Search Keywords

1. Compare

This section lists all of the circumstances that “vs” keyword suits.

vs (case-insensitive)

e.g:

• Time & Date Comparison:

  — e.g: 2019 VS 2020 VS 2021 Sales

• Specific Attribute (values in column) Comparison:

  — e.g: “West” vs “East” Sales

• Partial vs all:

  — e.g: Region Vs all Sales

2. Growth

Growth keywords show data growth at different time frequency.

Note:

1. Period-over-Period: vs last period
2. Periods over Year-over-Year: vs same period last year

Period-over-Period Growth Amount:

• growth amount of yy [measure] by xx [date] daily/weekly/monthly/quarterly/yearly

  — e.g: growth amount of Sales by Order_Date quarterly

Period-over-Period Growth Rate:

• growth of yy [measure] by xx [date] daily/weekly/monthly/quarterly/yearly

  — e.g: growth of Sales by Order_Date monthly

Periods over Year-over-Year Growth Amount:

• growth amount of yy [measure] by xx [date] daily/weekly/monthly/quarterly/yearly year over year

  — e.g: growth amount of Sales by Order_Date weekly year over year

Periods over Year-over-Year Growth Rate:

• growth of yy [measure] by xx [date] daily/weekly/monthly/quarterly/yearly year over year

  — e.g: growth of Sales by Order_Date yearly year over year

3. Sort

Sort keywords rank data and can display the best/worst data.

Note: The aggregation method includes: sum, min, max, average, std_deviation, variance, count, count_distinct.

Sort:

• sort by (aggregation) yy [measure] xx [attribute]

  — e.g: sort by average Sales Region

• sort by (aggregation) yy [measure] xx [attribute]

  — e.g: sort by Sales descending Product_Name

• sort by (aggregation) yy [measure] xx [attribute]

  — e.g: sort by sum Sales ascending Region

Single Sort:

• top (aggregation) yy [measure] xx [attribute]

  — e.g: top sum Sales Product_Name

• top n [number] (aggregation) yy [measure] xx [attribute]

  — e.g: top 5 sum Sales City

• bottom (aggregation) yy [measure] xx [attribute]

  — e.g: bottom sum Sales Customer_Name

• bottom n [number] (aggregation) yy [measure] xx [attribute]

  — e.g: bottom 8 sum Profit State

• top a [number] to b [number] (aggregation) yy [measure] xx [attribute]

  — e.g: top 3 to 5 sum Sales Product_Name

• bottom a [number] to b [number] (aggregation) yy [measure] xx [attribute]

  — e.g: bottom 3 to 5 sum Sales Product_Name

Group Sort:

• top (aggregation) yy [measure] by xx [attribute]

  — e.g: top sum Sales by Region

• bottom (aggregation) yy [measure] by xx [attribute]

  — e.g: bottom sum Sales by Product_Name

• top n [number] (aggregation) yy [measure] by xx [attribute]

  — e.g: top 10 sum Sales by City

• bottom n [number] (aggregation) yy [measure] by xx [attribute]

  — e.g: bottom 5 sum Sales by Region

• top a [number] to b [number] (aggregation) yy [measure] by xx [attribute]

  — e.g: top 5 to 10 average Sales by Sub_Category

• bottom a [number] to b [number] (aggregation) yy [measure] by xx [attribute]

  — e.g: bottom 3 to 5 average Sales by Product_Name

4. String

String keywords add filters on attributes.

• xx [attribute] begins with

  — e.g: Product_Name begins with “#” Sales

• xx [attribute] not begins with

  — e.g: Product_Name not begins with “#” Sales

• xx [attribute] ends with

  — e.g: Product_Name ends with “Envelopes” Sales

• xx [attribute] not ends with

  — e.g: Product_Name not ends with “Envelopes” Sales

• xx [attribute] contains

  — e.g: Product_Name contains “phone” Sales

• xx [attribute] not contains

  — e.g: Product_Name not contains “phone” Sales

5. Range

This section lists keywords that can restrict data within a range.

Filtering:

• xx [attribute] is null

  — e.g: Product_Name is null Sales

• xx [attribute] is not null

  — e.g: Product_Name is not null Profit

• yy [measure] > n [number]

  — e.g: Sales > 1000

• yy [measure] <</span> n [number]

  — e.g: Profit < 500

• xx =

  — e.g: Region = “Central”
      Sales = 500

• xx !=

  — e.g: Region != “Central”
      Profit != 400

• yy [measure] >= n [number]

  — e.g: Profit >= 800

• yy [measure] <= n [number]

  — e.g: Quantity <= 100

6. Numbers

This section shows aggregation keywords.

Attribute Column:

• count xx

  — e.g: count Order_ID

• unique count xx

  — e.g: unique count Customer_Name

Measure Column:

• sum yy

  — e.g: sum Profit

• max yy

  — e.g: max Profit

• min yy

  — e.g: min Profit

• average yy

  — e.g: average Profit

• variance yy

  — e.g: variance Profit

• standard deviation yy

  — e.g: standard deviation Profit

• distribution yy

  — e.g: distribution Profit

• yy between a [number] and b [number]

  — e.g: Profit between 1000 and 5000

7. Time

This section lists keywords relevant to detailed time (hour, minute).

Past Time:

• last n [number] minutes

  — e.g: last 30 minutes Quantity

• last minute

  — e.g: last minute Profit

• last n [number] hours

  — e.g: last 6 hours Sales

• last hour

  — e.g: last hour Order_ID

• n [number] minutes ago

  — e.g: 60 minutes ago Customer_Name

• n [number] hours ago

  — e.g: 6 hours ago Order_ID

Future Time:

• next minute

  — e.g: next minute Target

• next hour

  — e.g: next hour Target

• next n [number] minutes

  — e.g: next 60 minutes Target

• next n [number] hours

  — e.g: next 6 hours Target

Time Period:

• first n [number] hours for each day

  — e.g: first 3 hours for each day Order_Date Profit

• last n [number] hours for each day

  — e.g: last 3 hours for each day Order_Date Profit

• hourly

  — e.g: hourly Quantity

8. Date

Date keywords filter out time in several dimensions, including current dates, relative dates, time period, and etc.

Past of Relative Dates:

• before “yyyy”

  — e.g: before “2022” Profit

• before “yyyy/mm”

  — e.g: before “2021/8” Profit

• before “yyyy/mm/dd”

  — e.g: before “2020/06/30” Profit

• before “yyyy/mm/dd hh:mm:ss”

  — e.g: before “2020/05/30 23:59:00” Profit

Past of Current Dates:

• yesterday

  — e.g: yesterday Quantity

• last Monday/Tuesday/Wednesday/Thursday/Friday/Saturday/Sunday

  — e.g: last Friday Product_Name

• last weekend

  — e.g: last weekend Sales

• last week

  — e.g: last week Sales

• last month

  — e.g: last month Sales

• last quarter

  — e.g: last quarter Sales

• last year

  — e.g: last year Sales

• last n [number] days

  — e.g: last 14 days Profit

• last n [number] weeks

  — e.g: last 2 weeks Profit

• last n [number] months

  — e.g: last 2 months Profit

• last n [number] quarters

  — e.g: last 3 quarters Customer_Name

• last n [number] years

  — e.g: last 3 years Profit

• n [number] days ago

  — e.g: 15 days ago count Order_ID

• n [number] weeks ago

  — e.g: 5 weeks ago Quantity

• n [number] months ago

  — e.g: 3 months ago Quantity

• n [number] quarters ago

  — e.g: 3 quarters ago Sales

• n [number] years ago

  — e.g: 2 years ago Profit

Current Dates:

• today

  — e.g: today Customer_ID

• week to date

  — e.g: week to date Quantity

• month to date

  — e.g: month to date Sales

• quarter to date

  — e.g: quarter to date Profit

• year to date

  — e.g: year to date Sales

Future of Relative Dates:

• after “yyyy”

  — e.g: after “2021” Sales

• after “yyyy/mm”

  — e.g: after “2021/09” Quantity

• after “yyyy/mm/dd”

  — e.g: after “2021/05/30” Customer_Name

• after “yyyy/mm/dd hh:mm”

  — e.g: after “2021/12/08 17:08:12” Product_Name

Future of Current Dates:

• tomorrow

  — e.g: tomorrow Target

• next Monday/Tuesday/Wednesday/Thursday/Friday/Saturday/Sunday

  — e.g: next Thursday Target

• next weekend

  — e.g: next weekend Target

• next week

  — e.g: next week Target

• next month

  — e.g: next month Target

• next quarter

  — e.g: next quarter Target

• next year

  — e.g: next year Target

• next n [number] days

  — e.g: next 30 days Target

• next n [number] weeks

  — e.g: next 3 weeks Target

• next n [number] months

  — e.g: next 3 months Target

• next n [number] quarters

  — e.g: next 2 quarters Target

• next n [number] years

  — e.g: next 2 years Target

Segment Dates:

• yyyy

  — e.g: 2021 Sales

• January/February/March/April/May/June/July/August/September/October/November/December

  — e.g: August Profit

• “yyyy/mm”

  — e.g: “2020/08” Sales

• “yyyy/mm/dd”

  — e.g: “2020/8/30” Quantity

• Monday/Tuesday/Wednesday/Thursday/Friday/Saturday/Sunday

  — e.g: Friday Sales

• weekend

  — e.g: weekend Quantity

• xx [date] between “yyyy” and “yyyy”

  — e.g: Order_Date between “2020” and “2021” Sales

• xx [date] between “yyyy/mm” and “yyyy/mm”

  — e.g: Ship_Date between “2020/01” and “2021/06” Profit

• xx [date] between “yyyy/mm/dd” and “yyyy/mm/dd”

  — e.g: Ship_Date between “2020/06/01” and “2021/06/01” Sales

• xx [date] between “yyyy/mm/dd hh:mm” and “yyyy/mm/dd hh:mm”

  — e.g: Order_Date between “2020/06/01 12:00” and “2021/06/01 18:00” Profit

• by day

  — e.g: by day Sales

• by day of week

  — e.g: by day of week Sales

• by week

  — e.g: by week Sales

• by month

  — e.g: by month Sales

• by quarter

  — e.g: by quarter Sales

• by year

  — e.g: by year Sales

• daily

  — e.g: daily Profit

• weekly

  — e.g: weekly Profit

• monthly

  — e.g: monthly Profit

• quarterly

  — e.g: quarterly Profit

• yearly

  — e.g: yearly Profit

• first n [number] days for each week/month/quarter/year

  — e.g: first 20 days for each year Sales

• first n [number] weeks for each month/quarter/year

  — e.g: first 2 weeks for each month Sales

• first n [number] months for each quarter/year

  — e.g: first 2 months for each quarter Sales

• first n [number] quarters for each year

  — e.g: first 2 quarters for each year Sales

• last n [number] days for each week/month/quarter/year

  — e.g: last 20 days for each month Sales

• last n [number] weeks for each month/quarter/year

  — e.g: last 2 weeks for each quarter Sales

• last n [number] months for each quarter/year

  — e.g: last 2 months for each year Sales

• last n [number] quarters for each year

  — e.g: last 2 quarters for each year Sales

9. More

This section combines several keywords together to do advanced analysis.

Note: The aggregation method includes: sum, min, max, average, std_deviation, variance, count, count_distinct.

Compound Search:

• yyyy vs yyyy growth amount of yy [measure] by xx [date] daily/.../yearly by day/.../by year

  — e.g: 2019 vs 2020 growth amount of Profit by Order_Date monthly by quarter

• month [January/…] vs month growth of yy [measure] by xx [date] daily/.../yearly by day/.../by year

  — e.g: July vs August growth of Sales by Order_Date weekly by day of week

• day(xx [date]) </<=/>/>= day(now( ))

  — e.g: day(Order_Date) < day(now ( )) Order_Date Sales

• day(xx [date]) </<=/>/>= day(now( )) last n day/.../year daily/.../yearly yy [measure]

  — e.g: day(Order_Date) >= day(now ( )) last 5 months daily Profit

• yyyy [date] vs yyyy [date] top n [number] (aggregation) yy [measure] xx [attribute]

  — e.g: 2020 vs 2021 top 5 sum Profit Customer_Name

• yyyy [date] vs yyyy [date] top n [number] (aggregation) yy [measure] by xx [attribute] zz [attribute]

  — e.g: 2020 vs 2021 top 5 sum Profit by Region Customer_Name

• “aa” [column value] vs “bb” [column value] top n [number] (aggregation) yy [measure] xx [attribute]

  — e.g: “West” vs “East” top 3 sum Sales Product_Name

• “aa” [column value] vs “bb” [column value] top n [number] (aggregation) yy [measure] by xx [attribute] zz [attribute]

  — e.g: “West” vs “East” top 3 sum Sales by Segment Product_Name