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Build Your Data Copilot on AWS S3

Author
Dong Li
VP of Global Growth Marketing
Jan. 10, 2024

 
In this transformative era where ChatGPT and other GenAI technologies are redefining the business world, adopting a Data Copilot has transitioned from being a futuristic concept to an essential business tool. Mirroring the success seen in platforms like GitHub and Windows, the Data Copilot is now making a significant impact in the realm of Data & Analytics for enterprises, especially those utilizing AWS S3. This leap forward in technology brings with it unparalleled efficiency and value enhancement in data handling.
What is a data copilot?
At its core, a data copilot leverages Large Language Models (LLMs) to revolutionize tasks in data & analytics. For enterprise data teams, this translates to:
 
  1. Democratizing Data Usage: The data copilot eradicates conventional barriers to data access, enabling every enterprise member to leverage data effortlessly, thereby nurturing a robust, data-driven organizational culture.
  2. Enhancing Data Management: Going beyond mere data access facilitation, the data copilot fine-tunes the usage of vital data assets, amplifying their business worth.
Capabilities of A Data Copilot
The data copilot is designed to handle the most labor-intensive tasks, freeing up teams to concentrate on high-impact areas. Key capabilities include: 
  1. Conversational Data Analysis: This feature allows for swift, natural language-based data queries, streamlining the analysis process without the use of complex BI systems.

  1. Insight Discovery: Employing advanced analysis techniques like root-cause analysis, it uncovers deeper insights and narratives within the data, explaining the 'why' behind trends.

  1. Dashboard Generation: The copilot crafts user-friendly dashboards, making the sharing and interpretation of data insights more efficient.

  1. Business KPI Evaluation: It plays a vital role in assessing key performance indicators, aiding in informed strategic decision-making given current and future status of core business goals.

Building Your Data Copilot with AWS S3
Kyligence Zen empowers you to effortlessly construct a data copilot using AWS S3, eliminating the need for expert-level knowledge in data warehousing, business intelligence, or AI. The process involves three straightforward steps:
  1. Get Your Data Ready in AWS S3: Integrating systems and storing data in popular formats like CSV in S3 is simple. You only need to grant access to Kyligence Zen and connect it according to this guideline: https://zen-docs.kyligence.io/en/connect-data. For newcomers, Kyligence Zen offers sample data to explore without loading your own data.

  1. Defining Business Metrics: Tailor metrics in Kyligence Zen to align with your business logic. For example, setting up GMV metrics is a user-friendly process.

  1. Natural Language Interaction: The Kyligence Copilot interface allows business users to extract insights using natural language. Users can ask questions like "How many sales qualified leads are contributing to pipeline in Q1?"

Get Started with Data Copilot Today

Register now for a 7-day free trial and start transforming your data analytics capabilities with Kyligence Zen. This guide takes you through a seamless quickstart process, opening the doors to the comprehensive potential of cloud-based data analytics. Begin your path to smarter, more efficient data management now.