DBMS is a perfect database design that plays an important role for better performance and scalability of an application. Many Applications on the social platform like Facebook has improved its database structure that is why you can find high-resolution videos playing fine. With extra functionalities, the database structure of many applications has shown improvement in the past few years.
Designing Database in DBMS
You have known that the performance of any application is not completely independent of the database. There are so many essential factors like User Interface, API, etc. which also have an equal contribution to the high working performance of many application features. If there is any flaw in designing the database, then there can be a trouble in the performance while integrating the new features. The architecture of database design is being carried out in most companies by Database Architect.
The designing of the database in DBMS is highly responsible for the fast, smooth and high performance of the analytic application. You must focus on a few tips that can help in designing the best database:
- Work on Non-Relational Database
One thing should always be kept in mind while working on database design, always opt for NoSql Database as this will help in building Analytical Application and can be able to work on the unstructured form of data. In such a database, work is mostly related to schema dynamically. So, mainly for data science, choosing non-relational database can be the best idea to be worked upon. Usually, the Analytic applications hold the user records in millions and in order to manage the growth steadily the non-relational database can handle the massive number and also help in maintaining the horizontal scalability. It is faster and can be best suited to handle big data work of Analytical Applications.
- Working on flexible logical designs of database
In a flexible logical design of an analytical application, more generic attributes can be added easily. Most people failed to achieve it in database design. The basic point is that the declaration of various data types must not be fixed and restrict for ex. The datatype float is declared as generic but the datatype it is declared as special. Casting INT datatype into FLOAT datatype can be easy, but the reverse might be difficult.
- Untwisted coupled relation schema
The data should be held loosely which can easily be molded. This is mainly related to the relational typed database. Mostly, while designing the database in SQL, the constraints are being used. For ensuring the accuracy of data in the SQL designed the relational database, the integrity constraints play the major role. The other constraint like primary key plays a role of uniquely identifying column building rows of data. Like in Student database, the roll no is a primary key constraint because roll no is the uniquely identified id of a student and no two students have the same roll no.
While creating the table in the relational database, the unique logical key called primary key is being assigned. For more information on database design, sign up on RemoteDBAand get in touch with an expert for the solution of all your queries.
- Using NoSQL database design to perform the join operation
When you think about joining two tables, this can easily be performed in the relational design database, but this cannot be performed easily in the NoSQL database design of an analytical application. This situation can easily be taken care of during the designing phase of database building. The data flow should explicitly be taken care when such complex situations. During the database designing with no SQL, few things should be taken care.
- The interaction between data scientist and data: The data scientist and engineers working on big data has the very important role to be focused on the design of data. While working on the analytics of an application, at each stage of designing. You need to collect some details like:
- Fetching the data
- Cleaning the data
- Working on designing features of an application
- Streamlining the model for machine learning language
- Validating the model
- Checking the accuracy in real time
- Working on deployment segment
- Working on the Critical areas of Database design
It's important to locate the areas where performance gets affected because of database design. Going every stage by stage, you need first to fetch the information. You might get it from another external source like the third party or from inside like from own portal. After collecting the information, you need to keep a check of a few things like
- Questioning the elements of database design: You need to think from every prospect of performance and design and consider the situation where performance might be going down. If the answer for that is yes, then start looking for options like casing through short data and memory of application. Secondly, you can move over to NoSQL database. While working on the metadata database, the DBMS design rules should be in mind.
- Updating the database: Schedule updating the database if some design issue remains. Don’t let it affect the performance of the analytical application.
Setting the right path for designing the database can be a trick and smart way for a successful run of an application. Many data scientist walks their way to heights through such guidance on database design. It is the true database not entirely responsible for the successful running application, but it is a very interim part of the design phase of Application, database, and other components. The successful running of massive records can only be managed easily when database design will be carried out accurately.
Author Bio: William Darcy is the author of the article and has years of experience in Database architecture. He has written several blogs and articles on database design. In this article, he talks about the database design that needs to be taken care while structuring an analytical application. For more info, go to RemoteDBA.com and subscribe to latest updates.