Data Management

Data Archietcture

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What is Data Architecture

Data architecture is the process of standardizing and creating a blueprint of how organizations collect, store, transform, distribute, and use data; in short, it is the formal structure for managing data flow.

Legacy methods have become outdated — too cumbersome and slow to meet modern business and customer demands. However, tools and techniques have evolved to give businesses an edge in how to collect and use data that’s relevant to their needs. Data architecture bridges the traditional gap between business leaders and IT, giving them a platform to ensure that technology and strategy align to power the business forward. The goals and needs of your organization are what shapes the data architecture.

Proper architecture helps you gain a better understanding of the data, where it comes from, where it is stored and the process by which it flows from raw data to actionable insights. It is the backbone for which every other data-oriented work and strategy rests upon. A successful architecture provides clarity for every aspect of the data.

Data lakes

As the amount of data coming into the average enterprise continues to grow in volume and speed, a data lake helps stop the numbers from overwhelming the system.

A data lake isa centralized repository that allows you to store all your structured and unstructured data at any scale. Centralized data platforms act as a buffer to process transactions without taking computing power from core systems.

noSQL

Traditional relational database management systems (RDBMS) are a great choice if a business is dealing with small amounts of data that need to be kept well-structured.

As data volume and variability can make it harder for engineers and architects to manage the information manually, a noSQL engine helps stabilize data models while increasing their accuracy. noSQL provides a high level of scalability and is used in a distributed computing environment.

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Artificial Intelligence vs Data Science vs Machine Learning

Artificial Intelligence vs Data Science vs Machine Learning

Artificial Intelligence vs Data Science vs Machine Learning

Artificial Intelligence vs Data Science vs Machine Learning