Knowledge Hut

MARCH 19, 2024

With its extensive range of cloud services, Amazon Web Services (AWS) has completely changed the way businesses run. The AWS case studies comprehensively explain how companies or organizations have used Amazon Web Services (AWS) to solve problems, boost productivity, and accomplish objectives.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

Knowledge Hut

DECEMBER 26, 2023

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. As of May 2017, the total number of employees was 341,400.

Big Data 52

Big Data Unstructured Data Amazon Web Services Hadoop 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

phData: Data Engineering

JANUARY 3, 2022

Analyzing the data, ensuring it adheres to data governance rules and regulations. Understanding the pros and cons of data storage and query options. For example, an enterprise might be using Amazon Web Services (AWS) as a cloud provider, and you want to store and query data from various systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

ProjectPro

MARCH 16, 2015

Thus, the computing technology and infrastructure must be able to render a cost efficient implementation of: Parallel Data Processing that is unconstrained. Provide storage for billions and trillions of unstructured data sets. The upswing for big data in healthcare industry is due to the falling cost of storage.

Healthcare 40

Healthcare Big Data Project Hospitality 40

Knowledge Hut

DECEMBER 26, 2023

Analyzing and organizing raw data Raw data is unstructured data consisting of texts, images, audio, and videos such as PDFs and voice transcripts. The job of a data engineer is to develop models using machine learning to scan, label and organize this unstructured data.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98