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

RandomTrees

SEPTEMBER 17, 2024

Level III: Volumes, Tables, Views, Functions & Models Volumes: It is a Logical volume of unstructured, non-tabular data stored in cloud object storage. Tables: It is a collection of data organized by rows and columns and forming the core of structured data storage. GCS buckets on Google Cloud.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

ProjectPro

JANUARY 24, 2023

Since its public release in 2011, BigQuery has been marketed as a unique analytics cloud data warehouse tool that requires no virtual machines or hardware resources. BigQuery is a highly scalable data warehouse platform with a built-in query engine offered by Google Cloud Platform. What is Google BigQuery Used for?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Knowledge Hut

DECEMBER 4, 2023

A cloud provider leases infrastructure and technology to other businesses or individual people for computing, networking or storage purposes. The top 3 major providers as of this date are Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), with AWS leading the market. which you can explore.

Cloud Computing 52

Cloud Computing Cloud Google Cloud AWS 52

ProjectPro

SEPTEMBER 6, 2021

So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? It developed and optimized everything from cloud storage, computing, IaaS, and PaaS. And that is one big reason it is the market leader and dominates other cloud technologies aggressively. Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

ProjectPro

OCTOBER 6, 2021

Flexera’s State of Cloud report highlighted that 41% of the survey respondents showed the most interest in using Google Cloud Platform for their future cloud computing projects. Google Cloud Platform is an online vendor of multiple cloud services which can be used publicly.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

Knowledge Hut

JULY 24, 2023

In-memory Databases For applications that demand real-time data processing, in-memory databases are created. These databases use RAM-based data storage, which offers quicker access and response times than disk-based storage. These databases give users more freedom in how to organize and use data.

Database 52

Database NoSQL Management Relational Database 52

Knowledge Hut

NOVEMBER 17, 2023

The global market for cloud services is expected to reach $623 billion by 2023, up from $272 billion in 2018. This rapid growth is being driven by a number of factors, including the increasing adoption of cloud-based applications, the growing need for data storage and processing, and the rise of IoT devices.

Cloud Computing 52

Cloud Computing Cloud Google Cloud Amazon Web Services 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

AltexSoft

JULY 29, 2022

No matter the actual size, each cluster accommodates three functional layers — Hadoop distributed file systems for data storage, Hadoop MapReduce for processing, and Hadoop Yarn for resource management. 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

Rockset

MAY 24, 2021

Serverless Data Tools Myriad tools exist for serverless data storage layers, each one offering its own set of advantages. The most popular data storage layers for a serverless stack include: Amazon S3: Amazon Simple Storage Service is offered through AWS as a scalable infrastructure solution.

Database 40

Database Google Cloud AWS Cloud Storage 40

Knowledge Hut

MAY 8, 2023

Cloud computing platforms have become increasingly popular as businesses worldwide have stopped employing onsite data centers and server rooms. Around two-thirds of large firms are shifting business apps and data storage to Cloud services.

Cloud 52

Cloud Engineering Cloud Computing Amazon Web Services 52

ProjectPro

JULY 30, 2021

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. What is Cloud Computing?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 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.)

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

Knowledge Hut

APRIL 12, 2023

Gather and Store Metrics: Azure enables the collection and storage of metrics, which can assist in identifying efficient strategies. Virtual Hard Drives: Azure offers virtual hard drives (VHDs) that offer a significant amount of data storage. VHDs are extensions of virtual machines used for storing large amounts of data.

Cloud Computing 52

Cloud Computing Amazon Web Services Certification Cloud 52

U-Next

JULY 2, 2022

Introduction To Cloud Engineer Skills. The cloud computing model delivers computing resources on-demand – that is, through the Internet – such as data storage, compute power and data processing. The choice of one or more cloud engineer skills would depend on the business needs and the requirements.

Cloud 40

Cloud Engineering Cloud Computing Amazon Web Services 40

Christophe Blefari

AUGUST 4, 2023

The modern data stack as a collection of tools which interacts altogether to serve data to consumers is still relevant. Personally I think that the modern data stack characterises by having a central data storage in which everything happens. I hope you'll enjoy this Data News Summer Edition.

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Google Cloud MongoDB NoSQL Data 225

AltexSoft

MAY 12, 2023

For example, developers can use Twitter API to access and collect public tweets, user profiles, and other data from the Twitter platform. Data ingestion tools are software applications or services designed to collect, import, and process data from various sources into a central data storage system or repository.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Confluent

SEPTEMBER 20, 2019

Confluent Cloud addresses elasticity with a pricing model that is usage based, in which the user pays only for the data that is actually streamed. If there is no traffic in any of the created clusters, then there are no charges (excluding data storage costs).

Kafka 21

Kafka Management Cloud AWS 21

ProjectPro

MAY 31, 2021

For such scenarios, data-driven integration becomes less comfortable, so you must prefer event-based data integration. 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.

Big Data 52

Big Data Coding Project Hadoop 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