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On this page, you can find documentation about x-bees Snalytics which provides all the information you need to keep on top of your business. Created: May 2022 Permalink: https://confluence.wildix.com/x/BYL6Bg |
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The answer opens and besides viewing its details. Also, using the Explore this data panel on the right, you can modify the answer by applying additional filters, adding/ replacing columns, choose data for comparison:
Keyword reference
Use keywords to help define a search.
General
| Note |
|---|
Note: When using the top or bottom keywords without specifying a number (n), the number defaults to |
| Keyword | Description |
|---|---|
| top n | Generates the top n items from a sorted result. Examples: top 10 sales rep revenue top sales rep by count sales for average revenue > 10000 sales rep average revenue for each region top |
| top n measure1 by attribute|measure2 | Calculates top n items, then sorts the top items by another measure or attribute. Contrast with top n (swaps the order of operations). Example: top 10 sales rep revenue by profit margin |
| bottom n | Generates the bottom n items from a sorted result. Examples: bottom 25 customer by revenue for each sales rep bottom revenue average bottom revenue by state customer by revenue for each sales rep bottom |
| sort by | Sorts the result set by an attribute or measure. Examples: revenue by state sort by average revenue descending |
| by <measure> | Treats the measure as an attribute and groups the result set by it. Examples: conversations by day |
Date
| Keyword | Examples |
|---|---|
| after | conversations after 10/31/2022 |
| before | conversations before 03/01/2022 |
between ... and ... | conversations between 01/30/2022 and 01/30/2022 |
| daily | conversations daily |
| daily year-over-year | growth of revenue by order date daily year-over-year |
| day | count monday restaurant |
day of week | conversations by day of week last 6 months |
| growth of … by ... | growth of sales by order date |
| growth of … by … daily | growth of sales by order date daily |
| growth of … by … monthly | growth of sales by date shipped monthly sales > 24000 |
| growth of … by … quarterly | growth of sales by date shipped quarterly |
| growth of … by … weekly | growth of sales by receipt date weekly for pro-ski2000 |
| hourly | conversations by callee hourly |
| last day by | conversations last day by callee |
| last month | conversations last month by callee |
last month by | conversations last month by day |
| last n days | conversations last 7 days |
| last n months | conversations last 10 months by day |
| last n quarters | conversations last 2 quarters by month by service |
| last n weeks | conversations last 10 weeks by day |
| last n years | conversations last 2 years by service |
last quarter | conversations last quarter |
| last week | conversations last week by service |
| last year | conversations last year by callee |
| month | conversations by month last year |
| month | conversations January |
| month to date | sales by product month to date sales > 2400 |
month year | conversations by service February 2022 |
| monthly | conversations by service monthly |
| monthly year-over-year | growth of revenue by receipt date monthly year-over-year |
| n days ago | conversations 2 days ago |
| last n days for each month | conversations 2 days for each month |
| last n days for each quarter | conversations last 15 days for each quarter |
| last n days for each week | conversations last 2 days for each week |
| last n days for each year | conversations last 300 days for each year |
| last n hours for each day | conversations last 2 hours for each day |
| n months | conversations last 6 months |
| n months ago | conversations 2 months ago by service |
last n months for each quarter | conversations last 2 months for each quarter |
| last n months for each year | conversations last 8 months for each year |
| n quarters ago | conversations 4 quarters ago by service |
| last n quarters for each year | last 2 quarters for each year |
| n weeks ago | conversations 4 weeks ago by callee |
| last n weeks for each month | conversations last 3 weeks for each month |
| last n weeks for each quarter | last 2 weeks for each quarter |
| last n weeks for each year | last 3 weeks for each year |
| n years | opportunities next 5 years by revenue |
| n years ago | conversations 2 years ago by service |
| next day | shipments next day by order |
| next month | appointments next month by day |
| next n days | shipments next 7 days |
| next n months | openings next 6 months location |
| next n quarters | opportunities next 2 quarters by campaign |
next n weeks | shipments next 10 weeks by day |
| next n years | projected deals next 5 years |
| next quarter | opportunities next quarter amount > 30000 |
| next week | shipments next week by store |
| next year | opportunities next year by sales rep |
quarter to date | sales by product quarter to date for top 10 products by sales |
quarterly | conversations quarterly by service |
quarterly year-over-year | growth of revenue by date shipped quarterly year-over-year |
| this day | conversations this day by callee |
this month | conversations this month by day |
| this quarter | conversations this quarter by callee |
| this week | conversations this week by service |
| this year | conversations this year by callee |
| today | conversations today by callee |
| week | conversations by week last quarter |
| week to date | sales by order date week to date for pro-ski200 |
| weekly | conversations weekly |
| weekly year-over-year | growth of revenue by date shipped weekly year-over-year |
| year | revenue by product 2014 product name contains snowboard |
year to date | sales by product year to date |
| yearly | shipments by product yearly |
| yesterday | sales yesterday for pro-ski200 by store |
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Comparative
| Keyword | Examples | ||
|---|---|---|---|
| all | conversations uk_support vs all
| ||
| between... and... | revenue between 0 and 1000 | ||
= (equal) | unique count visitor by store purchased products = 3 for last 5 days | ||
| everything | revenue asia vs everything
| ||
| > (greater than) | sum sale amount by visitor by product for last year sale amount > 2000 | ||
>= (greater than or equal) | count calls by employee lastname >= m | ||
< (less than) | unique count visitor by product by store for sale amount < 20 | ||
<= (less than or equal) | count shipments by city latitude <= 0 | ||
!= (not equal) | sum sale amount region != canada date != last 5 days | ||
vs, versus | conversations uk_support vs us_support |
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In / Not in
| Keyword | Description |
|---|---|
| in | Query in query search (intersection of two sets). Must match last attribute before keyword with first attribute inside subsearch. Syntax: attribute in (attribute subsearch) Examples: store name in (top 10 store name by sales footwear) product name 2014 product name in (product name 2013) sales |
not in | Relative complement of two sets. Must match last attribute before keyword with first attribute inside subsearch. Syntax: attribute not in (attribute subsearch) Example: product name 2014 product name not in (product name 2013) sales |
...
Your search must have at least one attribute and one measure to be represented as a column chart.
Stacked columns
The stacked column chart is similar to the column the column chart, but with one major difference. It includes a legend, which divides each column into additional sections, by color.
| Note |
|---|
Note: You can only use an attribute to slice with color. |
Bar charts
The bar chart is very similar to the column chart. The only difference is that it is oriented horizontally, instead of vertically. The length of the bar is proportional to the data value.
Your search needs at least one attribute and one measure to be represented as a bar chart.
Stacked bar charts
Just like stacked columns, stacked bars combine the different secondary dimensions into a single stacked bar.
The stacked bar chart is similar to the bar the bar chart, but it also includes a legend, which divides each bar into additional sections by color.
| Note |
|---|
Note: You can only use an attribute to slice with color. |
Line charts
Line charts are good at showing trends over intervals of time. Like the column the column chart, the line chart is one of the simplest, yet most versatile. It is often chosen as default visual representation. Line charts display your data as a series of data points connected by straight line segments. The system orders the measurement points by the x-axis value.
Your search must have at least one attribute and one measure to be represented as a line chart. If your search has multiple attributes, you can slice with color to sort by the second attribute.
Pie charts
The pie chart is a classic chart type that displays your search in a circle.
Pie charts divide your data into sectors that each represent a proportion of a whole circle. To display the exact values of each slice and the percentage values, select the Edit chart configuration icon > Settings > icon > Settings > All labels.
Your search needs at least one attribute and one measure to be represented as a pie chart. Also, there must be fewer than 250 values in the attribute column.
Pie in pie charts
The pie in pie chart can be created from a regular pie chart in order to compare more than one component of an attribute. Pie in pie charts show two concentric pie charts comparing different measures.
To see a pie in pie chart, assign two different measures to the Size section under Edit chart configuration.
Scatter charts
The scatter chart is useful for finding correlations or outliers in your data. Scatter charts display your data as a collection of points, which can either be evenly or unevenly distributed. Each point is plotted based on its own axes values. This helps you determine if there is a relationship between your searched columns.
Your search needs at least one attribute and one measure to be represented as a scatter chart.
Bubble charts
The bubble chart is a variation of the scatter chart, and its data points appear as bubbles. Your search must have at least one attribute and two measures to generate a bubble chart. The bubble chart displays three to five dimensions or measures of data. In addition to the traditional X and Y axis, the size of the bubble represents a measurement. Bubble charts can show two more attributes, when you slice and/or slice by color.
Pareto charts
The pareto chart is a type of chart that contains both columns and a special type of line chart.
The individual values of a pareto chart are represented in descending order by columns, and the cumulative percent total is represented by the line. The y-axis on the left is paired with the columns, while the y-axis on the right is paired with the line. By the end of the line, the cumulative percent total reaches 100 percent.
Your search needs at least one attribute and one measure to be represented as a pareto chart.
Waterfall charts
The waterfall chart shows how an initial value is affected by a series of intermediate positive or negative values. Waterfall charts are good for visualizing positive and negative growth, and therefore work well with the growth over time keyword. The columns are color-coded to distinguish between positive and negative values. Your search needs at least one attribute and one measure to be represented as a waterfall chart.
Treemap charts
The treemap chart displays hierarchical data as a set of nested rectangles.
Treemap charts use color and rectangle size to represent two measure values. Each rectangle, or branch, is a value of the attribute. Some branches can contain smaller rectangles, or sub-branches. This setup makes it possible to display a large number of items in an efficient way. You can rearrange the columns of your search into category, color, and size under under Edit chart configuration.
Your search needs at least one attribute and two measures to be represented as a treemap chart.
Heatmap charts
The heatmap chart displays individual data values in a matrix following a color scale. The value of each cell depends on the measure you choose under Edit chart configuration.
Line column charts
The line column chart combines the column and line charts. Your search needs at least one attribute and two measures to be represented as a line column chart.
Line column charts display one measure as a column chart, and the other as a line chart. Each of these measures has its own y-axis.
Stacked line column charts
This chart is similar to the line column chart, except that it divides its columns with an attribute in the legend. The line stacked column chart combines stacked column and line chartscombines stacked column and line charts. There are two y-axes, one for each measure.
Funnel chart
The funnel chart shows a process with progressively decreasing proportions amounting to 100 percent in total. You can visualize the progression of data as it passes from one phase to another. Data in each of these phases is represented as different proportions.
Your search needs at least one attribute and one measure to be represented as a funnel chart. The attribute must contain 50 or fewer values.
Pivot table
Pivot tables are charts that enable you to explore an alternate visualization of your data in a wide, customizable table. With pivot tables, you can use the same table to visualize some of your data horizontally, and some data vertically. You can restructure your pivot table by dragging and dropping the measures and attributes under Edit chart configuration, or by dragging and dropping column headings on the table itself.
Sankey charts
The Sankey chart type contains both columns and a special type of line chart. Sankey diagrams illustrate a flow through, a process, or a system. When you build a Sankey chart, you must provide at least 2 (two) attributes and one measure. Your x-axis attributes can contain at most 13 values; any more and you cannot view a SanKey chart.
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