Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

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 is widely used by data engineers for building scalable and reliable data processing systems. Hadoop provides tools for data storage, processing, and analysis, including Hadoop Distributed File System (HDFS) and MapReduce. It can add more processing power and storage as the data grows.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Below, we share what the “basic” data platform looks like and list some hot tools in each space (you’re likely using several of them): The modern data platform is composed of five critical foundation layers. Data Storage and Processing The first layer?

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

JUNE 26, 2023

From analysts to Big Data Engineers, everyone in the field of data science has been discussing data engineering. When constructing a data engineering project, you should prioritize the following areas: Multiple sources of data (APIs, websites, CSVs, JSON, etc.) Master data processing methods.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

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. What are the Different Storage Layers Available in Snowflake? Add Your Heading Text Here REMOVE @my_internal_stage PATTERN='.*.csv.gz';

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52