Creating a New Analytics Report

A table is a grid that organizes data into rows and columns, often used for displaying precise values and comparisons.

Use: Displaying data in an organized format for easy reference (e.g. detailed information about sales).

A pivot table is a data summarization tool that allows you to reorganize and summarize selected columns and rows of data to obtain a desired report.

Use: Analyzing large datasets by summarizing, aggregating, or grouping data

A vertical bar chart uses rectangular bars that are oriented vertically to represent data values. Each bar’s height corresponds to the value it represents. 

Use: Comparing different categories or groups in an easy-to-visualize way (e.g. a comparison of marketing sources by number of contacts with each source).

A horizontal bar chart is similar to the vertical bar chart, but the bars are oriented horizontally.

Use: Comparing categories when labels are long or when it's easier to read horizontal bars (e.g. a comparison on 

A line chart uses a series of data points connected by straight lines to display trends over time.

Use: Showing changes over time or the relationship between two continuous variables.

An area graph is similar to a line chart, but the area below the line is filled with color to emphasize the volume of the data.

Use: Showing cumulative totals over time or illustrating the relationship between different categories.

A pie chart divides a circle into slices, where each slice represents a category’s proportion to the total.

Use: Showing percentage breakdowns or parts of a whole.

A Key Performance Indicator (KPI chart) visualizes key metrics or indicators to track performance against goals. It often uses gauges, progress bars, or traffic lights to indicate whether a target is met.

Use: Monitoring performance metrics or progress towards business objectives.

Alphanumeric characters, symbols, and spaces used to store textual information, such as descriptions, names, and addresses.

Also known as Boolean, represents logical values of true or false. Used for binary states and logical operations.

Represents numerical values, including integers and floating-point numbers. Used for quantities, measurements, and mathematical values.

Represents a specific point in time, including day, month, and year information. Used for storing dates and timestamps.

Represents monetary values, including currency unit and numeric value. Used for financial information like amounts, prices, and transactions.

Calculates the total number of entries in a field. Useful for tracking quantities, such as the number of transactions or interactions.

Examples:

• Track the total number of active users or completed tasks
• Count the number of leads generated by specific campaigns

Adds up all numeric values in a field. Commonly used for calculating totals, such as revenue or resource usage.

Examples:

• Calculate the total revenue generated in a specific time period
• Determine the total resources consumed in a project

Computes the mean of all values in a numeric field. Provides insights into typical values, such as average sales price or time to completion.

Examples:

• Analyze the average price of items in an inventory
• Review the average time required to resolve issues

Identifies the highest value in a field. Useful for determining peak performance, such as the highest revenue or score.

Examples:

• Identify the highest value achieved in a specific metric
• Highlight the top-performing team member by completed tasks

Identifies the lowest value in a field. Ideal for understanding baselines or lowest recorded metrics, like minimum cost or shortest duration.

Examples:

• Discover the lowest value in a dataset, such as costs or durations
• Determine the shortest time taken to complete a task

Groups data by individual days, providing the most granular view of day-to-day changes.

Examples:

• Monitor daily traffic to a website or app
• Track day-to-day sales performance

Groups data by weeks, allowing you to track trends over a 7-day period.

Examples:

• Compare the number of leads generated each week
• Analyze weekly engagement rates for a marketing campaign

Groups data by calendar months, making it easy to compare month-over-month performance.

Examples:

• Review monthly revenue or expenses
• Measure the month-over-month growth of a key metric

Groups data by fiscal or calendar quarters, ideal for tracking longer-term trends and aligning with business reporting cycles.

Examples:

• Analyze quarterly sales figures or product performance
• Report on quarterly financial results

Groups data by calendar years, offering a high-level view of annual performance and trends.

Examples:

• Assess annual trends in customer acquisition
• Compare year-over-year growth or decline for a specific metric

Filters data where the value starts with a specific string.

Example: Filtering a list of registration sources that begins with “Email”.

Filters data that includes a specific substring anywhere within the value.

Example: Finding units in a group of buildings containing “Townhome” in the name.

Filters data where the value does not include a specific substring.

Example: Excluding units from a list that have the word "Hold" in their status.

Filters data where the value ends with a specific string.

Example: Filtering a list of email addresses that end with “@spark.re”.

Filters data to match exactly with a specific value.

Example: Selecting contacts whose rating is "New" in a database.

Filters dates that fall within a specific range, inclusive.

Example: Finding sales that occurred between two dates.

Filters data where the value is empty (null or blank).

Example: Identifying records that have missing information in a field (e.g., missing phone numbers).

Currency
Number
Percentage

Filters data where the value is greater than a specified threshold.

Example: Finding units with list prices greater than $1,000,000.

Filters data where the value is greater than or equal to a specified threshold.

Example: Finding realtors who have sold 5 or more units.

Filters data where the value is less than a specified threshold.

Example: Finding units with list prices less than $500,000.

Filters data where the value is less than or equal to a specified threshold.

Example: Finding realtors who have sold 3 or fewer units.

Filters data where the value is not equal to a specific value.

Filters dates that do not fall within a specific range.

Example: Excluding contacts that have been contacted by phone during a specific time frame.

Filters data where the value is not empty (not null or blank).

Example: Showing records only where a description field is filled in.

Filters data where the date is not equal to a specific date.

Example: Excluding contacts that registered on a specific date.

Filters data where the date exactly matches a specific date.

Example: Finding a list of contacts who registered on a specific date.

Filters data where the date is either equal to or later than a specified date.

Example: Finding a list of contracts that were written on or after a specific date.

Filters data where the date is either equal to or earlier than a specified date.

Example: Finding a list of contracts that were written on or before a specific date.