Skip to main content

Changelog

The latest features, product improvements and bug fixes from the Propel team.

changelog-header-decoration
· 2 min read

In addition to counters and time series, we now support leaderboard queries. Leaderboards are great for visualizing the “top N” of something, such as “the top 10 salespeople of the month” or “the top 100 events last year.” You can query it with a timeRange set of dimensions to group on, a sort order, filters, and a lowLimit. For example,

query {
  metricByName(uniqueName: "sales")  {
    leaderboard  ({
      timeRange: { relative: "THIS_MONTH" },
      dimensions: [{ columnName: "SALES_PERSON" }],
      rowLimit: 10
    }) {
      headers
      rows
    }
  }
}

The result you get back is an array of headers and an array of rows:

{
  "headers": ["SALES_PERSON", "SALES"],
  "rows": [
    ["Alice", "100"],
    ["Bob", "99"],
    ["Carol", "80"],
    ["Dave", "76"],
    ["Erin", "75"],
    ["Frank", "75"],
    ["Grace", "66"],
    ["Heidi", "63"],
    ["Ivan", "34"],
    ["Judy", "33"]
  ]
}

Perfect for piping into your favorite graph visualization library! For example, here we use ECharts to visualize a leaderboard from the state of California:

A screenshot of a leaderboard visualization. Rows are labeled with areas from the state of California and are sorted in descending order. A screenshot of a leaderboard visualization. Rows are labeled with areas from the state of California and are sorted in descending order.

· One min read

Sometimes you need to define Metrics with a subset of the data you have. For example, if you have a Metric like revenue, you’ll want to exclude all sales records where the type is “PROMOTION” or “TRIAL”.

You can now define Metrics with a subset of records of a Data Pool. When defining a Metric via the Console or API, you can create Metric Filters to include or exclude records from the Metric values. See below for an example where we define a Metric to sum up records where “AREA” equals “California”.

An animated screen capture of the Propel console, showing how to use Metric Filters to select a subset of records from a Data Pool. An animated screen capture of the Propel console, showing how to use Metric Filters to select a subset of records from a Data Pool.

· One min read

Different products need to expose different Metrics to their end-users. For example, e-commerce products expose Sum Metrics like “Total Sales”, Count Metrics like “Number of orders”, and Count Distinct Metrics like “Unique visitors”.

When building in-product analytics, you can now define Sum, Count, or Count Distinct metrics for your product in a single place. Front-end engineers can access the Metric data with time series or counter queries using the Metrics API.

An animated screen capture of Propel’s GraphQL Explorer, showing how to query a Metric using the GraphQL API with various time granularities and filters. An animated screen capture of Propel’s GraphQL Explorer, showing how to query a Metric using the GraphQL API with various time granularities and filters.

· One min read

You can now connect Propel to your Snowflake account. This connection lets you use your Snowflake data in your customer-facing web and mobile applications with Propel's GraphQL API. Propel manages all the caching, optimization, authorization, and API infrastructure so that your teams can focus on the product experience. The Snowflake Data Source is now available to all customers.

An animated screen capture of the Propel console, showing how to create a Data Source and the numerous checks that confirm the connection is working An animated screen capture of the Propel console, showing how to create a Data Source and the numerous checks that confirm the connection is working

Read the blog posts:​