Database design plan
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For a growing business, good database design practices are essential. It enables data retrieval, analysis, and manipulation very easy. A good database design is important for the high performance of applications. Furthermore, a well-designed database is crucial for scalable applications. To explain this, with our expert analyst, we will make sure that the client’s database does not compromise their application’s performance and management. Scalability will help solve performance-related problems and code maintenance too.
Before creating a good database, we should ask our client some crucial questions to understand how we will implement the design. Some of the questions include; what is the purpose of the database? What data-types are required? Our many tables and columns? How are they related? What are the primary keys? After coming up with answers to these questions, it will be easier to easily create and apply normalization rules.
Our team of experts will construct a prototype of each database to consider the data provided by our clients in their database and structure them to make sure they are broken down into their smallest useful parts. Our analysts will create a database schema for our client, which will be essential in organizing data in the database. To enable a highly scalable database, we will need to first deal with unstructured data. For instance, in the product details table, our team will need to develop a column that will incorporate methods such as ‘quick and dirty’ where details such as product attributes are all fused in a single database field. This way, our experts will save much time, and much data will be available for ‘C’ level manager for quick analysis.
Our analysts will define attributes for our products. This way, it will be easy to deal with the product with so many attributes, such as color and sizes. What we asked ourselves is how these data will affect pricing. By answering this, we came up with ways to incorporate new attributes to our products. This attribute will be affected by where the items selected by customers or “C” level officers come from the database.
For database reports, our ‘C’ level officers will be using the Logi report tool, which will be implemented by our analysts for front-end purposes, and as a dashboard manager, the Logi reporting tool will enable our ‘C’ level officers create sophisticated reports with ease. The advantages of using the Logi reporting tool are: they are flexible and customizable, scaling is easy, and the implementation part is quicker. Logi reporting will also offer executives the ability to review results with ease.
Our analysts will use SQL to share, manage, create, and organize the data in the client’s database. The advantage of using SQL is performance speed. Using SQL queries produces results quicker for a larger amount of record in the database. They will also use Python for retrieval and management of the data, python database API comes in handy for this. The reason for this is because Python will be easy to implement and also maintain.
Our analyst dealt with data redundancies for the given database data. They were able to eliminate repeating and duplicated data and tables. For instance, we found that when a customer purchased a product from the client’s company, their names would be duplicated in the database because the client had not enforced referential integrity. Our analysts had to enforce techniques that eliminate undesirable characteristics such as insertion, update, and deletion anomalies to avoid this. This technique is known as database normalization.