Explore KSACs by Pathway
Explore Knowledge, Skills, Abilities, and Credentials (KSACs) by IT Pathway.
Cross-Cutting KSAs
| KSAC Description | Bloom's Taxonomy Level | Cross-Cutting | |
|---|---|---|---|
| Identify and describe basic file types and demonstrate fundamental file management. | skill | 2 | Cybersecurity (1.g) Data Management (1.r) Networking (5.f) Software Development (1.k) |
| Demonstrate an understanding of cloud architecture and the capabilities of services such as AWS, Azure, IBM, Oracle and Google. | knowledge | 2 | Cybersecurity (4.d) Data Management (1.p) Networking (1.a) Software Development (1.g) Machine Learning (1.i) |
| Ability to install and configure software. | ability | 3 | Cybersecurity (1.d) Data Management (1.s) Networking (5.a) Software Development (1.h) |
| Explain data security in terms of authentication, authorization, access and auditing. | knowledge | 3 | Networking (4.g) Software Development (1.l) |
| Understand OSI model and how it applies to an example. | knowledge | 2 | Cybersecurity (6.a.5) Networking (3.b) |
| Identify and apply Transmission Control Protocol and Internet Protocol (TCP/IP), Internet Protocol Version 4 (IPv4), Internet Protocol Version 6 (IPv6) applications and services (e.g., rlogin, Simple Mail Transfer Protocol [SMTP], Telecommunications Network [Telnet], File Transfer Protocol [FTP], Domain Name System [DNS], Network File System [NFS], Voice over Internet Protocol [VoIP], Internet Control Message Protocol [ICMP]). | knowledge | 2 | Software Development (1.n) |
| Compare and contrast Internet connection types, network types and their features (e.g. T-Lines, fiber cables, microwaves, cellular, satellite) Layers 1 & 2 | knowledge | 2 | Cybersecurity (6.a.7) Networking (1.e) |
| Apply secure network Protocols (e.g., IPSec, SNMP, SSH, DNS, TLS, SSL, TCP/IP, FTPS, HTTPS, SCP, ICMP). | ability | 2 | Cybersecurity (6.d) Networking (2.g) |
| Apply SQL data manipulation language such as Select (From), Insert, Update, Delete, JOIN (inner, outer, full, left, right), Where, Group By, Order By, etc. | ability | 3 | Data Management (1.l) Software Development (1.d) |
| Demonstrate fundamental programming skills including the use of variables, loops, conditional branching, and program logic. | skill | 3 | Data Management (1.m) Software Development (2.c) |
| Ability to normalize a database through 3rd normal form. | ability | 3 | Data Management (2.j) Software Development (1.a) |
| Differentiate common data typologies, including structured vs. unstructured, numeric vs. text, root vs. derived. | knowledge | 3 | Generalist (1.b) Data Analytics (1.d) |
| Explain and demonstrate how differences in data and desired outcomes impact the appropriateness of data analysis techniques (e.g., descriptive vs. diagnostic vs. predictive vs. prescriptive). | knowledge | 2 | Generalist (1.e) Data Analytics (1.d) |
| Demonstrate knowledge of probability and standard statistical distributions. | knowledge | 1 | Generalist (2.a) Data Analytics (5.a) |
| Demonstrate and explain the role and importance of model validation and accuracy metrics in analytics projects, hypothesis testing, and information retrieval. | knowledge | 2 | Generalist (2.c) Data Analytics (5.d) |
| Perform basic data manipulation and exploration using appropriate tools and software, including use of key Excel functions. | skill | 3 | Generalist (3.a) Machine Learning(4.f) Data Analytics (4.c) |
| Create and edit simple data structures and storage, understanding how version control affects each. | skill | 2 | Generalist (3.b) Data Analytics (4.d) |
| Explain the role of data visualization in discovery, communication, and decision-making. | knowledge | 3 | Generalist (4.a) Machine Learning(3.a) Data Analytics (6.a) |
| Evaluate data visualization options for proper application in various situations. | ability | 4 | Generalist (4.b) Machine Learning(3.b) Data Analytics (6.c) |
| Create effective static and interactive data visualizations or storytelling that employ analytics and visualization software and strategies for various audiences. | skill | 3 | Generalist (4.c) Machine Learning(3.c) Data Analytics (6.e) |
| Visualize data using various types of displays including tables, dashboards, graphs, maps, and trees. | skill | 3 | Generalist (4.d) Machine Learning(3.d) Data Analytics (6.d) |
| Distinguish between advanced visualizations and explain the advantages of each. | knowledge | 3 | Generalist (4.3) Machine Learning(3.e) |
| Discuss techniques for creating advanced data visualizations. | knowledge | 3 | Generalist (4.f) Machine Learning(3.f) |
| Apply the principles of color, composition, and hierarchy to design. | skill | 3 | Generalist (4.g) Machine Learning(3.g) |
| Properly define a problem in context, use appropriate data, and deliver a compelling visualization to explain or answer a question. | ability | 3 | Generalist (4.h) Machine Learning(3.h) Data Analytics (6.f) |
| Understanding of ADA/508 compliance for accessibility. | knowledge | 1 | Generalist (4.i) Machine Learning(3.i) |
| Identify how global legal, policy and/or ethical constraints might impact data analyses. | knowledge | 2 | Generalist (5.a) Machine Learning(5.a) Data Analytics (8.a) |
| Identify the established ethical and legal issues in data management facing organizations. | knowledge | 2 | Data Management (3.e) Generalist (5.b) Machine Learning(5.b) Data Analytics (8.b) |
| Explain how ethical, compliance, and legal issues should/must be considered in data driven decision making. | knowledge | 1 | Generalist (5.c) Machine Learning(5.c) Data Analytics (8.c) |
| Explain the importance of personal privacy issues related to the collection and usage of data. | knowledge | 2 | Data Management (3.f) Generalist (5.d) Machine Learning(5.g) Data Analytics (8.i) |
| Explain the important issues around data governance. | knowledge | 2 | Generalist (5.e) Machine Learning(5.d) Data Analytics (1.b) |
| Describe the fundamental cloud components (e.g., shared or dedicated processing, storage, memory, networking, hypervisor). | knowledge | 2 | Netowrking (1.b) Cybersecurity (4.a) |
| Differentiate between public, private, and hybrid clouds. | knowledge | 2 | Netowrking (1.c) Cybersecurity (4.b) |
| Identify common breaches and threats in the cloud environment. | knowledge | 1 | Netowrking (1.d) Cybersecurity (4.f) |
| Instantiate a small computing environment in a cloud service. | ability | 3 | Netowrking (1.e) Cybersecurity (4.e) |
| Explain the pros and cons of on-premises vs cloud-based analytics solutions. | knowledge | 2 | Netowrking (1.f) Data Analytics (2.c) |
| Understand how to set security configurations in a cloud environment. | knowledge | 2 | Netowrking (1.h) Data Analytics (4.g) |
| Understand the concept of opening/extending the network perimeter and the role of a cloud access security broker (CASB). | knowledge | 2 | Netowrking (1.i) Cybersecurity (8.u) |
| Explain DNS traffic. | knowledge | 2 | Netowrking (3.a) Cybersecurity (2.k) |
| Identify the layers of the OSI Model. | knowledge | 2 | Netowrking (3.c) Cybersecurity (2.c) |
| Summarize the responsibilities of each layer of the OSI Model. | knowledge | 2 | Netowrking (3.d) Cybersecurity (2.d) |
| Explain how the OSI Model is applied in networking. | knowledge | 3 | Netowrking (3.e) Cybersecurity (2.e) |
| Configure IPv4 and IPv6 classful subnets. | skill | 1 | Netowrking (3.f) Cybersecurity (2.f) |
| Compare public IP addresses and private IP addresses. | knowledge | 2 | Netowrking (3.g) Cybersecurity (2.g) |
| Identify IPv4 address network ID (Class A, Class B, Class C). | knowledge | 2 | Netowrking (3.h) Cybersecurity (2.h) |
| Interpret classless network ID (CIDR block notation). | knowledge | 2 | Netowrking (3.i) Cybersecurity (2.i) |
| Explain domain naming conventions (UNC path, FQDN, host name). | knowledge | 3 | Netowrking (3.j) Cybersecurity (2.l) |
| Compare Network Address Translation and Port Address Translation (NAT vs PAT). | knowledge | 2 | Netowrking (3.k) Cybersecurity (2.n) |
| Draw a network diagram. | skill | 3 | Netowrking (3.i) Cybersecurity (2.o) |
| Analyze the output from networking utilities (e.g. Netstat, Tracert, Traceroute, Ping IPConfig, IFConfig). | skill | 3 | Netowrking (3.m) Cybersecurity (2.p) |
| Discuss network software integration (client software (e.g. Windows 10 or Ubuntu) and server software). | ability | 3 | Netowrking (3.n) Cybersecurity (2.q) |
| Discuss network hardware integration (workstations, desktop, mobile devices). | knowledge | 2 | Netowrking (3.o) Cybersecurity (2.r) |
| Communicate best practices for troubleshooting networking issues (layers 1-2 at HS level) (7-step model). | knowledge | 3 | Netowrking (3.p) Cybersecurity (2.s) |
| Identify common coding errors that lead to insecure programs (e.g., buffer overflows, memory leaks, malicious code) and apply strategies for avoiding such errors. | skill | 3 | Software Development (10.a) Cybersecurity (11.d) |
| Apply the principles of least privilege, defensive programming, and fail-safe defaults. | ability | 3 | Software Development (10.d) Cybersecurity (11.e) |
| Write code with logging capabilities. | skill | 2 | Software Development (10.f) Cybersecurity (11.f) |
| Understand basics of securing web apps - SQL Injection and other input validation. | knowledge | 2 | Software Development (10.h) Cybersecurity (11.i) |
| Identify and differentiate structured vs unstructured data. | knowledge | 2 | Data Management (1.g) Software Development (1.o) |
| Design, implement, test, and debug a program that uses each of the following fundamental programming constructs: basic computation, simple I/O, standard conditional and iterative structures. | skill | 3 | Software Development (2.d) Cybersecurity (3.b) |
| Write a program that uses file I/O to provide persistence across multiple executions. | skill | 2 | Software Development (2.g) Cybersecurity (3.c) |
| Write programs that use each of the following data structures: arrays, records/structs, strings, linked lists, stacks, queues, sets, and maps. | skill | 3 | Software Development (3.c) Cybersecurity (3.f) |
| Choose the appropriate data structure for modeling a given problem. | skill | 3 | Software Development (3.f) Cybersecurity (11.a) |
| Implement a divide-and-conquer algorithm for solving a problem. | skill | 3 | Software Development (5.g) Cybersecurity (11.b) |
| Implement a coherent abstract data type, with loose coupling between components and behaviors. | skill | 3 | Software Development (5.i) Cybersecurity (11.c) |
| Explain core statistical inference concepts (for example, deriving relevant hypotheses, evaluating the hypotheses, and prediction with uncertainty). | knowledge | 2 | Machine Learning (1.a) Data Analytics (5.b) |
| Explain core probability concepts (e.g., random variables, key distributions, conditional probability, Bayes theorem). | knowledge | 2 | Machine Learning (1.c) Data Analytics (5.e) |
| Identify and describe several SDLC models (e.g., waterfall, Agile). | knowledge | 2 | Machine Learning (1.f) Data Analytics (7.c) |
| Provide rationale for selecting the appropriate sampling methodology. | skill | 3 | Machine Learning (4.g) Data Analytics (5.j) |
| Present real world examples of data bias and the unintended consequences of using analytics, machine learning, and AI in making decisions. | knowledge | 2 | Machine Learning (5.e) Data Analytics (8.e) |
| Discuss the importance of provenance, transparency, and explainability in data analysis and the ability to build trust. | knowledge | 2 | Machine Learning (5.f) Data Analytics (8.d) |
| Explain the limitations and potential unintended effects of data analysis when such algorithms encounter new scenarios. | knowledge | 2 | Machine Learning (5.i) Data Analytics (8.j) |
| Explain individual and data bias and the implications each has in data analysis. | knowledge | 3 | Data Management (3.j) Generalist(5.f) Machine Learning (5.k) |
| Describe the implications of data architecture on data processing such as data fabric. | knowledge | 2 | Data Management (1.n) Data Analytics (2.d) |