Course

Course Summary
Credit Type:
Course
ACE ID:
SKIL-0206
Organization:
SkillSoft Corporation
Location:
Classroom-based
Length:
Self-paced, 25 hours
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Data Science, Cloud Development, or Data Project Development
Description

Objective:

The course objective is to help prepare the learner for a Data Ops role with a focus on governance, security, and harnessing volume and velocity.

Learning Outcomes:

  • Implement cloud architecture for large scale applications, serverless computing, adequate storage, and analytical platforms using DevOps tools and cloud resources
  • Develop compliance strategies and implement data compliance programs
  • Apply techniques to establish and maintain a structured data access governance framework
  • Identify how data access can be monitored through SIEM and reports
  • Use encryption to protect data and monitor data access
  • Develop applications in Spark to work with streaming data
  • Explore different ways to process streams and generate an output
  • Use Amazon Redshift to set up and configure a data warehouse on the cloud
  • Use Amazon QuickSight to visualize data
  • Recognize required elements for deploying IoT solutions
  • Describe the security risks related to modern data capture and processing methods such as streaming analytics
  • Describe techniques and tools that can be used to mitigate security risks, and best practices related to securing big data
  • Recognize the differences between big data and smart data from the perspectives of volume, variety, velocity, and veracity
  • List the frameworks for smart data and specify the algorithms for smart data transition
  • Identify different uses of data science visualization, analytic, and database tools
  • Create and implement dashboards and visualizations using PowerBI and ELK
  • Create bar and line charts using Kibana
  • Create dashboards using Kibana, Tableau, and Qlikview
  • Plan and design a big data governance strategy
  • Interact with the Redshift service using both the console and the AWS CLI
  • List the critical design principles that need to be implemented when building IoT solutions
  • Implement transaction management and rollbacks using SQL Server
  • Implement change data capture in databases and NoSQL

General Topics:

  • Data Science Tools
  • Delivering Dashboards - Management Patterns
  • Delivering Dashboards - Exploration and Analytics
  • Cloud Architecture and Containerization
  • Cloud Data Management and Adoption Frameworks
  • Data Compliance Issues and Strategies
  • Implementing Governance Strategies
  • Data Access Governance and IAM
  • Data Classification, Encryption, and Monitoring
  • Getting Started with Streaming Data Architectures in Spark
  • Processing Streaming Data with Spark
  • Scalable Data Architectures Getting Started
  • Scalable Data Architectures Using Amazon Redshift
  • Scalable Data Architectures using Amazon Redshift and QuickSight
  • Building Data Pipelines
  • Data Pipeline: Process Implementation Using Tableau and AWS
  • Data Pipeline: Using Frameworks for Advanced Data Management
  • Integrating Data Sources from the Edge
  • Implementing Edge Data on the Cloud
  • Securing Big Data Streams
  • Turning Big Data into Smart Data
  • Transaction Rollbacks and Their Impact
  • Transaction Management and Rollbacks in NoSQL
Instruction & Assessment

Instructional Strategies:

  • Computer Based Training
  • Practical Exercises

Methods of Assessment:

  • Examinations
  • Quizzes

Minimum Passing Score:

70%
Supplemental Materials