CompTIA Data+ study plan

Define structured, semi-structured, and unstructured data and give two workplace examples of each

Diagram the flow between operational database, data warehouse, data lake, and data mart, labeling what each stores

Classify 25 sample data elements by data type and character set, noting where type mismatches would break a query

Write 10 single-table SQL statements using SELECT, WHERE, GROUP BY, ORDER BY, and aggregate functions

Contrast ETL and ELT and sketch both pipelines for a retail order scenario

Order the data mining lifecycle stages and name the artifact produced at each stage

Profile a public dataset by recording row count, column count, null rate, distinct count, and min/max for every column

Write 10 join queries using INNER JOIN, LEFT JOIN, and UNION against a two-table dataset

Categorize data quality defects (duplicates, nulls, inconsistent formats, out-of-range values, outliers) in a deliberately messy dataset

Cleanse that dataset using deduplication, format standardization, and null handling, writing a one-line justification per change

Apply normalization, binning, and aggregation to numeric fields and record how each changed the distribution

Compare the raw and cleansed datasets on row count, distinct values, and null rate to prove the cleanup worked

Explain the roles of data owner, data steward, and data custodian and assign each to a sample org chart

Score a sample dataset 1-5 on accuracy, completeness, consistency, timeliness, uniqueness, and validity with a written justification per score

Summarize what five common regulatory frameworks protect and which data categories they cover

Sit a 50-question timed practice test over Domains 1 and 2

Classify 15 data fields as PII, PHI, PCI, confidential, or public and assign a handling rule to each class

Explain access control approaches, encryption at rest and in transit, and masking versus tokenization with a use case for each

Draft a retention and destruction policy outline naming triggers, durations, and destruction methods

Build a 10-item audit control checklist covering source-to-report lineage and change tracking

Compute and interpret mean, median, mode, variance, standard deviation, and correlation on a real dataset

Match each analysis type (descriptive, diagnostic, predictive, prescriptive) to a business question it answers

Run one hypothesis test or simple regression and translate the result into a single plain-language business conclusion

Detect trend, seasonality, and outliers in a time-series dataset and label each finding

Match 12 chart types to the question each answers best and list two anti-patterns per chart family

Build a dashboard of at least 3 visuals that answers one clearly stated business question

Apply hierarchy, color, labeling, and chart-junk reduction rules and annotate where you applied each

Write a 5-slide data story with an executive summary and a next-step recommendation

Sit two full-length timed practice exams and record scores broken out by domain

Re-study the two lowest-scoring objectives until repeat practice accuracy on them exceeds 85%

Recall from memory the core statistics formulas, six data quality dimensions, and governance role definitions

Complete one end-to-end mini project that ingests, cleanses, analyzes, visualizes, and documents governance for a single dataset