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Query 1

Query 2

Query 3

Query 4

Query 5

Query 6

Query 7

Complex Media - Global KPI dashboard
February 17, 2017 · Refreshed over 2 years ago

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SELECT 0.29 AS rate UNION ALL SELECT 0.32
SELECT 0.29 AS rate UNION ALL SELECT 0.32
SELECT 'premium' AS type, 0.24 AS rate UNION ALL SELECT 'free',0.76
SELECT 'premium' AS type, 0.24 AS rate UNION ALL SELECT 'free',0.76
SELECT 17.1 AS session_length UNION ALL SELECT 15.2
SELECT 17.1 AS session_length UNION ALL SELECT 15.2
SELECT week, retention_rate FROM modeanalytics.retention_rate_sample ORDER BY 1
SELECT week, retention_rate FROM modeanalytics.retention_rate_sample ORDER BY 1
SELECT DATE_TRUNC('month',occurred_at) AS month, COUNT(*)*33 AS signups FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' -- AND occurred_at BETWEEN '2013-06-03' AND '2013-09-30' GROUP BY 1 ORDER BY 1
SELECT DATE_TRUNC('month',occurred_at) AS month, COUNT(*)*33 AS signups FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' -- AND occurred_at BETWEEN '2013-06-03' AND '2013-09-30' GROUP BY 1 ORDER BY 1
SELECT DATE_TRUNC('month',occurred_at) AS month, COUNT(*)*33 AS signups FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' AND occurred_at BETWEEN '2014-04-01' AND '2014-05-30' GROUP BY 1 ORDER BY 1
SELECT DATE_TRUNC('month',occurred_at) AS month, COUNT(*)*33 AS signups FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' AND occurred_at BETWEEN '2014-04-01' AND '2014-05-30' GROUP BY 1 ORDER BY 1
SELECT DATE_TRUNC('week',occurred_at) AS week, COUNT(*)*113 AS rev FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' AND occurred_at BETWEEN '2013-06-03' AND '2014-05-18' GROUP BY 1 ORDER BY 1
SELECT DATE_TRUNC('week',occurred_at) AS week, COUNT(*)*113 AS rev FROM modeanalytics.fake_growth_events WHERE event_name = 'complete_signup' AND occurred_at BETWEEN '2013-06-03' AND '2014-05-18' GROUP BY 1 ORDER BY 1
<link href="https://fonts.googleapis.com/css?family=Montserrat" rel="stylesheet"> <style type="text/css"> html, body { font-family: 'Montserrat', sans-serif !important; background: #E3E2EB !important; } .chart { background-color: #E3E2EB; border: none; } .mode-embed .mode-object { border: none; background: #E3E2EB; } </style> <link rel="stylesheet" href="https://mode.github.io/alamode/alamode.min.css"> <script src="https://mode.github.io/alamode/alamode.min.js"></script> <div class="mode-header embed-hidden"> <h1>{{ title }}</h1> <p>{{ description }}</p> </div> <div class="mode-grid container"> <div class="row" data-row-height="small"> <div class="col-md-3"> <mode-text id="text_5f726aa7-7c41-41bf-d475-1e75eef8b5fc" dataset="dataset" options="text_options"> <p class="ql-align-center"><img 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"></p> <p><br></p> </mode-text> </div> <div class="col-md-3"> <mode-chart id="chart_4e5f5445d993" dataset="dataset" options="chart_options"></mode-chart> </div> <div class="col-md-3"> <mode-chart id="chart_341569a8ad5c" dataset="dataset" options="chart_options"></mode-chart> </div> <div class="col-md-3"> <mode-chart id="chart_a35da37ee90c" dataset="dataset" options="chart_options"></mode-chart> </div> </div> <div class="row"> <div class="col-md-6"> <mode-chart id="chart_c7e360617d80" dataset="dataset" options="chart_options"></mode-chart> </div> <div class="col-md-6"> <mode-chart id="chart_688a6aef5b60" dataset="dataset" options="chart_options"></mode-chart> </div> </div> <div class="row" data-row-height="small"> <div class="col-md-12"> <mode-chart id="chart_92acf812eb5c" dataset="dataset" options="chart_options"></mode-chart> </div> </div> </div> <script> alamode.customChartColors({ charts: ["chart_a35da37ee90c"], colors: { 0: "#895FD8", 1: "#1ACCE0" } }) alamode.customChartColors({ charts: ["chart_c7e360617d80"], colors: { 0: "#895FD8" } }) alamode.customChartColors({ charts: ["chart_688a6aef5b60"], colors: { 0: "#1ACCE0" } }) alamode.customChartColors({ charts: ["chart_92acf812eb5c"], colors: { 0: "#1ACCE0" } }) </script>
{{ dataSourceName(params.queryId) }}

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