Data Science · Data and Computing
Virginia SOL DS.12
Virginia SOL DS.12 is part of the Data and Computing strand in Data Science (Math). Under this Standards of Learning objective, students select and utilize technological tools to process and prepare data for analysis. Below is what DS.12 covers in plain language, the specific skills it is assessed on, the key concepts to review, and how to practice DS.12 for the Virginia SOL test.
What SOL DS.12 means
Select and utilize technological tools to process and prepare data for analysis.
Skills you’ll practice for DS.12
- Access data effectively from multiple sources (tables, CSV, spreadsheets, documents, databases) using technology tools.
- Explore data for issues and errors using tools before processing.
- Define the process to optimally ingest and export data using technology.
- Clean and validate data by removing incomplete, incorrect, or duplicated entries; removing outliers; and standardizing data.
- Combine and store data by merging datasets and optimizing storage based on volume, velocity, and variety.
- Format and store data appropriately for effective analysis.
Key concepts covered by DS.12
- data access
- data sources
- CSV
- spreadsheets
- databases
- data exploration
- error detection
- data validation
- data ingestion
- data export
- process definition
- technology tools
- data cleaning
- outlier removal
- data standardization
- data combination
- data storage
- dataset merging
- storage optimization
- data formatting
- analysis preparation
How to study and practice SOL DS.12
Start with a quick diagnostic to see whether DS.12 is already solid, then work each skill above with guided notes, flashcards, and SOL-style practice questions. For official released items, see our Virginia SOL practice tests guide and how to study for the SOL test.
Related Data Science standards in Data and Computing
- DS.13 — Select and utilize technological tools to analyze and communicate data effectively.
Frequently asked questions about SOL DS.12
What is Virginia SOL DS.12?
SOL DS.12 is a Data Science Standard of Learning in the Data and Computing strand. It expects students to select and utilize technological tools to process and prepare data for analysis.
What skills does SOL DS.12 cover?
SOL DS.12 is assessed on 6 skills: access data effectively from multiple sources (tables, CSV, spreadsheets, documents, databases) using technology tools; explore data for issues and errors using tools before processing; define the process to optimally ingest and export data using technology; clean and validate data by removing incomplete, incorrect, or duplicated entries; removing outliers; and standardizing data; combine and store data by merging datasets and optimizing storage based on volume, velocity, and variety; format and store data appropriately for effective analysis.
What strand of Data Science is SOL DS.12 in?
SOL DS.12 belongs to the Data and Computing reporting strand of the Data Science Virginia Standards of Learning.
How do I study and practice for SOL DS.12?
Start with a diagnostic to see whether DS.12 is already solid, then work the 6 skills above with guided notes, flashcards, and SOL-style practice questions. For official released items, see the Virginia SOL practice tests guide.