WITH (QUERYGRID) D) SELECT * FROM HIVE.<table>@QUERYGRID Answer: D Explanation: The “@QUERYGRID” suffix tells Vantage to route the query to the Hive connector. Question 10. Which statistical test is appropriate for comparing the means of two independent groups when the data are normally distributed? A) Paired t‑test B) Two‑sample t‑test C) ANOVA D) Chi‑square test Answer: B Explanation: The two‑sample t‑test evaluates the difference between means of two independent, normally distributed samples. Question 11. A scatter plot shows a tight upward trend with points closely aligned along a line. Which correlation coefficient value best describes this relationship? A) – 0. B) – 0. C) 0. D) 0. Answer: D Practice Exam
Explanation: A strong positive linear relationship yields a correlation close to +1. Question 12. If a hypothesis test returns a p‑value of 0.03, what decision should be made at the α = 0.05 significance level? A) Fail to reject the null hypothesis. B) Reject the null hypothesis. C) Increase the sample size. D) Change the test to a two‑tailed test. Answer: B Explanation: Since p < α, the result is statistically significant; we reject the null hypothesis. Question 13. In a logistic regression output, the coefficient for variable X1 is – 0.75. What does this indicate about the relationship between X1 and the odds of the target event? A) Each unit increase in X1 multiplies odds by e^(–0.75) ≈ 0.47 (decreases odds). B) Each unit increase in X1 adds 0.75 to the odds. C) X1 has no effect because the coefficient is negative. D) The odds increase by 75 % for each unit increase in X1. Answer: A Explanation: Logistic coefficients are log‑odds; exponentiating – 0.75 gives ≈0.47, meaning odds are reduced by about 53 %. Question 14. Which metric is calculated as True Positives / (True Positives + False Negatives)? A) Specificity B) Sensitivity (Recall) C) Precision
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C) Data truncation D) Inappropriate chart type Answer: B Explanation: Starting the axis above zero can distort visual perception of differences. Question 18. When using the Vantage “TOPN” function to retrieve the top 5 customers by sales, which clause must be included? A) ORDER BY sales DESC LIMIT 5 B) QUALIFY ROW_NUMBER() OVER (ORDER BY sales DESC) <= 5 C) TOP 5 BY sales DESC D) FETCH FIRST 5 ROWS ONLY Answer: B Explanation: Vantage uses QUALIFY with ROW_NUMBER to filter after window calculation. Question 19. Which text‑mining function tokenizes a string into individual words? A) NER_EXTRACT B) REGEXP_REPLACE C) TOKENIZE D) SENTIMENT_EXTRACT Answer: C Explanation: TOKENIZE splits a text string into tokens (words) based on delimiters. Question 20. After applying the SENTIMENT_EXTRACT function, which column indicates the overall sentiment polarity? A) sentiment_score B) sentiment_category
Practice Exam
C) sentiment_confidence D) sentiment_text Answer: B Explanation: SENTIMENT_EXTRACT returns a categorical label (e.g., POSITIVE, NEGATIVE) in the sentiment_category column. Question 21. Which syntax correctly invokes Named Entity Recognition (NER) to extract person names from column “review_text”? A) SELECT NER_EXTRACT(review_text, ‘PERSON’) FROM tbl; B) SELECT EXTRACT_NER(review_text, ‘PERSON’) FROM tbl; C) SELECT NER(review_text, ‘PERSON’) FROM tbl; D) SELECT PERSON_NER(review_text) FROM tbl; Answer: A Explanation: NER_EXTRACT takes the source text and the entity type as arguments. Question 22. In a session analysis, the NPATH function is used with the pattern ‘A → B → C’. What does NPATH return? A) Number of occurrences of the exact sequence A‑B‑C per session. B) Total time spent between A and C. C) All sessions that contain at least one of the three events. D) The probability of transitioning from A to C directly. Answer: A Explanation: NPATH counts how many times the specified event path appears in each session. Question 23. Which parameter controls the maximum idle time allowed before a session is closed in the SESSIONIZE function?
Practice Exam
Question 26. In traditional aggregation, which clause is used to group rows before applying aggregate functions? A) ORDER BY B) QUALIFY C) GROUP BY D) PARTITION BY Answer: C Explanation: GROUP BY defines the grouping set for aggregate calculations. Question 27. The CFilter function returns a “LIFT” metric of 1.8 for an association rule. What does this value indicate? A) The rule is 80 % less likely than random. B) The rule’s confidence is 1.8 %. C) The rule is 1.8 times more likely than chance. D) The rule’s support is 1.8 % of total transactions. Answer: C Explanation: LIFT > 1 means the antecedent increases the probability of the consequent by that factor compared to random chance. Question 28. Which of the following best describes the purpose of the “TIME_BUCKET” function? A) Convert timestamps to a specific timezone. B) Group timestamps into equal‑length intervals (e.g., hourly). C) Calculate the difference between two timestamps. D) Extract the day of week from a timestamp.
Practice Exam
Answer: B Explanation: TIME_BUCKET rounds timestamps down to the nearest bucket size, facilitating time‑based grouping. Question 29. When using the “ROW_NUMBER()” window function, which clause determines the order in which numbers are assigned? A) PARTITION BY B) ORDER BY inside the OVER clause C) QUALIFY D) GROUP BY Answer: B Explanation: ORDER BY within OVER defines the ranking sequence for ROW_NUMBER. Question 30. Which function would you use to calculate the moving average of sales over the previous 7 days for each day? A) AVG(sales) OVER (ORDER BY sales_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) B) MOVING_AVG(sales, 7) C) AVG(sales) OVER (PARTITION BY sales_date ROWS 7) D) SUM(sales) OVER (ORDER BY sales_date RANGE INTERVAL '7' DAY PRECEDING) / 7 Answer: A Explanation: The window frame “6 PRECEDING AND CURRENT ROW” creates a 7‑day moving window for the average. Question 31. In a data quality scenario, duplicate rows exist based on columns (customer_id, order_date). Which statement removes duplicates while preserving the earliest order_date per customer? A) SELECT DISTINCT * FROM tbl;
Practice Exam
Question 34. Which statistical measure is most affected by extreme outliers? A) Median B) Mode C) Mean D) Interquartile range Answer: C Explanation: The arithmetic mean incorporates every value and can be pulled dramatically by outliers. Question 35. In a time‑series forecast, which method assumes that future values are a linear combination of past observations? A) Exponential smoothing B) ARIMA C) K‑means clustering D) Decision tree regression Answer: B Explanation: ARIMA (AutoRegressive Integrated Moving Average) models each value as a function of past values and errors. Question 36. Which Vantage function extracts the year from a TIMESTAMP column? A) YEAR() B) EXTRACT(YEAR FROM timestamp_col) C) DATE_PART('year', timestamp_col) D) All of the above are valid. Answer: D
Practice Exam
Explanation: Vantage supports YEAR(), EXTRACT, and DATE_PART for retrieving the year component. Question 37. When visualizing a proportion of categories that sum to 100 %, which chart type is most appropriate? A) Stacked bar chart B) Pie chart C) Scatter plot D) Histogram Answer: B Explanation: Pie charts are designed to show parts of a whole that add up to 100 %. Question 38. A line chart’s X‑axis is labeled “Month” but the data points are spaced irregularly because some months are missing. What is the likely visualization flaw? A) Over‑aggregation B) Inappropriate chart type C) Missing data handling D) Misleading axis scaling Answer: D Explanation: An evenly spaced X‑axis implies regular intervals; missing months cause a misleading representation of time continuity. Question 39. Which configuration setting improves performance for large JOIN operations in Vantage? A) SET SESSION CHARSET = 'UTF8' B) SET QUERY_BAND = 'JoinMode=Broadcast' C) SET ENABLE_HASH_JOIN = TRUE
Practice Exam
A) (80 + 85) / 200 = 0.
B) (80 + 85) / (80 + 20 + 15 + 85) = 0.
C) 80 / (80 + 20) = 0.
D) 85 / (85 + 15) = 0.
Answer: B Explanation: Accuracy = (TP + TN) / Total = (80 + 85) / 200 = 0.825. Question 43. Which of the following best describes “precision” in a binary classification context? A) TP / (TP + FN) B) TP / (TP + FP) C) TN / (TN + FP) D) (TP + TN) / Total Answer: B Explanation: Precision measures the proportion of predicted positives that are actually positive. Question 44. When using the “MERGE” statement to upsert data, which clause defines the rows to be updated? A) WHEN MATCHED THEN UPDATE B) WHEN NOT MATCHED THEN INSERT C) ON TARGET.id = SOURCE.id D) USING SOURCE TABLE Answer: A Explanation: The WHEN MATCHED clause specifies the action (UPDATE) for rows that already exist in the target.
Practice Exam
Question 45. Which analytic function can be used to fill forward missing values in a time‑ordered series? A) LAST_VALUE(... IGNORE NULLS) OVER (ORDER BY ts ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) B) COALESCE(value, LAG(value) OVER (ORDER BY ts)) C) INTERPOLATE(value) OVER (ORDER BY ts) D) ALL of the above are valid approaches. Answer: A Explanation: LAST_VALUE with IGNORE NULLS returns the most recent non‑null value, effectively forward‑filling. Question 46. In a Vantage session, which command displays the current QueryGrid connections? A) SHOW QUERYGRID; B) SELECT * FROM dbc.QueryGridConnections; C) HELP SESSION; D) SELECT * FROM dbc.QueryGridStatus; Answer: B Explanation: The DBC view QueryGridConnections lists active QueryGrid sessions. Question 47. Which statistical concept describes the probability of observing a test statistic as extreme as, or more extreme than, the one calculated from the sample data? A) Confidence interval B) Power C) p‑value D) Effect size Answer: C
Practice Exam
D) FILTER
Answer: B Explanation: QUALIFY applies conditions after window functions are computed, similar to HAVING but for analytic results. Question 51. A dataset contains sales amounts in different currencies. Which transformation should be applied before aggregating revenue? A) Normalize each amount using Z‑score. B) Convert all amounts to a common currency using exchange rates. C) Apply MIN‑MAX scaling. D) Take the logarithm of each amount. Answer: B Explanation: Aggregating across currencies without conversion yields meaningless totals; conversion to a single currency is required. Question 52. Which Vantage function can be used to compute the exponential moving average (EMA) with a smoothing factor α? A) EXP_MOVING_AVG(value, α) B) EMA(value, α) OVER (ORDER BY ts) C) SUM(value * α) OVER (ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) D) There is no built‑in EMA; you must implement it with recursive CTE. Answer: D Explanation: Vantage does not provide a direct EMA function; it must be calculated using a recursive approach or user‑defined function. Question 53. In a correlation analysis, which condition must be satisfied for Pearson’s correlation coefficient to be valid?
Practice Exam
A) Both variables are ordinal. B) Both variables are normally distributed and linearly related. C) Variables are categorical. D) At least one variable is binary. Answer: B Explanation: Pearson’s r assumes continuous, normally distributed variables with a linear relationship. Question 54. Which statement correctly describes the effect of increasing the “HASHAMP” parameter in a hash join? A) It reduces the number of AMPs involved, decreasing parallelism. B) It increases the number of hash buckets, potentially reducing skew. C) It forces a broadcast join. D) It disables the hash join optimizer. Answer: B Explanation: HASHAMP controls the number of hash buckets; more buckets can distribute data more evenly, mitigating skew. Question 55. Which visualization best displays the change in a metric over time for multiple categories simultaneously? A) Stacked area chart B) Grouped bar chart C) Heat map D) Scatter plot matrix Answer: A Explanation: Stacked (or layered) area charts show temporal trends for several series on the same axis.
