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Introduction

Data Design, by definition, has a design. And when we talk about innovation, we refer to modeling the different data sets and deciding what we will do with them.

Thus, a Data Design  without design is a lawless and confused set of information. So, it would not be shocking that this reality is wanted to be give an order. Furthermore, this has become even more important, if possible, in times of Big Data. Today data management has become a vital issue. This will serve so that the use of a base achieves better results; not in hopeless, what is quoted is that knowledge is valuable.

It is also energetic to remember that a database requires a previous process. And, if you want it to be successful, it has to be a systematic effort. But nevertheless, it is worth considering because it is much more difficult for the user to be functional and efficient if these premises are not met.

What Is Data Design?

Database design is a fundamental process for modeling our data sets and defining the operations we want to perform on them. Data is the most critical asset of our organization. Therefore, a well-designed database directly influences the efficiency we will obtain when storing, retrieving, and analyzing our data.

Advantages Of Data Design

Advantages Of Data Design

A Data Design Carried Out Properly Offers Us Total Rewards :

  • It allows us to save space through improved database design without duplicate data.
  • It helps us preserve the accuracy and integrity of the data so that information is not lost.
  • Significantly speeds up data access and processing.

Why Is Data Design Important?

A good design of your data is essential because it brings several advantages. The most important are the following:

  • It is streamlining data processing. It is clear that the more functional the design, the easier it will be to speed up data processing.
  • Space saving. Saving space is easier since an optimize data layout eliminates duplication, which always uses space.
  • Better data accuracy and integrity. When the data design is optimal, data loss is avoid, and, above all, precision is gain. This is already a reason to give importance to this issue.

These aspects are beneficial because they will serve to make a difference. Consequently, the ideal design will provide added value that you should not disdain.

Choosing A Data Management System

This phase will choose the specific database management system (DBMS) that best suits our project, such as Oracle, MySQL, Microsoft SQL Server, and PostgreSQL.

Logical Design

In this phase, the previous conceptual model is translate into a logical schema, which describes the database structure. This is the phase in which the tables themselves are designed, with rows, columns, and relationships. The logical model depends on the DBMS to be use.

Physical Design

In this phase, the storage structures of the database are physically define when the code (for example, SQL) is write to specify the design in the file engine that we have chosen.

Application

Finally, the database plan is create and compile, and the files and the applications that implement the transactions made.

File Data Design Values

For our file to be efficient and respond to the requirements, it is necessary to follow principles guiding the database design process. Below we will describe the main ones:

  • Competent organization of tables, the fundamental units of the file. Each table comprises rows, also called records, and posts, known as fields. Single one type of information (logical part) should be store in the areas. Data that controls other data can obtain should also not be store.
  • The layout of primary keys and foreign keys. Important keys (or PK) are columns that uniquely identify each row and allow relationships to be built between tables. Primary keys can never have a null or identical value. On the other hand, foreign keys must correspond to the primary keys of the tables with which they are relate.
  • Design relationships between tables, which container be one-to-one, one-to-many, or many-to-many. Relations allow information to be organize between different tables, optimizing the available space.
  • Database normalization, which allows compliance with industry standards.

What Is A Good Data Design?

The excellent design of a database fulfills a series of points. Thus, the most exciting aspects being note are the following:

The first thing is that the distribution is in thematic tables. The objective, in this case, is to eliminate the redundancy or repetition of data, which is one of the most problematic aspects.

Of course, the information must be of good quality. And this implies that the data capture is correct so that they can be transfer to the table. You have to check that the data conforms to what was previously design.

Third, quality data feedback is essential. What is impose, in these cases, is that the appropriate changes be made on the fly. And it is no secret that, for this, having data adapt to what you need is essential.

On the other hand, a good database promptly meets the demands for reports and information. And, of course, it has to work with full compatibility with the database operators.

Conclusion

Hence, data Design is essential for you to achieve good results in your analytics. And, as a general principle, you have to know how to elaborate the procedure to avoid future problems; time and money are save. Therefore, it is convenient for you to understand what this discipline consists of and what it can contribute to you.

Also Read: What is Ethereum Homies?

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