Native Analytics On Elasticsearch With Knowi

Table of Contents

• Introduction
• Creating Your First Visualization
• Connecting to Elasticsearch
• Writing Your First Query
• Creating Your First Visualization
• Drilldowns
• Multi-Index Joins
• Joining Your Indexes
• Search-based Analytics & Self-Service Analytics with Knowi
• Summary

Introduction

Creating Your First Visualization

1. From the Playground dashboard, select “Datasources” on the left-hand side panel then click ‘New Datasource’
2. Select Elasticsearch from the list of datasources
3. Once in the ‘New Datasource’ page, start by giving your datasource a name
4. Enter your Elasticsearch credentials including the Endpoint URL and deployment username and password
5. Choose your Elasticsearch version (Version 5+ by default)
6. Click ‘Test Connection’ to confirm successful connection to the Elasticsearch cluster
7. Hit ‘Save’

Writing Your First Query

1. Open the Query Generator by clicking ‘Start Querying’
2. In the ‘Indexes’ drop down menu, choose the sending_activity index
3. In the ‘Metrics’ dropdown, select the fields customer, message_type, sent, and opened
4. Notice that in the Query Editor to the right, a native Elasticsearch JSON Query is being auto-generated (If you already knew the query you needed, you could’ve pasted or written it directly)
5. Click ‘Preview’ to to instantly preview the results, returned in tabular format
6. After previewing the results, give your query a name then hit ‘Save & Run Now’

Creating Your First Visualization

1. On the left-hand side panel, click ‘Dashboards’ 
2. Hit the ‘+’ icon to create a new dashboard and give it a name then click ‘OK’
3. Drag the widget/report you previously created into the dashboard. By default, it will be in grid form

1. On the top-right corner of the widget, click the ‘More Settings’ icon then select ‘Analyze’
2. In the following screen drag customer and message_type to the ‘Groupings/Dimensions’ section
3. Drag sent to the ‘Fields/Metrics section. In the ‘Operation’ dropdown, select ‘Sum’’
4. Notice that for Wells Fargo (first row), there were 22,406,800 total marketing messages sent

1. At the top of the screen, click the ‘Visualization’ tab which takes you to the visualization settings screen. We want to create a stacked column chart with customer in the x-axis and sum of sent in the y-axis
2. In the ‘Settings’ section under the ‘Visualization Type’ dropdown, select ‘Stacked Column’
3. In the ‘Options’ section under the ‘Grouping/Legend’ dropdown, select message_type. We can now visualize the total number of emails by message type for each customer
4. Hit the ‘Clone’ icon on the top right, to create a new widget derived from the original. This allows us to keep the original widget as is
5. Give the cloned widget a name, then add it to the dashboard

Drilldowns

1. On the top-right corner of the bar chart widget, click the ‘More Settings’ icon then select ‘Drilldowns’. The drilldown menu box will appear
2. Under the ‘Drilldown type’ dropdown, select ‘Widget’
3. For ‘Drill into’, select the name of the widget you want to drill into. 
4. For ‘Optional Drilldown Filters’ select ‘customer’ = ‘customer’ 
5. Hit ‘Save’
6. Remove the original grid chart widget from the dashboard
7. In the bar chart, click on any of the bars representing each customer (i.e. Wells Fargo)
8. By clicking on Wells Fargo, we were able to “drill down” in the original grid chart, but this time only showing details for the customer Wells Fargo

Multi-Index Joins

1. From the left-hand side panel of the Knowi UI, select ‘Queries’ 
2. Look for the ‘Elasticsearch - Demo’ query we ran earlier and click the ‘Edit’ icon
3. In our first query, let’s add the date and conversions field to the metrics
4. Click the ‘Join’ button on the lower-left side of the screen. Select your Elasticsearch datasource from the dropdown
5. This will populate the ‘Join Fields’ section and another ‘Query Builder’ and ‘Query Editor’ sections below the first one
6. In the ‘Indexes’ dropdown menu, choose the sending_activity_customer index
7. In the ‘Metrics’ dropdown menu, select your key field customer, followed by the street and state fields.
8. Notice that in this index contains mostly customer information-related fields

1. In the ‘Join Fields’ section, click ‘Join Builder’. Note that you can also type in the join free-hand in the text bar
2. Once the fields are retrieved, select ‘INNER JOIN’ as the ‘Join Type
3. Under ‘Left Field’ (sending_activity index side), select the key field customer
4. Under ‘Right Field’ (sending_activity_customer index side), you’ll also select the key field customer then save
5. Now, let’s click ‘Preview’ to see how our combined dataset looks like

Search-based Analytics & Self-Service Analytics with Knowi

1. Let’s find ask our data to find out the “maximum emails sent”
2. Notice that as you type, Knowi auto-suggest the question you are asking
3. When the results are returned, you can check to confirm that the ‘Max’ operation was performed on the sent field

1. Now, let’s find out where each of the customers are located by asking “street and state by customer”
2. Notice that it automatically knew to group the results by customer then return the address for each

1. Finally, let’s take things a little further and find out what our conversion rate it is by customer on a weekly basis
2. Notice that it automatically knew to apply the ‘Week’ operation on the date field, then group the results by customer and by week