The Digital Transformation Security Professional course provides IT professionals with knowledge of the fundamentals of digital transformation. It covers implementing digital transformation and how to address cybersecurity concerns during this process. The course provides a comparison of standard IT security with Cybersecurity and further explores how Cybersecurity can be applied to a range of contemporary technologies. Common roles, drivers, benefits and challenges are also covered.
As an authorized partner of Arcitura, TechnoEdge Learning uses the official curriculum to prepare for the Digital Transformation Security Professional course, which can be taken through Pearson Vue online. Completion of the Certified Digital Transformation Security Professional course and passing the Digital Transformation Security Professional Certification Exam (DT90.SEC) proves proficiency in best practices for digital transformation as they relate to cybersecurity, allowing professionals to support digital transformation while protecting the organization.
The course includes a 12-month subscription to the following digital course materials:
- Video Lessons (Modules 1, 2, 4 and 15)
- Workbook (Modules 1, 2, 4 and 15)
- Exam Preparation Guides (Modules 1, 2, 4 and 15)
- Symbol Legend Poster (Modules 1, 4 and 15)
- Mind Map Poster (Modules 1, 2, 4 and 15)
- Flashcards (Modules 1, 2, 4 and 15)
- Blockchain Models Poster
- Consensus Types Poster
- Digital Transformation Security Professional Certification Exam (DT90.SEC) Voucher
Arcitura Certified Digital Transformation Security Professional Course Course Outline
Module 1: Fundamental Digital Transformation
- Understanding digital transformation
- Benefits of digital transformation
- Challenges of digital transformation
- Digital transformation business and technology drivers
- Understanding customer-centricity
- Product-centric vs. customer-centric relationships
- Relationship-value actions and warmth
- Omni-channel customer interactions
- Customer journeys and customer data intelligence
- Data intelligence basics
- Data origins and data sources
- Data collection methods and data utilization types
- Intelligent decision-making
- Computer-assisted manual decision-making and conditional automated decision-making
- Intelligent manual decision-making vs. intelligent automated decision-making
- Direct-driven automated decision-making and periodic automated decision-making
- Realtime automated decision-making
Module 2: Digital Transformation in Practice
- Understanding digital transformation solutions and distributed solution design basics
- Data ingress basics, including File Pull, File Push, API Pull, API push and data streaming
- An introduction to digital transformation automation technologies
- Cloud computing basics and cloud computing as part of digital transformation solutions
- Common cloud computing risks and challenges
- Blockchain basics and blockchain as part of digital transformation solutions
- Common blockchain risks and challenges
- Internet of things (IoT) basics and IoT as part of digital transformation solutions
- Common IoT risks and challenges
- Robotic process automation (RPA) and RPA as part of digital transformation solutions
- Common RPA risks and challenges
- An introduction to digital transformation data science technologies
- Big data and data analytics and big data as part of digital transformation solutions
- Common big data risks and challenges
- Machine learning basics and machine learning as part of digital transformation solutions
- Common machine learning risks and challenges
- Artificial intelligence (AI) basics and AI as part of digital transformation solutions
- Common AI risks and challenges
- Inside a customer-centric digital transformation solution (a comprehensive, step-by-step exploration)
- Mapping individual digital transformation technologies to solution processing
- Tracking how data intelligence is collected and used in a digital transformation solution
Module 4: Fundamental Blockchain
- Benefits and challenges of blockchain
- Blockchain business drivers and technology drivers
- Understanding blockchain’s decentralized model
- Blockchain value propositions
- How blockchain can be used for different industries
- Blockchain applications, networks and the distributed ledger
- How the distributed ledger can relate to relational database
- Fundamental components of a blockchain architecture
- Transactions, records and pools
- Blocks, chains and block headers
- Blockchain users, full nodes and partial nodes
- Step-by-step understanding of the record and block lifecycle
- Step-by-step understanding of how the merkle tree works
- Step-by-step understanding of how consensus works
- Consensus algorithms (PoW, PoS, PoA, DPoS, LPoS, PoI, PoET, PoC, PoB, round robin)
- Public vs. private/permissionless vs. permissioned blockchains
- Coins, tokens, smart contracts
- Basics of crypto hashing and cryptography
- On-chain, off-chain and cross-chain activity
- Common blockchain metrics
Module 15: Fundamental Cybersecurity
- Introduction to cybersecurity
- Understanding cyber fraud and cybercrime
- Common benefits and challenges
- Common business and technology drivers
- Cybersecurity versus IT security
- Common terms and concepts
- Cybersecurity and network security
- Cybersecurity and data security
- Common cybersecurity tools and mechanisms
- Cybersecurity CIA (confidentiality, integrity, availability) principle
- Cybersecurity impacts on people, processes and technology
- Cybersecurity and blockchain
- Cybersecurity and cloud computing
- Cybersecurity and services and APIs
- Cybersecurity and big data, ML and AI Data
- Cybersecurity and digital transformation
- Common cybersecurity roles
Who Should Take This Course
- Digital Transformation Professionals
- Information Security Professionals
- Cybersecurity Analysts
- Cybersecurity Consultants
