Mastering Data Stewardship: Hands-On

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: Hands-On Benefits 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 Fundamentals Data Overview Databases Data Lakes Data Warehouses Data Analytics Machine Learning and Artificial Intelligence Business Insights Data Management 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 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 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 Modern Data Architecture Overview Scalable Data Lakes Purpose-Built Analytics Services Unified Data Access Unified Data Governance 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 Exercises: 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