Pre Sales
  • BDB Pre Sales
  • Manufacturing Use Case
    • Introduction
    • How is BDB different than Azure, AWS, or GCP?
    • Project Definition and Requirements
      • Functional Requirements
      • Technical Requirements
      • Non-Functional Requirements
      • Project Deliverables
    • Functional Requirements from Manufacturing
    • Technical Requirements
      • Data Ingestion
      • Data Processing (Batch Data)
      • Data Processing (Real-Time Data)
      • Data Preparation
      • Data Store(Data Lake)
      • Data Store (Enterprise Datawarehouse)
      • Query Engine
      • Data Visualization
      • BDB Search
      • Advanced Analytics and Data Science
    • Data Services
    • Security Requirements
    • Networking Requirements
    • Operational Requirement
    • Non-Functional Requirements
      • Scalability
      • Availability
    • Data Platform Benchmarking
    • Hardware Sizing Requirements
  • Data Platform Evaluation Criteria
    • Data Preparation
    • Data Platform Evaluation Highlights
    • Data Pipeline
    • Ingestion Connector
      • Seamless Handling of Data ops and ML ops
    • Ingestion Process
      • Building a path from ingestion to analytics
    • Data Preparation
      • Processing Modern Data Pipeline
  • BDB POC Approach
  • BDB Vertical Analytics
  • Technical FAQs
    • Data Platform
    • Administration
    • Data Security & Privacy
    • Analytics
    • Data Preparation
    • Data Pipeline
    • Dashboard Designer
    • Business Story
    • Performance & Scalability
    • Global and Embeddable
    • Deployability
    • User Experience
    • Support & Licensing
    • AI
    • Change Management
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  1. Manufacturing Use Case

Introduction

When enterprises fail to find ways to integrate, manage, and use their data, they are leaving a lot of value on the table—and the data value gap continues to widen as the number of data increases. They also need to collect a lot of Business KPIs and Competitive data to benchmark against internal data and project the same to their ecosystem (R&D, Production, Quality, Sales, Marketing, HR, Finance, Partners, Govt, 3rd Parties)

Therefore, most Enterprises look for Integrated Data Analytics Platforms to create successful Data Platforms for themselves! Most people call it Data Modernization under Digitization Objectives.

BDB is one of the most feature rich, Integrated, Unified, End-to-End Data Analytics Platforms built in the history of the Business Intelligence space in the world. Its main aim is to serve large Applications (with huge no of users) through Integrations thereby giving seamless analytics to enterprises working on their Data Platforms (for their Data Monetization purposes). Enterprises over the last 10-15 years have invested in many BI tools and custom code which is giving them value. For data monetization, one needs to relook at the strategy.

Use what’s been built but use an Integrated Platform to deliver the next set of Analytics!

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Last updated 2 years ago