Knowi enables visualization, warehousing, and reporting automation from Oracle along with other structured and unstructured datasources.
Overview
- Connect, extract, and transform data from your Oracle database, using one of the following options:
a. Through our UI connect directly.
b. Using our Cloud9Agent. This can securely pull data inside your network. See agent configuration for more details. - Visualize and Automate your Reporting instantly.
UI
Connecting
1. Log in to Knowi and select Queries from the left sidebar.
2. Click on the New Datasource + button and select Oracle from the list of datasources.
3. After navigating to the New Datasource page, either use the pre-configured settings into Cloud9 Chart's own demo Oracle database or follow the prompts and configure the following details to set up connectivity to your own Oracle database:
a. Datasource Name: Enter a name for your datasource
b. Host Name: Enter the host name to connect to
c. Port: Enter the database port
d. SID or Service Name: Enter the connection string to connect to the database instance
e. Schema Name: Enter the name of the schema
f. User ID: Enter the User ID to connect
g. Password: Enter the password to connect to the database
h. Database Properties: Additional database connection properties.
4. Establish Network connectivity and click on the Test Connection button.
Note: The connection validity of the network can be tested only if it has been established via Direct Connectivity or an SSH tunnel. For more information on connectivity and datasource, please refer to the documentation on- Connectivity & Datasources.
5. Click on Save and start Querying.
Query
Set up Query using a visual builder or query editor.
Visual Builder
After connecting to the Oracle datasource, Knowi will pull out a list of tables along with field samples.
Step 1: Generate queries through our visual builder in a no-code environment by either dragging and dropping fields or making your selections through the drop-down.
Step 2: Define data execution strategy by using any of the following two options:
- Direct Execution: Directly execute the Query on the original Oracle datasource, without any storage in between. In this case, when a widget is displayed, it will fetch the data in real-time from the underlying Datasource.
- Non-Direct Execution: For non-direct queries, results will be stored in Knowi's Elastic Store. Benefits include- long-running queries, reduced load on your database, and more. Non-direct execution can be put into action if you choose to run the Query once or at scheduled intervals.
For more information, please refer to this documentation- Defining Data Execution Strategy.
Step 3: Click on Preview to review the results and fine-tune the desired output, if required.
The result of your Query is called Dataset.
After reviewing the results, name your dataset and then hit the Create & Run button.
Query Editor
A versatile text editor designed for editing code that comes with a number of language modes including Oracle Query and add-ons like Cloud9QL, and AI Assistant which empowers you with powerful transformations and analysis capabilities like prediction modeling and cohort analysis if you need it.
AI Assistant
AI assistant query generator automatically generates queries from plain English statements for searching the connected databases and retrieving information. The goal is to simplify and speed up the search process by automatically generating relevant and specific queries, reducing the need for manual input, and improving the probability of finding relevant information.
Step 1: Select Generate Query from AI Assistant dropdown and enter the details of the query you'd like to generate in plain English. Details can include table or collection names, fields, filters, etc.
Example: “Show clicks in dataset_76170_1693950762063462783”
Note: The AI Assistant uses OpenAI to generate a query and only the question is sent to OpenAI APIs and not the data.
Step 2: Define data execution strategy by using any of the following two options:
- Direct Execution: Directly execute the Query on the original Oracle datasource, without any storage in between. In this case, when a widget is displayed, it will fetch the data in real-time from the underlying Datasource.
- Non-Direct Execution: For non-direct queries, results will be stored in Knowi's Elastic Store. Benefits include- long-running queries, reduced load on your database, and more. Non-direct execution can be put into action if you choose to run the Query once or at scheduled intervals.
For more information, please refer to this documentation- Defining Data Execution Strategy
Step 3: Click on the Preview button to analyze the results of your Query and fine-tune the desired output, if required.
Note 1: The OpenAI must be enabled by the admin before using the AI Query Generator.
Note 2: The user can copy the API key from the personal OpenAI account and use the same or use the default key provided by Knowi.
{Account Settings → Customer Settings → OpenAI Integration}
Furthermore, AI Assistant offers you additional features that can be performed on top of the generated query as listed below:
- Explain Query
- Find Issues
- Syntax Help
Explain Query
Provides explanations for your existing query. For example, an explanation requested for the query generated below AI Assistant has returned the description-
“This Oracle query is counting the total number of records in the dataset_76170_1693950762063462783 table and assigning the result to the alias "Total Clicks". The result of the query will be a single number representing the total number of records in the table.”
Find Issues
Helps in debugging and troubleshooting the query. For example, finding issues in the query generated below returns this error- “This query is missing a WHERE clause, so it will return the total number of rows in the table, rather than the total number of clicks.”
Syntax Help
Ask questions about query syntax for this datasource. For example, suggesting the syntax for the requested query returned the response- “UPDATE table_name SET column1 = value1, column2 = value2, … WHERE condition;”.
Cloud9Agent Configuration
As an alternative to the UI-based connectivity above, you can use a Cloud9Agent inside your network to pull from Oracle securely.
Highlights:
- Pull data using SQL.
- Execute queries on a schedule, or, one time.
The agent contains a datasource_example_oracle.json and query_example_oracle.json under the examples folder of the agent installation to get you started.
- Edit those to point to your database and modify the queries to pull your data.
- Move it into the config directory (datasource_XXX.json files first if the Agent is running).
Datasource Configuration:
| Parameter | Comments |
|---|---|
| name | Unique Datasource Name. |
| datasource | Set value to oracle |
| url | URL to connect to, where applicable for the datasource. Example for Oracle: localhost:1521:cloud9demo |
| userId | User id to connect, where applicable. |
| Password | Password, where applicable |
| userId | User id to connect, where applicable. |
Query Configuration:
| Query Config Params | Comments |
|---|---|
| entityName | Dataset Name Identifier |
| identifier | A unique identifier for the dataset. Either identifier or entityName must be specified. |
| dsName | Name of the datasource name configured in the datasource_XXX.json file to execute the query against. Required. |
| queryStr | Oracle SQL query to execute. Required. |
| frequencyType | One of minutes, hours, days, weeks, months. If this is not specified, this is treated as a one-time query, executed upon Cloud9Agent startup (or when the query is first saved) |
| frequency | Indicates the frequency if frequencyType is defined. For example, if this value is 10 and the frequencyType is minutes, the query will be executed every 10 minutes |
| startTime | (Optional) Can be used to specify when the query should be run for the first time. If set, th frequency will be determined from that time onwards. For example, is a weekly run is scheduled to start at 07/01/2014 13:30, the first run will run on 07/01 at 13:30, with the next run at the same time on 07/08/2014. The time is based on the local time of the machine running the Agent. Supported Date Formats: MM/dd/yyyy HH:mm, MM/dd/yy HH:mm, MM/dd/yyyy, MM/dd/yy, HH:mm:ss,HH:mm,mm |
| c9QLFilter | Optional post processing of the results using Cloud9QL. Typically uncommon against SQL based datastores. |
| overrideVals | This enables data storage strategies to be specified. If this is not defined, the results of the query is added to the existing dataset. To replace all data for this dataset within Knowi, specify {"replaceAll":true}. To upsert data specify "replaceValuesForKey":["fieldA","fieldB"]. This will replace all existing records in Knowi with the same fieldA and fieldB with the current data and insert records where they are not present. |
Datasource Example:
[
{
"name":"demoOracle",
"url":"localhost:1521:cloud9demo",
"datasource":"oracle",
"userId":"cloud9demo",
"password":"cloud92014"
}
]
Query Examples:
[
{
"entityName":"Errors",
"dsName":"demoOracle",
"queryStr":"select error_condition as 'Error', count 'Count' from errors",
"frequencyType":"minute",
"frequency":10,
"overrideVals":{
"replaceAll":true
}
},
{
"entityName":"Queues",
"dsName":"demoOracle",
"queryStr":"select Name, size as 'Queue Size', Type from queue",
"overrideVals":{
"replaceValuesForKey":["Type"]
},
"startTime":"07:20",
"frequencyType":"daily",
"frequency":1
}
]
The first query is run every 10 minutes at the top of the hour and replaces all data for that dataset in Knowi. The second is run once a day at 07:20 AM and updates existing data with the same Type field, or inserts new records otherwise.