Data modeling
is the process of creating a simplified diagram of a software system and the
data element contains text and symbols to represent the data and how it flows.
- Data models
serve as a blueprint for creating a new database or reengineering an existing
one. Overall, data modeling assists an organization in successfully
using its data to satisfy business information demands.
- Data
modelers, data architects, and other data management experts have created data
models with the help of business analysts, executives, and users.
- Helps to
define the primary and foreign keys, relational tables, and stored procedures.
- Helps to
define the database and conceptual, logical, and physical levels.
- Identify any
redundant or missing data.
- Make maintenance
and upgrades on the IT infrastructure faster and more affordable.
WHY
USE A DATA MODEL?
- A data model
helps design the database at the conceptual, physical, and logical levels.
- Data model
structure helps to define the relational tables, primary and foreign keys, and
stored procedures.
- Database
developers may use it to build a physical database since it gives a clear image
of the fundamental data.
- Although the
initial data model generation is labor-intensive and time-consuming, it
ultimately makes IT infrastructure upgrades and maintenance less expensive and
quicker.
TYPES
OF DATA MODELS:
There are several
data models available, Mainly THREE types of data models used:
- Conceptual
data model
- Logical data
model
- Physical
data model
Other data
model types are:
- Graph data
model
- Relational
data model
- Hierarchical
data model
- Entity-relational
data model
The data
models are used to represent the data and how it is stored in the database.
NOTE: Database
Schemas and Data Models are not the same. The database
schema is a collection of conceptual tools for defining data, data
relationships, and consistency constraints, whereas the data model is a
collection of conceptual tools for describing data, data relationships, and
consistency constraints. CONCEPTUAL
DATA MODEL: - The conceptual data model is a structured business view of
the data needed to support business operations, record business events, and
track quality measures.
- Mainly it is used by business stakeholders.
- This data model defines WHAT the system contains. It
is not tied to specific database and applications technology.
 LOGICAL
DATA MODEL:
- Logical data
models show how data entities are related and describe the data from a
technical perspective.
- This model
is typically created by data architects and business analysts.
- It establishes
the structure of data elements and the relationships among them.
- It is mainly
used for:
1. Business requirements
2. Quality data structures
- There are
THREE main components of the Logical Data Model:
1. Entities
2. Attributes
3. Relationships
PHYSICAL
DATA MODEL: - The
construction of a physical data model is based on a logical model.
- This data
model describes HOW the system will be implemented using a specific DBMS
system.
- It represents
relational data objects and their relationships.
- It is used
to generate DDL statements which can then be deployed to a database server.
- Types of data
models:
1. Flat-file
2. Hierarchical
3. Relational
4. Object-Oriented DATA MODELING SOFTWARE/ TOOLS: some important data mode tools are: - ER/Studio
- DbSchema Pro
- Ewin Data
Modeler
- Archi
- SQL Database
Modeler
- IBM
InfoSphere Data Architect
- PgModeler
ADVANTAGES
AND DISADVANTAGES OF DATA MODELING:
ADVANTAGES
OF DATA MODELING:
- It verifies
that the items depicted are correct.
- The ability
to create a strong link between tables, stored procedures, primary and
foreign keys.
- Data Model
is used as a reference for developing SQL, and SQL logic may be readily
constructed utilizing it.
- Ability to find
a solid relationship between the tables, stored procedures, and primary and
foreign keys.
- Clear scope.
- Identify the
source of data.
- Document data
mapping.
- Control of
data redundancy.
- Build software
faster.
- Data consistency.
- Security.
- Enforcement of
standards.
- Reduce cost.
- Helping businesses
to communicate within and across organizations.
- Allowing the
business to document data mappings in the ETL process
DISADVANTAGES
OF DATA MODELING: - You must
know the physical data are stored characteristics to develop a data model.
- A complete
application must be modified to accommodate even minor structural changes.
- Database
management systems don't provide a language for set manipulation.
- In DBMS,
there is no standard data manipulation language.
CONCLUSION:
In this
article, we learn about data modeling, types of data models, advantages and
disadvantages of data models. The primary goal of a designing data model is to
ensure that data objects provided by the functional team are accurately
represented. The main disadvantage is that even minor changes in structure
necessitate changes to the entire application.
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