Designing a database schema requires careful consideration of the entities, relationships, attributes, and their interactions within the system. For a market research store, where various types of data related to market research studies are stored and managed, the following is a basic example of a database schema:
- The $1 Trillion Counterfeit Goods Market: A Deep Dive into its Scope and Impact
- High Energy Military Laser Market Forecast
- U.S. Federal Cybersecurity Market Forecast
- Adapting to Survive: Analyzing the Evolution of the Social Media Industry Amidst Technological, Regulatory, and User-Driven Shifts
- Social Media Monitoring in PR and Communication
- The Rise of Federation in Social Media
- Navigating the Regulatory Landscape: Deepfakes and Altered Media
- Embracing Universal Benefits: A Case for Fair and Inclusive Welfare Systems
- Beyond Fairytales: The Billion-Dollar Legacy of Disney’s Public Domain Adaptations
- Text-to-Image AI Generators and their Impact on Media Markets
Entities and Relationships:
- Client:
- Attributes: ClientID (Primary Key), Name, Contact Info, Company Name, Industry, Address
- Study:
- Attributes: StudyID (Primary Key), Title, Description, Start Date, End Date, ClientID (Foreign Key referencing Client), Budget
- Researcher:
- Attributes: ResearcherID (Primary Key), Name, Contact Info, Area of Expertise
- Market Segment:
- Attributes: SegmentID (Primary Key), Name, Description
- StudySegmentMapping:
- Attributes: StudySegmentID (Primary Key), StudyID (Foreign Key referencing Study), SegmentID (Foreign Key referencing Market Segment)
- Data:
- Attributes: DataID (Primary Key), StudyID (Foreign Key referencing Study), ResearcherID (Foreign Key referencing Researcher), Data_Type, Upload Date, File_Path
- Reports:
- Attributes: ReportID (Primary Key), StudyID (Foreign Key referencing Study), ResearcherID (Foreign Key referencing Researcher), Report_Type, Creation Date, File_Path
Entity Relationships:
- Each Client can have multiple Studies (One-to-Many relationship).
- Each Study can have multiple Researchers (Many-to-Many relationship through an intermediary table).
- Each Study can be associated with multiple Market Segments (Many-to-Many relationship through an intermediary table).
- Each Study can have multiple Data entries (One-to-Many relationship).
- Each Study can have multiple Reports (One-to-Many relationship).
Database Tables:
- Clients:
- ClientID (Primary Key)
- Name
- Contact Info
- Company Name
- Industry
- Address
- Studies:
- StudyID (Primary Key)
- Title
- Description
- Start Date
- End Date
- ClientID (Foreign Key)
- Researchers:
- ResearcherID (Primary Key)
- Name
- Contact Info
- Area of Expertise
- MarketSegments:
- SegmentID (Primary Key)
- Name
- Description
- StudySegmentMapping:
- StudySegmentID (Primary Key)
- StudyID (Foreign Key)
- SegmentID (Foreign Key)
- Data:
- DataID (Primary Key)
- StudyID (Foreign Key)
- ResearcherID (Foreign Key)
- Data_Type
- Upload Date
- File_Path
- Reports:
- ReportID (Primary Key)
- StudyID (Foreign Key)
- ResearcherID (Foreign Key)
- Report_Type
- Creation Date
- File_Path
This schema provides a basic structure for managing market research data, client information, study details, researcher profiles, market segments, and associated data and reports. Depending on the specific needs of your market research store, you might need to further refine and expand this schema.
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