Unlock Data Insights with OpenAI Analytics Connector

Unlock Data Insights with OpenAI Analytics Connector

Table of Contents

1. Introduction
2. Open AI Analytics Connector for Click Cloud Analytics
3. Setting up the Open AI Analytics Connector
   1. Creating an Open AI Platform Account
   2. Obtaining the Open AI API Key
4. Configuring the Analytics Connector
   1. GPT3 Rows Configuration
   2. GPT3 JSON Tables Configuration
   3. Completions API GPT35 Configuration
5. Testing the Connection
6. Creating the Connection in Data Load Editor
7. Implementing the Connector in Chart Expressions
   1. Defining the Prompt and Parameters
   2. Handling Selections in the Expression
8. Viewing Real-Time Generated Insights
9. Expanding the Possibilities with the Open AI Analytics Connector
10. Conclusion

Article: Exploring the Open AI Analytics Connector for Click Cloud Analytics

In today's digital age, data analytics plays a crucial role in decision-making and gaining valuable insights. To enhance the analytics capabilities, Click Cloud Analytics offers the Open AI Analytics Connector, which allows users to leverage the power of Generative AI for data analysis. This connector enables users to generate custom insights in real-time, producing dynamic results Based on specific parameters. In this article, we will Delve into the details of the Open AI Analytics Connector for Click Cloud Analytics and explore its various functionalities.

1. Introduction

In the world of data analytics, the need for innovative tools and technologies has Never been greater. Click Cloud Analytics, a leading analytics platform, understands this demand and offers the Open AI Analytics Connector to its users. This connector integrates with Open AI's powerful generative AI models and enables users to generate insights dynamically based on predefined parameters.

2. Open AI Analytics Connector for Click Cloud Analytics

The Open AI Analytics Connector provides a seamless integration between Click Cloud Analytics and Open AI's generative AI models. By leveraging the capabilities of Open AI's API, users can utilize the power of natural language processing to generate Relevant and contextual insights.

3. Setting up the Open AI Analytics Connector

Before diving into the functionalities of the Open AI Analytics Connector, it is essential to set up the necessary components. This involves creating an Open AI Platform account and obtaining the API key required for integration.

3.1 Creating an Open AI Platform Account

To access Open AI's generative AI models and APIs, users need to Create an Open AI Platform account. The account creation process involves signing up at platform.OpenAI.com and following the registration steps. It is important to note that the Open AI Platform account is separate from the GPT account offered by Open AI.

3.2 Obtaining the Open AI API Key

After creating the Open AI Platform account, users need to obtain the API key required for integrating the Open AI Analytics Connector with Click Cloud Analytics. The API key comes with a certain number of tokens or credits attached, which affects usage and billing. Users can find the API key within the Open AI connector settings in Click Cloud Analytics.

4. Configuring the Analytics Connector

The Open AI Analytics Connector offers three different configurations to cater to various requirements: GPT3 Rows, GPT3 JSON Tables, and Completions API GPT35. Each configuration has its own unique features and use cases.

4.1 GPT3 Rows Configuration

The GPT3 Rows configuration enables users to send each row of data as a question to Open AI's Completions API. This configuration improves performance by sending small batches of data and storing the response as text in a table. It is suitable for both chart expressions and data load scripts.

4.2 GPT3 JSON Tables Configuration

In the GPT3 JSON Tables configuration, each row of data sends a request to Open AI, expecting a JSON list of data as a response. The connector converts the JSON table into a data table within the Click data model. This configuration is useful when users need to work with structured JSON data.

4.3 Completions API GPT35 Configuration

The Completions API GPT35 configuration is similar to the GPT3 Rows configuration but sends each row as a request to the Open AI Completions API. The requests contain a different user message role in each data row. This configuration allows for more customized responses based on the user's input.

5. Testing the Connection

Before proceeding with the implementation of the Open AI Analytics Connector, it is crucial to test the connection and ensure that all mandatory fields are filled. The test connection feature in Click Cloud Analytics validates the connection settings but does not establish a connection to Open AI.

6. Creating the Connection in Data Load Editor

To begin using the Open AI Analytics Connector in Click Cloud Analytics, users must create a new connection in the Data Load Editor. This involves selecting the Open AI connector and providing the API key obtained from the Open AI Platform account. The connector configuration and connection name play a vital role in generating the desired insights.

7. Implementing the Connector in Chart Expressions

Once the Open AI Analytics Connector is set up, users can integrate it within chart expressions to generate real-time insights. By defining Prompts and parameters, users can pass relevant data from Click to the Open AI API, which will produce dynamic responses based on the provided Context.

7.1 Defining the Prompt and Parameters

The prompt acts as the input to the Open AI API, generating responses based on the specified parameters. Users can customize the prompt to query specific topics and Gather insights accordingly. The selected fields and values from the Click data model are passed as parameters to provide context for generating the insights.

7.2 Handling Selections in the Expression

To ensure that the prompt and parameters only generate insights when valid selections are made, it is essential to include logic in the chart expression. If no selections are made, a default message can be displayed, prompting the user to select the required values for Meaningful insights.

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