Performance interview questions

1. A.the columnar in-memory engine that compresses imported data column by column for fast scanning
2. B.a built-in tool that records how long each visual's queries and rendering take to find bottlenecks
3. C.the practice of lowering the number of distinct values in a column to improve compression and shrink model size
4. D.a policy that reloads only recently changed partitions instead of the whole table to speed up imports

Answer + AI explanation with Pro

1. A.Incremental refresh
2. B.Cardinality reduction
3. C.Performance analyzer
4. D.VertiPaq

Answer + AI explanation with Pro

1. A.VertiPaq — the practice of lowering the number of distinct values in a column to improve compression and shrink model size
2. B.VertiPaq — a policy that reloads only recently changed partitions instead of the whole table to speed up imports
3. C.VertiPaq — the columnar in-memory engine that compresses imported data column by column for fast scanning
4. D.VertiPaq — a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows

Answer + AI explanation with Pro

1. A.a policy that reloads only recently changed partitions instead of the whole table to speed up imports
2. B.the columnar in-memory engine that compresses imported data column by column for fast scanning
3. C.a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
4. D.a built-in tool that records how long each visual's queries and rendering take to find bottlenecks

Answer + AI explanation with Pro

1. A.Cardinality reduction
2. B.VertiPaq
3. C.Aggregation table
4. D.Performance analyzer

Answer + AI explanation with Pro

1. A.Aggregation table — a policy that reloads only recently changed partitions instead of the whole table to speed up imports
2. B.Aggregation table — the columnar in-memory engine that compresses imported data column by column for fast scanning
3. C.Aggregation table — the practice of lowering the number of distinct values in a column to improve compression and shrink model size
4. D.Aggregation table — a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows

Answer + AI explanation with Pro

1. A.a policy that reloads only recently changed partitions instead of the whole table to speed up imports
2. B.a built-in tool that records how long each visual's queries and rendering take to find bottlenecks
3. C.the practice of lowering the number of distinct values in a column to improve compression and shrink model size
4. D.a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows

Answer + AI explanation with Pro

1. A.VertiPaq
2. B.Cardinality reduction
3. C.Performance analyzer
4. D.Incremental refresh

Answer + AI explanation with Pro

1. A.Cardinality reduction — a built-in tool that records how long each visual's queries and rendering take to find bottlenecks
2. B.Cardinality reduction — the practice of lowering the number of distinct values in a column to improve compression and shrink model size
3. C.Cardinality reduction — a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
4. D.Cardinality reduction — a policy that reloads only recently changed partitions instead of the whole table to speed up imports

Answer + AI explanation with Pro

1. A.a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
2. B.the practice of lowering the number of distinct values in a column to improve compression and shrink model size
3. C.a policy that reloads only recently changed partitions instead of the whole table to speed up imports
4. D.a built-in tool that records how long each visual's queries and rendering take to find bottlenecks

Answer + AI explanation with Pro

1. A.Performance analyzer
2. B.Aggregation table
3. C.Incremental refresh
4. D.Cardinality reduction

Answer + AI explanation with Pro

1. A.Incremental refresh — a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
2. B.Incremental refresh — a policy that reloads only recently changed partitions instead of the whole table to speed up imports
3. C.Incremental refresh — the practice of lowering the number of distinct values in a column to improve compression and shrink model size
4. D.Incremental refresh — the columnar in-memory engine that compresses imported data column by column for fast scanning

Answer + AI explanation with Pro

1. A.the practice of lowering the number of distinct values in a column to improve compression and shrink model size
2. B.a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
3. C.a built-in tool that records how long each visual's queries and rendering take to find bottlenecks
4. D.the columnar in-memory engine that compresses imported data column by column for fast scanning

Answer + AI explanation with Pro

1. A.Incremental refresh
2. B.VertiPaq
3. C.Performance analyzer
4. D.Aggregation table

Answer + AI explanation with Pro

1. A.Performance analyzer — a pre-summarized cached table that intercepts queries to answer them faster than scanning detailed source rows
2. B.Performance analyzer — a built-in tool that records how long each visual's queries and rendering take to find bottlenecks
3. C.Performance analyzer — the practice of lowering the number of distinct values in a column to improve compression and shrink model size
4. D.Performance analyzer — a policy that reloads only recently changed partitions instead of the whole table to speed up imports

Answer + AI explanation with Pro