2. DESIGN
Design is the phase in the software development lifecycle where the blueprint of the software is laid out. It involves making key decisions about the software's structure, user interface, data management, technology stack, and security considerations. Let’s explore the essential components.
Note: The following sections are interchangeable and can be approached either bottom-up or top-down based on your preferences.
"Data dominates. If you've chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming."
- Rob Pike
Data management is the practice of organizing and maintaining data processes efficiently to ensure that information is accurate, accessible, and secure. Database design is the process of organizing how your data will be stored, accessed, and managed. This involves creating Entity-Relationship (ER) diagrams and schemas to map out the structure of the database.
Here’s a basic breakdown to get you started.
why data management matters
- Accuracy. Proper data management ensures that information is correct and reliable, which is crucial for making informed decisions.
- Accessibility. Well-managed data is easy to find and use, helping you quickly retrieve the information you need.
- Security. Effective data management protects sensitive information from unauthorized access and breaches.
DATA STORAGE
For modern startups, cloud solutions offer significant benefits over on-premise infrastructure. They provide scalable resources that can be adjusted as needed, avoiding high initial costs and long-term commitments of on-premise hardware. Cloud services also handle maintenance, security, and updates, allowing startups to focus on their core business. This combination of flexibility, cost-efficiency, and reduced operational complexity makes the cloud an ideal choice for startups looking to grow and adapt quickly.
TYPES OF DATA
- System of Record. Core data that you rely on for day-to-day operations, like customer contact information.
- Sensitive Data. Information that needs extra protection, such as financial records or personal identification.
- Transactional Data. Data related to transactions, like sales receipts or purchase orders.
- Business Intelligence Data. Data used for making business decisions, such as sales trends or market analysis.
- Log Data. Records of system activities, like traffic or user behavior, useful for monitoring and troubleshooting.
TYPES OF DATA STORAGE
- Files/Folders. Think of this as saving documents on your computer. It’s simple and straightforward for organizing small amounts of data.
- Relational Databases (SQL). Imagine a well-organized spreadsheet with multiple interconnected sheets. SQL databases are used for structured data with clear relationships, like customer information linked to orders.
- NoSQL Databases. These are like flexible containers that can hold different types of data, similar to having various boxes for different items. They’re useful when data doesn’t fit neatly into tables.
- Data Lakes. Picture a large storage facility where you keep all kinds of raw data. Data lakes store vast amounts of unstructured data, such as videos or social media posts.
- Data Warehouses. Think of this as a specialized archive for data that’s been cleaned and organized for analysis. It’s used to gather and analyze large amounts of structured data.
ENTITY-RELATIONSHIP (ER) DIAGRAM
Once you have identified your data requirements and relationships, start documenting them in a Entity-Relationship (ER) Diagrams. These are like blueprints for your data. They show how different pieces of data are related to each other, helping you understand and manage complex data structures.
TOOLS: LUCIDCHART, DRAW.IO, MICROSOFT VISIO OR ANY OTHER FREE TOOL!
In Summary:
- Identify the data requirements and relationships. Define the key data entities and how they relate to one another within the system.
- Create ER diagrams to represent data structures. Visualize the data entities and their relationships using Entity-Relationship (ER) diagrams to ensure clarity.
- Develop database schemas based on the ER diagrams. Translate the ER diagrams into detailed database schemas that define tables, columns, and data types.
- Review and optimize the database design. Analyze the database structure for performance improvements and potential issues, optimizing where necessary.
- Document the database design and obtain approval. Create thorough documentation of the database structure and seek final approval from stakeholders.