Knowi's Natural Language capabilities are a powerful way to enable self-service analytics for non-technical users, by asking questions in plain English to drive insights and visualizations quickly. This empowers any member and individual with the ability to make better, data-driven decisions, at any time.
Natural Language capabilities are available for use across all datasets and widgets within a dashboard. It can be accessed using the Natural Language/Self-Serve Analytics icon on a widget. As you explore your data with natural language, Knowi recommends questions based on your input and the data source available. The technology works by translating your natural language query to Cloud9QL statement to resolve your request.
NLP Across Datasets
Using natural language processing at the dashboard queries across all datasets within your account. Auto-complete suggestions will be recommended as you type based on the associated dataset. For example, if you had multiple datasets powering a single sales and marketing dashboard, and you wanted information on your latest marketing activity, typing your query matches the requested fields and aggregation to the datasets the user has access to.
When using NLP across datasets, you can explicitly request which datasets/query to use by incorporating "from" at the end of your query. For example,
what is the average revenue by sales_representation by region from product sales (prod)
From the example above, product sales (prod) is the name of the dataset/query containing the sales information.
Enable NLP Usage Across Datasets
Using NLP across datasets is a customer user feature that must be enabled by an admin role. To enable this feature for users:
-
From the Knowi panel, click Settings and navigate to the User Settings page
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In the Account Settings tab, click the NLP ACCESS switch to ENABLE/DISABLE the feature
NLP Within Widgets
Unlike across datasets, for use within widgets, natural language queries are applied directly on the dataset powering that widget.
NLP is available on all widgets inside a dashboard from the widget menu and available to all users, regardless of user role/permission.
Dataset Tags
You can tag your dataset fields with text strings making it easier to execute NLP queries. These tags do not change your data model but instead are used in Knowi services such as NLP.
For example, if your data model contains the following fields employee_firstname,
employee_lastname, sales, department. You can add one or more tags to synonymize select fields i.e. department can hold the following tags: team, group. While employee_lastname and employee_firstname share the tags: associates, rep
To add tags:
- Select the dataset. On any widget, click More Settings -> Data Diagram.
- Click the NLP tab. Under Synonyms, select the fields, enter tags, then click Save.
- Decide how to query with NLP: on a widget, within a dashboard, or across all datasets
Examples
The following are examples of natural language queries to get you started:
Simple field selection
"bounced, sent, customer"
"bounced and sent and customer"
"Show me all for Wells Fargo"
"all for customer Wells Fargo"
"all fields for customer like Wells Fargo"
"bounced and sent for Wells Fargo"
Aggregations
"Sum of sent sum of open by customer"
"Total sent by customer by week"
"Total sent, Total bounced for Wells Fargo"
"Average Sent, Total bounced by customer by campaign_name for newsletter"
Dates
"all for date after January this year"
"average close monthly"
"close by date for january this year"
"close by date for january last year"
"close by date between january and march this year"
"From 2022 to 2024"
"Between 2022 and 2024"
"Since 2024, From 2024, Until 2024"
"In 2024" "from June 1st to Jun 4th"
NLP Ranking
In Natural Language Processing, ranking often refers to ordering or prioritizing items based on their relevance to a particular query or context. In the Knowi NLP prompt, users can rank their data in ascending or descending orders, fetch the top five entries, etc.
Here are a few examples:
"Top 5 names for (total/average) opens"
"Rank name ascending/desc/asc/descending"
"Top 5 names since September last year"
"Arrange the names in ascending/ descending order"
"Rank by name"
Edit Search-Based Analytics
Using Knowi's Search-based Analytics available on the Dataset page, the settings related to natural language queries can be edited for the following:
NLP Indexer: Useful when you want to exclude a dataset from search-based analytics/NLP. By default, it’s on. Turn off indexing for NLP.
NLP Slack Indexer: Turn off indexing for slack NLP. By default, it’s on.
Synonyms: Specify one or more synonyms that can be used in NLP for the Dataset.
Note: Users can add more than one set of synonyms and remove them. To add, click +; to remove, click -.
Data Limit: Limit the number of records to process for NLP. Set to 0 for unlimited. Defaults to 200K when empty.
Skip NLP Processing: Specify one or more fields that will be skipped in NLP for the Dataset.
Default NLP Date: Specify the default NLP date to fetch in NLP processing for the Dataset. A random date is selected for NLP when empty.
Indexable fields: Gives you control over the ability to set unique values on string fields. These fields are often used as a part of a condition.
Index values from another Dataset: Pointing to other datasets gives you fine-grained values that can be driven from another dataset. The values are determined for the first column of the dataset, or if the dataset has multiple columns, the column name matches the field to index. By default, the values are sampled from the dataset, if non-direct.
Alternatively, you can navigate to the edit settings of the Search-Based Analytics by clicking on the edit button on the dataset within the dataset lineage diagram.
Extended Support For Synonyms
Multiple keywords can be associated with a field. Instead of a field, you can also specify calculations or Cloud9QL functions. For example, if the bounced rate per million is defined as (bounced/sent)*1000000 set the definition as a field name and set bounced rate per million as the synonym.
Configure Runtime Parameters for Synonyms
You can use runtime parameters into the synonyms where a user can specify/define one or more parameters with a value in the synonyms fields. It will help the users to return the results in an optimized and quicker way for a particular given NLP query.
It allows the users to change runtime param values upon on your NLP query but the idea of changing the runtime params is that the user can define params once in query settings and then use them in the widget Analyze screen (which appears when the user applies the NLP query on the widget) and then the user can fine-tune values of runtime params.
For example, you can pass the runtime parameters *(bounced/$c9_someval$(100)$[Threshold]$) + 5* in the synonyms field and provide any related label to this param named as *bouncedThresholdQuery* as illustrated below.
“bounced” is a field name from source data.
“$c9_sometoken$” is defined as the c9 runtime param.
The default value and label are optional. The 100 is the default value and “Threshold” is a label in the sample above.
Note: After applying the NLP query synonyms, you can change the “Threshold” value. It will reset the data and instantly return the latest result on your screen based on your executed input values query.
Embedding Search-based Analytics (NLP)
Using Knowi's Search Analytics can be embedded in your application through Single Sign-On. Try it out.
Similar to embedding with SSO and the Javascript API, the steps to embedding Search Analytics is almost identical and can be achieved in three steps:
1. User Token: Create a Knowi user token for a new or existing user
curl -i -X POST -d "user=email@domain.com&ssoCustomerToken=<SSO_TOKEN>" https://knowi.com/sso/user/create
2. Session Token: Create a Knowi session token with the user token from step 1
curl -i -X POST -d "user=email@domain.com&userToken=<USER_TOKEN>" https://knowi.com/sso/session/create
3. Embed: Write a Javascript file with the session token returned from step 2
function loadSearchAnalytics() {
Knowi.render('#knowi-div', {
type: 'nlp',
token: "BYhXXCeu0Ego8zA1FqtLOOM4BDWot5AYBLI7PWrQTbsie",
url: 'https://www.knowi.com',
view: {
nlpOptions: {
icon: "off",
css: {
background: 'transparent'
},
placeholder: "Try: total sales for canada this week",
}
}
}, function () {
});
}
Note: For embedding Search Analytics,type must benlp
Search-Analytics Resources:
Natural Language Processing Settings
You can edit the natural language processing settings given under the user settings to configure NLP Across Datasets, Index By Default, NLP Bot Integration, and more.
NLP Across Dataset: Enables natural language interface across datasets.
NLP Bot Integration: Enables natural language interface for slack/teams.
NLP Favorites: Configure a list of NLP queries per category type displayed when a user types in /knowi. Typically, these would be the most commonly used questions. The format can be as follows:
Category1
Category2
Category3
/knowi your_nlp_question1
/knowi your_nlp_question2
NLP Synonyms: Configure a list of NLP synonyms. The format can be as follows:
FieldName1=Synonym1,Synonym2,Synonym3
FieldName2=Synonym1,Synonym2,Synonym3
Note: Users can add more than one set of synonyms and remove them. To add, click +; to remove, click -.