Data modelling refers to the creation of data models which can be physical, logical, or conceptual. It also involves determination of the data needs of an entity and its objectives. Data modelling does not just explain the elements of data but also the structures they create and any relationships between them. Data model development needs experts, or data modellers, will work together with the organization’s workforce to determine the objectives and information systems end-users. After creating the data models, you can analyze your data in real-time with the aid of Elasticsearch. You can ask professional data developers to work with your organization to find a suitable solution for Elasticsearch. This has been made easier by the availability of elasticsearch consulting services.
A brief history
Data modelling, databases, and programming languages depend on each other. They have therefore, evolved together. This happened in four phases which sometimes overlap each other.
Phase 1 – between the 1960s and 1999. This period included the creation of hierarchical database management systems. In the 1990s, object-oriented database management systems were created.
Phase 2 – it is defined as a relational phase, and this is where the structured query language and some nonSQL products were introduced. It roughly started in 1990.
Phase 3 – this is the phase which allowed for the support of online analytical processing. Specialized database management systems were also created at this stage. It was also developed around 1990.
Phase 4 – it led to the introduction of NoSQL in the year 2008. It supported Big Data use, nonrelational data, and graphs.
Data modelling in the 1960s
Development of data models started getting crucial in the 1960s. This is the era in which the popularity of management information systems was on a rise. Before this period, there was less or no storage of data. This is the time when theoretical data models were proposed and some of them were turned into reality. This led to the introduction of the hierarchical data model and the network data model. Also at this time, there was the creation of the first database system known as an integrated data store. It worked with the network model, giving an effect of representing the relationships between objects.
Data modelling in the 1970s
E.F. Codd played a significant role during this stage, coming up with ideas which suggested different means of data handling. He said that the entire data in a database can be displayed in table form by the use of rows and columns in a structure he termed relations. A person would gain access to these relations with the aid of non-procedural language. Instead of using an algorithm to find data, his idea just required the entry of a file name to identify information.
Data modelling in the 1980s
During this period, object role modelling was created which significantly changed the perception of data. Traditionally, data procedures were separately stored. Codd’s relational data models were increasingly becoming popular, replacing the hierarchical data model. This was enhanced by the fact that query optimizers were good enough to incorporate the relational model.
1998 to present
In 1998, the NoSQL database was created. The model did not use SQL connections but was still relational. The later versions of this model did not use relations. NoSQL is so flexible that it allows for the storage of data in large quantities. However, there seems to be a deficiency in modellers having expert knowledge in the NoSQL systems. Thus, finding experienced NoSQL data modellers and tools has become an ever-present need.