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Data Modeling

Data modeling is the process of designing and creating a model or blueprint of a database that defines the structure of the data, the relationships between the data, and the rules for data integrity. Data modeling helps organizations to better understand their business processes and to more effectively design and implement databases to support those processes. There are different types of data models that can be used, including conceptual, logical, and physical models. Conceptual models focus on the high-level concepts and relationships in the data, logical models show the detailed structure of the data, and physical models show how the data will be stored and accessed in a specific database management system.

Data modeling can help improve business functions in several ways

Improved understanding of business processes: Data modeling helps organizations to understand their business processes and how data is used within those processes. This can lead to more effective and efficient processes.
Better data management: Data modeling helps to define the structure of the data, the relationships between data elements, and the rules for data integrity. This can improve the quality and consistency of the data, and make it easier to manage and maintain.
Enhanced data communication: Data modeling helps to clearly document and communicate the structure and relationships of the data to different stakeholders, including developers, analysts, and business users.
Improved decision making: Data modeling helps organizations to understand their data and how it is used, which can enable more informed and effective decision making.
Increased efficiency: By designing a well-structured database, organizations can improve the efficiency of their business processes and reduce the time and effort required to access and manipulate data.

There are several types of data modeling techniques, including

Conceptual Data Modeling: This type of data modeling focuses on the high-level concepts and relationships in the data, and is used to define the overall structure of the data.
Logical Data Modeling: This type of data modeling focuses on the detailed structure of the data, and is used to define the relationships between different data elements.
Physical Data Modeling: This type of data modeling focuses on how the data will be stored and accessed in a specific database management system. It includes details such as data types, indexes, and constraints.
Entity Relationship (ER) Modeling: This type of data modeling is used to describe the relationships between entities (data elements) in a database.
Object-Oriented Data Modeling: This type of data modeling is based on the object-oriented programming paradigm, and is used to model the data as objects and their relationships.
Dimensional Modeling: This type of data modeling is used for data warehouses and is based on the concept of a "fact table" that contains the core data, and "dimension tables" that contain additional data about the facts.
NoSQL Data Modeling: This type of data modeling is used for non-relational databases, such as NoSQL databases, and is based on the data storage and access requirements of the application.

Features

Data Architecture

Design DE cloud solutions designed by a team of certified experts

Preparation and automation of ETL processes for multi-structured data

Design optimization of database and data warehouse platforms

Preparation of software solutions for integrating systems

Data Processing

Implementation of scalable data driven solutions

Real-time and batch data pipelines & processing

Data quality and standardization services

Data integration & maintenance services

Data Lakes and Data Warehouses setup

Data Analytics

Consultancy and preparation of a plan for analytical method development
Preparation of recommendation systems
Searching for patterns in sequential data
Quality evaluation of organizations’ analytical products