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

MARCH 20, 2024

Data Engineer The design, building, and management of the data infrastructure that underpins data-driven applications are the responsibilities of a data engineer. Cloud architects are well-versed in various cloud service providers, including Google Cloud Platform, Microsoft Azure, and Amazon Web Services (AWS).

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

Edureka

FEBRUARY 9, 2023

Data Warehousing: The process of collecting, storing, and managing large amounts of data in a centralised repository, such as a data warehouse, to support business intelligence and decision-making processes is referred to as data warehousing.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

JUNE 14, 2023

Google BigQuery – Google’s cloud warehouse, BigQuery, provides a serverless architecture that allows for quick querying due to parallel processing, as well as separate storage and compare for scalable processing and memory. So the Backcountry team had to move quickly to migrate from a legacy stack to a modern data stack.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JULY 30, 2021

Cloud-Native are technologies and services built to leverage cloud architecture. What are some examples of popularly used Cloud Computing services? Windows Azure, Amazon Web services, and iCloud are the very popular ones. Oracle Cloud and IBM cloud are present as market competitors as well.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Confluent

MARCH 4, 2019

Different data problems have arisen in the last two decades, and we ought to address them with the appropriate technology. We need something that can handle large amounts of data, something that can handle unstructured data coming from logs and social media, and data in their native form.

Cloud 88

Cloud Banking Kafka NoSQL 88

Knowledge Hut

FEBRUARY 7, 2023

Data Science on Google cloud platform Google Cloud is one of the best data science learning platforms. It offers all of the tools data scientists need to unlock value from data. The easy-to-pay feature enables users to pay only for consumed services. can take up lots of memory 3.

Data Science 52

Data Science Google Cloud Programming Language AWS 52

ProjectPro

AUGUST 24, 2021

They are also often expected to prepare their dataset by web scraping with the help of various APIs. Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

U-Next

SEPTEMBER 12, 2022

Self-service is crucial to cloud computing since it allows users to quickly and easily get started by filling out a web form. . Zoom Video and Slack allow us to continue living our digital lives thanks to cloud services from Google Cloud, Microsoft Azure, and Amazon Web Services.

Cloud Computing 52

Cloud Computing Cloud Amazon Web Services Banking 52

ProjectPro

MAY 31, 2021

This project will teach you how to design and implement an event-based data integration pipeline on the Google Cloud Platform by processing data using DataFlow. MLOps on GCP Project for Autoregression using uWSGI Flask Here is a project that combines Machine Learning Operations (MLOps) and Google Cloud Platform (GCP).

Big Data 52

Big Data Coding Project Hadoop 52

Monte Carlo

AUGUST 19, 2023

Google BigQuery – Google’s cloud warehouse, BigQuery, provides a serverless architecture that allows for quick querying due to parallel processing, as well as separate storage and compare for scalable processing and memory.

Building 52

Building BI Data Lake Data Governance 52