Data Analysts

No matter how many resources you have, there's never enough people to get information fast enough. Imagine if executives could instantly pull data or ask questions directly, and the system would give clear, accurate answers.

This would save time and let analysts focus on more complex work. Executives could ask simple questions like, "What deals moved last week?" and get quick, useful answers without waiting for a full report.

Often, analysts have already built dashboards, but executives don’t use them, expecting someone to present the info instead. Conduit is a system that provides quick answers and includes analysts to verify the data's quality could solve this problem and make decision-making faster.

Implementation of data pipelines and calculations using AI

• Describe the Data Processing Steps: Outline the specific data processing steps you need.
• AI-Generated Python Program: AI will generate a Python program tailored to your requirements, which will run on the Conduit server.
• ETL Data Pipelines: This program will create ETL (Extract, Transform, Load) data pipelines.
• Data Processing: It will process your data in the Data Lake.

Ad hoc reports

Even if you use a reporting solution like Google Looker or Microsoft BI, you can share the data from these reports with an AI chatbot, which will generate ad-hoc reports for business users.

Conduit Automates Routine ETL Operations

• Loading Source Data: Importing data from business applications.
• Data Consolidation: Combining data from multiple sources.
• Data Merging and Cleaning: Ensuring data accuracy and consistency.
• Postprocessing Reports: Finalizing and formatting reports.
• Report Distribution: Distributing reports to various clients and teams.