Data Architecture

Keywords

Data Architecture, Data Quality, Sustainable Data Architecture, Big Data

Description

Data is the core of any enterprise system, and it is used for decision-making, training machine learning(ML)/deep learning(DL) models, creating reports, and generating insights. Data-driven describes a strategic process of leveraging insights from data, To Achieve Data-Driven, we need the best ways to collect, store, analyze and protect valuable data. Data architecture is a discipline that documents an organization's data assets, maps how data flows through the system and provides a blueprint for managing data. It provides criteria for data processing operations to make it possible to design data flows and also control the flow of data in the system. Data architecture is an “intellectually graspable" abstraction of a complex data-driven system; It gives a basis for analyzing Data-Driven systems' behavior.¬†Model-Driven Engineering (MDE) techniques, such as meta-modeling, model weaving, and model transformation; MDE aims to address the complexity of software development by raising the abstraction level and automating the generation of the application artifacts.

Objective

  1. Provide Meta-model for Data Architecture for Big Data.
  2. Provide Architecture Modeling Tool
  3. Analyzing the data quality by integrating the Modeling tool with other technologies like Greate_Expectations.
  4. Provide Sustainable Data Architecture

Focus Areas

Software Architecture, Big Data Management, Model Driven Engineering