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 Rise of APS-C Cameras: A Professional Renaissance in Photography
- Market Brief: Disruption in Spanish Orange Supply Chain and Strategic Response by UK Retailers
- Global AI-Powered Movie Scenario Market Analysis 2023-2030: Growth, Trends, and Forecast
- Market Research Report: US Government Cybersecurity Market in 2024
- Market Research Report: Global Advertising Revenue Projections and Trends in the Entertainment & Media Industry
- Social Media: The Rise of Formulaic Content
- Netflix’s Creative Decline: The Rise of Formulaic Content
- The Transformation of Media: Navigating the Waning Allure of Social Platforms
- Apple’s Potential Entry into the Camera Market: A Disruptive Force Set to Redefine the Industry
- Camera Sales Reach Highest Levels in Three Years, Reports CIPA
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.