What is Data Modelling?
Data modelling is the process of creating a conceptual representation of data and its'
relationships to other data. It involves identifying the types of data that will be stored,
organizing that data into logical groups, and defining the relationships between those
groups. The goal of data modelling is to create a clear and consistent blueprint for how
data will be organized and used within an organization.
There are several different types of data models, including conceptual, logical, and phy
models. Conceptual models provide a high-level view of the data and its relationships,
while logical models provide a more detailed representation of the data's structure and
relationships. Physical models are used to map the logical model to the physical storage
data in a database or other data storage system.
Data modelling is an important step in the development of information systems and
databases because it helps ensure that the data is organized and stored in a way that
supports the needs of the organization. It can also help identify potential problems and
inconsistencies in the data early in the development process, which can save time and
resources later on.
,Stages involved in the decision-
making process for data modelling
Problem Data Data Model Model Model Mod
Identificatio Collection Preparation Selection Developme Evaluation Deploy
n nt t
,Problem Identification
The first stage involves identifying the
problem that needs to be solved or the
question that needs to be answered. This
step typically involves consulting with
stakeholders and identifying their
requirements.
, DATA COLLECTION
The second stage involves collecting relevant
data that can be used to address the
problem or answer the question. This may
involve gathering data from internal sources
such as databases or external sources such
as APIs, surveys, or third-party data
providers.
Data modelling is the process of creating a conceptual representation of data and its'
relationships to other data. It involves identifying the types of data that will be stored,
organizing that data into logical groups, and defining the relationships between those
groups. The goal of data modelling is to create a clear and consistent blueprint for how
data will be organized and used within an organization.
There are several different types of data models, including conceptual, logical, and phy
models. Conceptual models provide a high-level view of the data and its relationships,
while logical models provide a more detailed representation of the data's structure and
relationships. Physical models are used to map the logical model to the physical storage
data in a database or other data storage system.
Data modelling is an important step in the development of information systems and
databases because it helps ensure that the data is organized and stored in a way that
supports the needs of the organization. It can also help identify potential problems and
inconsistencies in the data early in the development process, which can save time and
resources later on.
,Stages involved in the decision-
making process for data modelling
Problem Data Data Model Model Model Mod
Identificatio Collection Preparation Selection Developme Evaluation Deploy
n nt t
,Problem Identification
The first stage involves identifying the
problem that needs to be solved or the
question that needs to be answered. This
step typically involves consulting with
stakeholders and identifying their
requirements.
, DATA COLLECTION
The second stage involves collecting relevant
data that can be used to address the
problem or answer the question. This may
involve gathering data from internal sources
such as databases or external sources such
as APIs, surveys, or third-party data
providers.
