Striim

FEBRUARY 10, 2023

It provides networking solutions to support the world’s largest telecommunications service providers, submarine network operators, data and cloud operators, and large enterprises. Quickly turn data into actionable insights that help Macy’s deliver quality digital customer experiences and improve operational efficiencies.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

Data Engineering Podcast

SEPTEMBER 22, 2019

Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. How do you approach project governance and sustainability?

AWS 100

AWS Google Cloud Cloud Storage Data Lake 100

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Source : A stream of sensor data represented as a directed acyclic graph.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

NOVEMBER 16, 2023

Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. There are some renowned cloud players like Amazon Web Services, Google Cloud, IBM Watson, etc.,

Data Science 52

Data Science Technology Programming Language Cloud Computing 52

ProjectPro

OCTOBER 6, 2021

With 67 zones, 140 edge locations, over 90 services, and 940163 organizations using GCP across 200 countries - GCP is slowly garnering the attention of cloud users in the market. Google Cloud Platform is an online vendor of multiple cloud services which can be used publicly. In that case, you’re on the right page.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

Hevo

MAY 8, 2023

The exponential rate of data generation in every modern business from various SaaS applications, Marketing Channels, etc. has compelled them to move from On-premise databases to Cloud-Based Data Warehouses.

Data Warehouse 52

Data Warehouse Machine Learning Cloud Database 52

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. We can clean the data, convert the data, and aggregate the data using dbt so that it is ready for analysis.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

MAY 24, 2021

Serverless computing (often just called "serverless") is a model where a cloud provider, like AWS, abstracts away the concept of servers from the user. In fact, the popularization of separating storage and compute for databases has allowed service providers the ability to offer serverless databases. What Is Serverless?

Database 40

Database Google Cloud AWS Cloud Storage 40

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to make this vision a reality.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Monte Carlo

FEBRUARY 20, 2024

Integrations : They offer a wide array of connectors for databases, SaaS applications, cloud storage solutions, and more, covering both popular and niche data sources. Batch vs Streaming : They focus on automated batch data integration but also support near real-time data replication for certain sources.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Monte Carlo

AUGUST 25, 2023

At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

dbt Developer Hub

NOVEMBER 22, 2022

Once your data warehouse is built out, the vast majority of your data will have come from other SaaS tools, internal databases, or customer data platforms (CDPs). Spreadsheets are the Swiss army knife of data processing. But there’s another unsung hero of the analytics engineering toolkit: the humble spreadsheet.

Data Warehouse 52

Data Warehouse ETL Tools Google Cloud Cloud Storage 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. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Christophe Blefari

AUGUST 4, 2023

A few requirements The source data lies in Postgres database, in flat CSV and in Google Sheets. I want something cloud agnostic—when possible. FAQ and remarks Why do you use Google Cloud? DuckDB is not really a data warehouse. I want to use open-source tooling.

Google Cloud 225

Google Cloud MongoDB NoSQL Data 225

Towards Data Science

MARCH 5, 2024

BigQuery basics and understanding costs BigQuery is not just a tool but a package of scalable compute and storage technologies, with fast network, everything managed by Google. At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ).

Bytes 72

Bytes Google Cloud Cloud Storage Utilities 72

ProjectPro

JULY 30, 2021

Why Learn Cloud Computing Skills? The job market in cloud computing is growing every day at a rapid pace. A quick search on Linkedin shows there are over 30000 freshers jobs in Cloud Computing and over 60000 senior-level cloud computing job roles. What is Cloud Computing? Thus came in the picture, Cloud Computing.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

JANUARY 24, 2023

With the global cloud data warehousing market likely to be worth $10.42 billion by 2026, cloud data warehousing is now more critical than ever. Cloud data warehouses offer significant benefits to organizations, including faster real-time insights, higher scalability, and lower overhead expenses.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

AltexSoft

JULY 29, 2022

Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware. They enable you to access the framework functionality in the cloud, typically charging fees per cluster/ per hour. It lets you run MapReduce and Spark jobs on data kept in Google Cloud Storage (instead of HDFS); or.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

OCTOBER 21, 2022

A single cluster can span across multiple data centers and cloud facilities. This allows for easy horizontal scaling — just add new servers or data centers to your existing infrastructure to handle more amount of data. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

AltexSoft

MAY 12, 2023

There are several widely used unstructured data storage solutions such as data lakes (e.g., Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage), NoSQL databases (e.g., MongoDB, Cassandra), and big data processing frameworks (e.g., Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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. Snowflake Real-Time Data Warehouse Project for Beginners Snowflake provides a cloud-based analytics and data storage service called "data warehouse-as-a-service."

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Monte Carlo

AUGUST 19, 2023

With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52