical Data Models
- Hands-on Exercise: Creating Physical Data Models
- Hands-on Exercise: Examining Data Modeling Techniques
- Hands-on Exercise: Examining the Data Modeling Process
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Mastering Data Stewardship Training FAQs
This course is designed for data professionals including Data Stewards, Data Architects, Data Engineers, Data Analysts, Data Modelers, IT Managers, Business Intelligence Professionals, and Compliance Officers. It is also suitable for anyone looking to advance their career in data management, governance, and analytics.
Basic understanding of data concepts and familiarity with data storage and processing technologies are recommended but not mandatory. The course will cover foundational topics before advancing to more complex material.
You will gain a comprehensive understanding of data fundamentals, Data Management, Data Governance, Data Analytics, Data Modelling, and Modern Data Architecture. You will also acquire hands-on experience through practical exercises using common data services and technologies.
The course includes practical exercises such as creating a data lake, performing ETL processes, data cleansing, data analytics, implementing data modelling processes, and examining various data modelling techniques.
Yes, we offer customized training solutions tailored to meet the specific needs of your organization. Please contact us for more information on bespoke training options.