CertiThree stores
The lake keeps native files. The lakehouse adds tables. The warehouse keeps modeled history. The mart serves one team. A silo is a store others cannot use.
Study guide · Flashcards & memory notes
Data+ Flashcards & Memory Notes
40 recall cards for the facts Data+ (DA0-002) keeps asking you to separate: stores and tools, preparation, analysis, and governance.
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Deck 1 · Concepts and environments
Stores, types, tools, and AI.
1.1How does a relational database differ from a non-relational one?
Relational databases store tables linked by keys. Non-relational stores do not require that fixed table model.
1.2How do a lake, a lakehouse, a warehouse, a mart, and a silo differ?
A lake keeps native files. A lakehouse adds warehouse-style tables. A warehouse holds modeled history. A mart is one subject. A silo is a store others cannot use. A silo is a problem, not a target design.
1.3What do a fact table, a dimension, and a bridge table hold?
A fact table holds measures. A dimension holds labels you slice by. A bridge table links a many-to-many pair. Do not average a dimension label.
1.4How do object, block, and file storage differ?
Object storage keeps files as objects. Block storage presents disks. File storage presents folders. Local storage stays on one machine. Shared file storage is available to more than one system.
1.5What does containerization package?
An application and its dependencies, so it runs the same way on different hosts. A container is not a data type and not a chart.
1.6How do CSV, JSON, and JPEG files differ?
CSV separates fields in text. JSON names fields, often nested. A JPEG is an image. An image is not a table of sales.
1.7How do varchar, BLOB, and GUID differ?
Varchar is text. A BLOB is a binary large object. A GUID is an identifier meant to be unique. Null means missing, not zero.
1.8Which tool shapes tables in code, and which tool builds a visual?
pandas and tidyverse shape tables in code. Tableau, Power BI, and Looker build visuals. MongoDB Compass is a non-relational client. SSMS is a relational client.
1.9How do a large language model and robotic process automation differ?
An LLM generates or interprets text. RPA repeats a software task, such as an automated report. Neither one is a join.
1.10How do public, private, and hybrid cloud differ?
Public cloud is shared infrastructure. Private cloud is for one organization. Hybrid uses both. On-premises means the organization runs the systems itself.
Deck 2 · Acquisition and preparation
Queries, defects, and reshaping.
2.1How do ETL and ELT differ?
ETL transforms, then loads. ELT loads the raw extract, then transforms it. ELT keeps a raw landing you can rerun.
2.2How do a join and a union differ?
A join combines tables by a key. A union stacks compatible rows. A bad key makes a join double-count. Concatenate also stacks rows.
2.3How do duplicate data and redundant data differ?
A duplicate is the same row twice. Redundant data is the same fact in more than one place. A real history row is not an accidental duplicate.
2.4What is imputation, and what is an outlier?
Imputation fills a missing value. An outlier is an extreme value. Confirm an outlier before you delete it.
2.5How do an index and a parameter help a query?
An index speeds reads that match its keys. A parameter reuses one statement. A subset shrinks the working set. A temporary table holds an intermediate result.
2.6How do parsing and exploding differ?
Parsing splits or matches text. Exploding turns a nested list into rows. A regular expression is a parsing tool, not a chart.
2.7What does scaling mean while you prepare data?
Put variables on a comparable scale. That is not the same as splitting a dimension table into more tables.
2.8How do merging and appending differ?
A merge brings columns together by a key. Append adds rows. A derived field is calculated, such as margin.
2.9How do sampling and a survey differ from a full extract?
A sample is a subset. A survey asks people. A full extract copies the source set. None of those is an index.
2.10What does a nested query do?
It runs a query inside another query. Read the inner result before you blame the outer filter.
Deck 3 · Analysis
Methods, audiences, and broken results.
3.1How do descriptive, inferential, predictive, and prescriptive methods differ?
Descriptive summarizes the set. Inferential generalizes from a sample. Predictive estimates what comes next. Prescriptive recommends an action. Name the family before you name a formula.
3.2How do the mean, the median, and the mode differ?
The mean is the average. The median is the middle. The mode is the most frequent value. Extreme values pull the mean.
3.3Sales go from 80 to 100. What is the percent change?
25 percent, because the base is 80. Dividing by the new value, 100, is a different comparison.
3.4What does a measure of dispersion describe?
How spread out the values are, such as the range from smallest to largest. The mean is a center, not a spread.
3.5What should an executive see, and what should a technical reader see?
Executives get a few KPIs. Technical readers get field definitions and filters. A mock-up shows the layout before you build it.
3.6What stays off a public page?
Sensitive fields, including identifiers the external audience does not need. Internal and external audiences do not get the same columns.
3.7How do a connectivity failure and corrupt data differ?
Connectivity means the tool cannot reach the source. Corrupt data is damaged content. Enable logging and validate the source before you delete rows.
3.8What is a KPI?
The number that matches the business question. Extra columns that do not change the decision bury it.
3.9Which method family summarizes what already happened?
Descriptive. Predictive estimates a later value. Prescriptive recommends an action.
3.10What is the first check when a user says the total is wrong?
Reproduce the issue, then validate the source and the query. A new color scheme does not repair a bad join.
Deck 4 · Reports and governance
Delivery, protections, and quality.
4.1How do a snapshot and a real-time feed differ?
A snapshot is one moment. A real-time feed moves with the source. Compare the refresh time when two totals disagree.
4.2How do a static dashboard and a dynamic dashboard differ?
Static stays as published. Dynamic changes as the source or the filters change. Recurring delivery repeats. Ad hoc delivery is one time.
4.3When is a line chart a better choice than a map?
A line shows values in time order. A map places values by location. A pivot table regroups totals. It is not a geographic map.
4.4A report is hours behind the source. What do you check first?
The refresh interval and the source, not the legend colors. Stale data is a delivery defect.
4.5The dashboard takes too long to open. What is a likely cause?
The data set is too large for the view. Filter to the subset the reader needs.
4.6How do masking and encryption differ?
Masking hides identifiers and can leave a usable value. Encryption protects data at rest or in transit. Do not put the key in the report footer.
4.7How do PII, PHI, and PCI differ?
PII identifies a person. PHI is health information. PCI is payment card data. They are classifications, not chart types.
4.8How do a data dictionary and the source of truth differ?
A dictionary defines names. The source of truth is the record you trust when systems disagree. Lineage shows where a value came from.
4.9What is data drift?
A shift in the shape or meaning of the data over time. A health check and automated monitoring look for that shift.
4.10What does GDPR require you to recognize?
A jurisdictional privacy rule about personal data, including how long you may keep it and how you report a breach. Retention is the keep-or-delete rule. PCI DSS is the card-data rule.
Memory notes
Groupings that make the highest-yield Data+ facts easier to recall.
Two load orders
ETL transforms, then loads. ELT loads, then transforms. A join adds columns by a key. A union stacks rows. Profile, then repair, then profile again.
Four methods
Descriptive summarizes the past. Inferential generalizes from a sample. Predictive estimates what comes next. Prescriptive recommends an action. The mean moves with outliers.
Two visuals
A line is time. A map is place. A snapshot is one moment. A real-time feed moves. A slow refresh is a data problem, not a missing legend.
Two protections
Mask the identifier. Encrypt the file or the wire. PII, PHI, and PCI are different labels. A dictionary defines names. The source of truth is the record you trust.
One audience rule
Executives get few KPIs. Technical readers get the field definitions. Sensitive fields stay off the public page. Write the refresh time.
Continue the Data+ study path
Test what you have learned with a timed practice exam.
Overview
Exam format, the 675 passing score, five DA0-002 domain weights, and how V2 differs from retired DA0-001.
Core Notes
Reference notes for sources, preparation, statistics, visuals, and governance.
Flashcards & Memory Notes
40 recall cards in four decks, plus memory notes for stores, statistics, and reports.
Practice Exams
200 original questions with custom exams, explanations, and an unofficial score on the 100-900 scale.
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