Data Modelling

Data Modelling is the process of creating a data model for the data to be stored in the database and formulating data in an information system in a well structured format as it assists in analyzing data which further aids in burgeoning the business requirements data models can be used for various purposes from high-level conceptual models to physical data models. A data model is used to document, define, organize and showcases how the data is stored within the given system. Data modelling emphasizes on what data is needed and how it should be organized.

Data modelling requires data modelers who can work efficiently with the stakeholders of the information system.

 The process of data modelling involves designing and producing all types of data models. These data models are then converted through a data definition language which is used in generating the database. Then the database will be termed as a fully attributed data model.

Why use Data Model

• The data model is used in designing the database at the various data levels i.e. conceptual, logical and physical.
• Data model exhibits a vivid understanding of business specific needs
• It assists in you in locating the missing data
• Can be used by database developers to create a physical database
• It defines relational tables, stored procedures, primary and foreign key
• It amends the data quality and assists the project managers with quality management
• Data model reduces the chances of data omission

Stages of Data Modeling

• Conceptual – Conceptual model is also known as domain models make a common platform for all the stakeholders by defining basic concepts. This stage of the model tells us what needs to be there in the model structure in order to define the business concepts. This model is created by business architects and main focusses on business-oriented attributes. The conceptual model is developed so that data can be represented for users ease.
• Logical –  This stage of the model focuses on the implementation part. It majorly includes all kinds of data that need to be captured such as tables, columns. The underlying reason behind this model is to develop a roadmap of technical rules and restrictions and the model is developed by business analysts and data architects. It describes data needs for a single project and has the potential to integrate with other logical data models.
• Physical – This model also focuses on implementation part but through the database management system. Its actual purpose is of the implementation of the database as it breaks the data down into actual tables, clusters, indexes required for the data store. This model is created by DBA and developers.in physical model primary foreign keys, views, indexes are also defined.

Advantages of Data models

• It aids in documenting data mapping during the ETL process
• It improves business intelligence by making data modelers work closely with ground realities of the project
• Improves the overall communication within the organization
• Data modelling provides a structured system for unstructured forms of data

What is Dimensional Modeling

It is a design technique of data warehouse which makes use of conformed dimensions and facts and aids in fast performance query.

Keys related to Dimensional modelling:

• Business keys – It is the field that uniquely identifies an entity
• The primary and alternate keys-Primary key is a key which has unique records stored in it and the key which are left after the user’s selection are called alternate keys
• Compound keys – When a key represents more than one field, it is termed as a compound key
• Surrogate keys – It is a field which is autogenerated and has no business meaning
• Foreign Keys – It is a key which indicates another key in some of the other table

Is Data modelling and Data analysis the same?

The answer to the above question is no as they are very different from each other but are often misinterpreted by people.

Data analysis is like filtering through data to gather the most relevant insights in the form of visualizations, graphs, reports.

Data modelling, on the other hand, is about creating the conditions to make the data analysis possible as it tells you what type of data you need to bring in. Data modelling involves normalization as data modelling is incomplete without normalization as normalization is the process by which anomalies are avoided and redundancy is eliminated.in simpler terms, it removes the partial dependencies from the data. Normalizing a data model means structuring data so that each entity has only one theme or topic. There are three different levels of normalization starting at first normal form and then going to the last form and the most common form is the third one.

Best Database designing and modelling tools

• Lucidchart – It can assist you in creating quick database diagrams online with its collaborative design tool. Lucidchart came into existence in 2008 and with its versatile features have secured a strong marketplace. It is cloud-based but one thing which some people don’t prefer as it is can be accessed only through the website. Its unique features have bagged many prestigious awards.
• SQL Server database modeler – It is an open source data modelling tool suitable for small and medium businesses. It is one of the most used data modelling tools used for designing the database online by importing the existing database. It also has some remarkable features like friendly UI, the concept of creating multiple subject areas.
• Visual paradigm and tools – One of the most helpful database schema design tool because ERD is the baseline of the database. Its usage in multifarious industries ranges from commercial as well as personal and it has a standard to community version which is free.
• Power designer – A leading database modelling tool supporting robust metadata repository and various output formats. It is having an easy to use interface which helps the user to solve problems quickly.
• IBM infosphere data architect – It operates on Eclipse-which is an open source platform. this software assists business in both the physical as well as logical models in creating model diagrams which can be further used in multifarious ways. As it is by IBM it can easily be integrated with other IBM applications.
• Sparx enterprise architect – If someone who wants to save cost and desires to have one of the finest data modelling tools, then their search might end with this tool named Sparx enterprise architect as it aids in the building. All in all this tool have the potential of running a dynamic model simulation to showcase the verifiability of models.

Skills needed to become a Data modeler

• Ability to learn something new – There are changes happening every second and now with advanced technology, database system structure are constantly upgrading themselves and one ha to be well versed with all the key technical aspects and have the ability to adopt new modelling methods as it will give the person broaden insights.
• Boolean logic – By boolean logic it is meant that digital logic as it is the basis for all computer systems as the system works on the binary code i.e 0 and 1.As computers interpret coding in binary format only, so it is paramount to possess the skills in the similar format.
• Data representation – It involves breaking down complex information into small bites making it easier to code and interpret by the systems as it saves time, money and all -in all it is cost effective.
• Versatile in DBMS – Must have an experience or should learn how to use basic and advanced level database management systems as they have the potential to handle big data and being a reference in handling DBMS is always beneficial as a whole.

In contrary data, modelling reflects business roles and it makes sure that the data model implemented in the system solidifies those rules. There are basically two types of data models -relational and dimensional and both serve different purposes as the dimensional data model is used for building reporting and analytical systems whereas relational data models are used in storing non-key data only once thus maintaining the integrity of the data in the database. The above-mentioned tools and skills will have to go hand in hand as both are equally beneficial for the business to burgeon. Every tool has its own unique feature and you can choose the tool according to your choice. Data modelling can help businesses grow at an accurate growth rate if used in putting the data effectively in various uses in the organization as the idea would be to provide high-level modelling primitives as an integral part of the data model in order to facilitate the visualization of real-world situations.