Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

Knowledge Hut

OCTOBER 6, 2023

Recently, the AWS Data Analytics Certification has captured my attention, and I have been researching the many AWS data analytics certification benefits. I'll delve into the specifics in this post to help you determine if AWS Data Analytics certification is worth it. What is AWS Data Analytics?

AWS 52

AWS Certification Data Analytics IT 52

Christophe Blefari

JANUARY 20, 2024

formats — This is a huge part of data engineering. Picking the right format for your data storage. You'll be seen as the most technical person of a data team and you'll need to help regarding "low-level" stuff you team. You'll be also asked to put in place a data infrastructure.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Striim

SEPTEMBER 11, 2024

Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

JANUARY 12, 2024

We’ve previously discussed the need for quality over quantity when it comes to big data and, in this article, we’ll be looking at how recent technological innovations and new processes across 4 of the 5 ‘V’s of big data (volume, velocity, veracity, variety) are changing the future of big data analytics.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Edureka

JUNE 1, 2023

This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Sync Computing

JANUARY 27, 2025

They offer a high memory-to-CPU ratio, with configurations providing up to 1 Terabyte of memory, making them ideal for in-memory databases, big data analytics, and real-time processing. Ideal for real-time analytics, high-performance caching, or machine learning, but data does not persist after instance termination.

AWS 52

AWS Data Lake Machine Learning Big Data 52

ProjectPro

FEBRUARY 8, 2023

Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. The popular data integration tool, AWS Glue, enables data analytics users to quickly acquire, analyze, migrate, and integrate data from multiple sources.

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Weekly

MARCH 3, 2024

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding.

Data Engineering 68

Data Engineering Data Engineer Engineering Pipeline-centric 68

Rockset

JULY 29, 2022

For query processing, BigQuery charges $5 per TB of data processed by each query, with the first TB of data per month free. For storage, BigQuery offers up to 10GB of free data storage per month and $0.02 per additional GB of active storage, making it very economical for storing large amounts of historical data.

Data Analytics 52

Data Analytics Data Warehouse Datasets Cloud 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

AltexSoft

AUGUST 4, 2021

Since data marts provide analytical capabilities for a restricted area of a data warehouse, they offer isolated security and isolated performance. Data mart vs data warehouse vs data lake vs OLAP cube. Data lakes, data warehouses, and data marts are all data repositories of different sizes.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

Knowledge Hut

JANUARY 18, 2024

IBM is one of the best companies to work for in Data Science. The platform allows not only data storage but also deep data processing by making use of Apache Hadoop. The CDP private cloud is a scalable data storage solution that can handle analytical and machine learning workloads.

Data Science 98

Data Science Amazon Web Services Big Data Finance 98

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

Edureka

FEBRUARY 7, 2023

They should also be proficient in programming languages such as Python , SQL , and Scala , and be familiar with big data technologies such as HDFS , Spark , and Hive. Learn programming languages: Azure Data Engineers should have a strong understanding of programming languages such as Python , SQL , and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. For example, developers can use Twitter API to access and collect public tweets, user profiles, and other data from the Twitter platform.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

NOVEMBER 7, 2023

The applications of cloud computing in businesses of all sizes, types, and industries for a wide range of applications, including data backup, email, disaster recovery, virtual desktops big data analytics, software development and testing, and customer-facing web apps. What Is Cloud Computing?

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Snowflake

JUNE 29, 2023

Snowflake empowers government agencies to meet this challenge by providing modern cloud technologies and services for deploying critical workloads, including modern data sharing. This milestone ensures our recently launched Government & Education Data Cloud is even better equipped to help U.S.

Education 52

Education Government Data Lake Data Security 52

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

ProjectPro

OCTOBER 6, 2021

GCP offers 90 services that span computation, storage, databases, networking, operations, development, data analytics , machine learning , and artificial intelligence , to name a few. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization 2.

Google Cloud 52

Google Cloud Project Data Lake Healthcare 52

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 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.) Source Code: Realtime Data Analytics 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

MARCH 1, 2018

The leading big data analytics company Kyvo Insights is hosting a webinar titled “Accelerate Business Intelligence with Native Hadoop BI platforms.” The webinar will address examples from the many organizations that depend on Kyvos and also the data compiled by Forrester Research. PRNewswire.com, February 1, 2018.

Hadoop 52

Hadoop NoSQL Retail BI 52

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Project Coding 52

Knowledge Hut

NOVEMBER 17, 2023

Azure Storage As the name suggests, Azure storage deals with data storage solutions on the Microsoft cloud. It is highly secure and scalable and can be used to store a variety of data objects. They can also use Azure CLI or Azure PowerShell for configuring tasks and data management.

Data Lake 52

Data Lake Programming Language Certification Java 52

ProjectPro

APRIL 1, 2016

(Source: [link] ) Hadoop is powering the next generation of Big Data Analytics. NetworkAsia.net Hadoop is emerging as the framework of choice while dealing with big data. Commvault’s new technology will be supporting various big data environments like Hadoop, Greenplum and GPFS. March 11, 2016. March 22, 2016.Computing.co.uk

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

Knowledge Hut

MARCH 28, 2024

They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? These pipelines differ from traditional ELT pipelines by doing the data cleaning and normalization prior to load.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

FEBRUARY 8, 2017

.” said the McKinsey Global Institute (MGI) in its executive overview of last month's report: "The Age of Analytics: Competing in a Data-Driven World." 2016 was an exciting year for big data with organizations developing real-world solutions with big data analytics making a major impact on their bottom line.

Big Data 40

Big Data Hadoop Data Lake Machine Learning 40

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40