Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Notice how Snowflake dutifully avoids (what may be a false) dichotomy by simply calling themselves a “data cloud.”

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

APRIL 25, 2023

It provides a unified API that allows businesses to collect customer data from various sources, such as websites, mobile apps, and servers. Key features: Centralized customer data Real-time data streaming Support for data governance 6. It can add more processing power and storage as the data grows.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

DareData

JANUARY 30, 2023

As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. Gone are the days when organizations could rely on models trained and stored in notebooks without any structure, governance, or testing.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Amazon S3 for AWS, Azure Blob Storage for Azure, or Google Cloud Storage for GCP) to store the actual data files in micro-partitions.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below. Here are some of the most common solutions that are involved in modern data pipelines and the role they play.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. This comprehensive guide will cover all of the basics of data engineering including common roles, functions, and responsibilities.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

U-Next

OCTOBER 27, 2022

Cloud computing is the term used to describe internet data storage and access. It doesn’t store any data on your computer’s hard drive and allows users to access data from faraway servers. Data ingestion capability . Introduction . Listening to and comprehending business needs .

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

ProjectPro

MAY 31, 2021

Personal data privacy and protection are becoming increasingly crucial, and you should prioritize them immediately as you embark on your big data journey. You must consolidate all your data initiatives, sources, and datasets into one location or platform to facilitate governance and carry out privacy-compliant projects.

Big Data 52

Big Data Coding Project Hadoop 52

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? Zero Copy Cloning: Create multiple ‘copies’ of tables, schemas, or databases without actually copying the data. This noticeably saves time on copying and drastically reduces data storage costs. However, merely knowing what it consists of isn’t enough.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations.

Building 52

Building BI Data Lake Data Governance 52