๐ŸŒŸ Industry Side Chat: MongoDB Flexible Database Schema, Time Series, Atlas Vector Search RAG๐ŸŒŸ

danc

Danny Chan

Posted on August 7, 2024

๐ŸŒŸ Industry Side Chat: MongoDB Flexible Database Schema, Time Series, Atlas Vector Search RAG๐ŸŒŸ

Use Case 1: Healthy Lifestyle Platform ๐Ÿ’ช


Cure.fit:

  • Handle spikes in traffic ๐Ÿ“ˆ
  • Delivering unique content based on user's regions ๐ŸŒ
  • Personalized experience on pages (merchandising) ๐Ÿ›’


Challenge:

  • Capture different data across user segments ๐Ÿ“Š
  • Personalized content ๐ŸŽฏ
  • Three-layer architecture:
    • Backend: MongoDB Atlas ๐Ÿ—ƒ๏ธ
    • Middle: API layer ๐ŸŒ
    • Front: Microservices ๐Ÿงฑ


Solution:

  • MongoDB Flexible Database Schema ๐Ÿ”
  • Capture a wide range of data (web forms, tracking customer usage) ๐Ÿ“ˆ
  • Organize diverse data ๐Ÿ—‚๏ธ


MongoDB Features:



Use Case 2: Turn Asset Data into Value ๐Ÿ’ฐ



Digitread Connect: Industrial IoT-as-a-Service ๐ŸŒ


Challenge 1:

  • Data from sensors across industry verticals, machinery, industrial assets ๐Ÿค–
  • Analysis process ๐Ÿ”
  • Client end-users: engineers, service technicians, surveyors, farmers ๐Ÿ‘จโ€๐Ÿ”ง


Challenge 2:

  • Collecting data to useful deliverable ๐Ÿ“Š
  • Extract data from microcontrollers or programmable logic controllers ๐Ÿ”Œ
  • Analyze data, necessary data to cloud ๐Ÿ’ป
  • IoT platform, edge & application side ๐ŸŒ


Solution: MongoDB Time Series Data:

  • Industrial mechanized, robotic environments ๐Ÿค–
  • Track equipment activity, performance ๐Ÿ“ˆ
  • Analyzed and filtered, only keep useful data, upload to relevant application ๐Ÿ’พ



Use Case 3: Ideal Customer Profiles (ICP) ๐ŸŽฏ



Scalestack:

  • Connect go-to-market (GTM) data to customers' Ideal Customer Profiles (ICP) ๐Ÿค


Challenge:

  • Sales engineers waste time reconciling data ๐Ÿ’ป


Solution:

  • MongoDB Atlas Vector Search ๐Ÿ”
  • Retrieval-Augmented Generation (RAG) ๐Ÿค–
  • Searches over large datasets using vector similarity ๐Ÿง 
  • Aggregate, manage, and automate disparate GTM (go to market) data sets ๐Ÿ“Š
  • Aggregate and understand a variety of data from different sources ๐Ÿ—ƒ๏ธ
  • Help sales to create scenario-specific strategies ๐Ÿง 


Details:

  • Connect LinkedIn, Crunchbase, Zoominfo, job postings ๐ŸŒ
  • Connect customer info, company facts, news, and job openings ๐Ÿ“‹
  • Connect lead generation forms ๐Ÿ“
  • Create personalized suggestion, prioritized actions for user to boost sales ๐Ÿ’ฐ



Reference:

capture and analyze data on edge device
https://www.mongodb.com/solutions/customer-case-studies/digitread-connect

Atlas Vector Search, Amazon Bedrock
https://www.mongodb.com/solutions/customer-case-studies/scalestack


Editor

Image description

Danny Chan, specialty of FSI and Serverless

Image description

Kenny Chan, specialty of FSI and Machine Learning

๐Ÿ’– ๐Ÿ’ช ๐Ÿ™… ๐Ÿšฉ
danc
Danny Chan

Posted on August 7, 2024

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