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Start a timed practice session focusing on Data Mining and Preparation topics from the DATAPLUS question bank.
Start DATAPLUS Practice Quiz →DATAPLUS Data Mining Question Bank (11 Questions)
Browse all 11 practice questions covering Data Mining and Preparation for the DATAPLUS certification exam. Answers are intentionally hidden on this page so you can self-test first before checking results in quiz mode.
- Question 1Data Acquisition & Preparation
A dataset has rows where the 'state' field contains both 'CA' and 'California'. What data quality issue does this represent?
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Start DATAPLUS Quiz - Question 2Data Acquisition & Preparation
An analyst receives a CSV file where dates are formatted as 'MM/DD/YYYY' but the target database requires 'YYYY-MM-DD'. This conversion is part of which process?
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Start DATAPLUS Quiz - Question 3Data Acquisition & Preparation
An analyst discovers that 15% of records in a dataset have null values in the 'income' field. Which approach is MOST appropriate for handling this?
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Start DATAPLUS Quiz - Question 4Data Acquisition & Preparation
Converting a dataset from wide format (one column per month) to long format (one row per month) is called:
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Start DATAPLUS Quiz - Question 5Data Acquisition & Preparation
Which technique detects outliers by identifying data points that fall more than 1.5 times the interquartile range (IQR) beyond Q1 or Q3?
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Start DATAPLUS Quiz - Question 6Select All That ApplyData Acquisition & Preparation
Which of the following tasks are part of data wrangling? (Choose TWO.)
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Start DATAPLUS Quiz - Question 7Data Concepts & Environments
In an ETL pipeline, during which phase are data type conversions and field mappings applied?
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Start DATAPLUS Quiz - Question 8Data Concepts & Environments
What is the MAIN difference between ETL and ELT?
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Start DATAPLUS Quiz - Question 9Data Acquisition & Preparation
During an ETL process, duplicate customer records from two source systems need to be merged into a single record. Which technique is MOST appropriate?
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Start DATAPLUS Quiz - Question 10Data Acquisition & Preparation
Which ETL component is responsible for tracking changes in source data and loading only new or modified records?
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Start DATAPLUS Quiz - Question 11Data Acquisition & Preparation
Which step in an ETL pipeline validates that the number of rows extracted matches the number loaded into the target?
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Key Data Mining Concepts for DATAPLUS
DATAPLUS Data Mining Exam Tips
Data Mining and Preparation questions in DATAPLUS are typically scenario-based. Focus on service-level decision making aligned to official exam objectives. Priority concepts: etl, cleansing, wrangling.
What DATAPLUS Expects
- Anchor your answer in select the most practical, secure, and scalable answer for the stated scenario.
- Data Mining scenarios for DATAPLUS are frequently mapped to Domain 2 (22%), so read the objective carefully before picking controls or architecture.
- Expect multi-topic scenarios where Data Mining interacts with security, networking, infrastructure, or troubleshooting patterns rather than appearing as an isolated question.
- When two options are both technically valid, prefer the choice that best aligns with the exam's operational scope (Associate) and vendor best practices.
High-Value Data Mining Concepts
- Know the core Data Mining building blocks cold: etl, cleansing, wrangling.
- Review the edge-case features and limits for etl, cleansing; these details are commonly used to differentiate answer choices.
- Practice service-integration reasoning: how Data Mining pairs with Data Acquisition, Data Analysis, Data Governance in real deployment patterns.
- For DATAPLUS, explain why the chosen Data Mining design meets reliability, security, and cost expectations better than the alternatives.
Common DATAPLUS Traps
- Watch for answers that partially solve the requirement but miss operational constraints.
- Questions in Data Acquisition and Preparation often include distractors that look correct for Data Mining but violate security policy, performance, or reliability requirements.
- Avoid picking options purely by feature name; validate data path, failure handling, and governance impact before answering.
- If the prompt hints at automation or repeatability, eliminate manual-only operational answers first.
Fast Review Checklist
- Can you compare at least two Data Mining implementation paths and justify which one best fits the scenario?
- Can you map the chosen answer back to Data Acquisition and Preparation (22%) outcomes for DATAPLUS?
- Can you explain security and access boundaries for Data Mining without relying on default-open assumptions?
- Can you describe how Data Mining integrates with Data Acquisition and Data Analysis during failure, scaling, and monitoring events?