Existek

JANUARY 11, 2022

We suggest drawing a detailed comparison of Azure vs AWS to answer these questions. Azure vs AWS market share. What is Microsoft Azure used for? Azure vs AWS features. Azure vs AWS comparison: other practical aspects. Azure vs AWS comparison: other practical aspects. Azure vs AWS: which is better?

Azure 52

Azure AWS Cloud How To 52

Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

InnovationM

MAY 14, 2023

In this article, I will share practical insights and technologies utilized in building and harnessing the potential of data lakes. Demystifying Data Lakes Data lakes serve as flexible storage repositories, enabling organizations to store raw and diverse data types, breaking away from the constraints of traditional data warehouses.

Data 52

Data Storage Construction Business Intelligence 52

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JANUARY 15, 2021

As depicted in the chart, Cloudera Data Warehouse ran the benchmark with significantly better price-performance than any of the other competitors tested. Compared to CDW, Amazon Redshift ran the workload at 19% higher cost, Azure Synapse Analytics had 43% higher cost, DW1 had 79% higher cost, and DW2 had 5.5x higher cost.

Performance 97

Performance Cloud Data Storage 97

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

This will be a blend of private and public hyperscale clouds like AWS, Azure, and Google Cloud Platform. Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. Engagements may be on a short-term tactical basis or as part of a long-term managed service.

Cloud 78

Cloud Google Cloud Azure AWS 78

Cloudera

NOVEMBER 6, 2017

A noteworthy point is that Cloudera complements popular cloud services, such as Amazon Web Services (AWS) and Microsoft Azure. Simply choose the AWS or Azure compute instances, class of storage, and go. Security policies are set once and implemented uniformly upon data and users anywhere.

Cloud 40

Cloud Azure Analytics AWS 40

ParkMyCloud

JANUARY 17, 2020

Each of the ‘big three’ cloud providers (AWS, Azure, GCP) offer a number of cloud certification options that individuals can get to validate their cloud knowledge and skill set, while helping them advance in their careers and broaden the scope of their achievements. . Microsoft Azure Certifications. Azure Fundamentals.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

InfoWorld

FEBRUARY 9, 2024

It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment. In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex.

Big Data 98

Big Data Azure Google Cloud Data 98

Datavail

JUNE 15, 2023

The Microsoft Fabric announcement at Microsoft Build 2023 has caused quite a stir in the data and analytics world. Microsoft Fabric is an all-in-one analytics solution that brings together seven Azure services on a shared SaaS foundation, in a unified experience combined with AI. What is Microsoft Fabric?

Azure 52

Azure Analytics Storage Generative AI 52

Cloudera

MAY 22, 2018

It was exactly one year ago at Strata London that we introduced the world to Cloudera Altus Data Engineering. We believed that if you empowered data engineers, data scientists, and analysts with self-service tools and access to unlimited data and compute, your organization can accomplish truly great things.

Azure 40

Azure Data Engineering AWS Engineering 40

O'Reilly Media - Ideas

JANUARY 25, 2024

Attendees included small business owners, sales and marketing personnel, and C-suite executives, along with many programmers and engineers from different disciplines. We’ve also been running courses focused on specific industries: Generative AI for Finance had over 2,000 registrations, and Generative AI for Government over 1,000.

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

Cloudera

DECEMBER 15, 2022

With CDP, customers can deploy storage, compute, and access, all with the freedom offered by the cloud, avoiding vendor lock-in and taking advantage of best-of-breed solutions. With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Advanced capabilitie.

Cloud 81

Cloud Data Analytics Machine Learning 81

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. How data engineering works under the hood.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

JULY 19, 2022

The HR team will manage all of this data and generate datasets to be consumed by other users in the company like the marketing team. They also own the governance of their domain. It’s easiest to understand the concept of a data mesh by looking at the core principles behind it which we’re going to uncover more extensively later on.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

APRIL 26, 2022

The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. The former extracts and transforms information before loading it into centralized storage while the latter allows for loading data prior to transformation. Modern data pipeline with Snowflake technology as its part.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

OCTOBER 2, 2020

Data is a valuable source that needs management. If your business generates tons of data and you’re looking for ways to organize it for storage and further use, you’re at the right place. Read the article to learn what components data management consists of and how to implement a data management strategy in your business.

Database Administration 64

Database Administration Strategy Data Technical Review 64

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. Here at ParkMyCloud, we talk to a lot of Cloud Architects!

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

MARCH 6, 2018

Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security. This clearly defines the data context even for transient compute applications. Altus SDX creates a common catalog of data, defining what is available and how it can be used by whom.

Analytics 40

Analytics Cloud Big Data AWS 40

Cloudera

OCTOBER 26, 2017

Check out Greg Rahn’s session, “ Rethinking data marts in the cloud: Common architectural patterns for analytics ” at the Strata Data Conference in Singapore, December 4-7, 2017, to learn how to architect analytic workloads in the cloud and the core elements of data governance. Let’s discuss each in more detail.

Cloud 43

Cloud Data Storage Analytics 43

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

NOVEMBER 5, 2021

Health information governance and stewardship ensure compliance of data use with regulations, standards, ethical norms, and internal organizational policies. Particularly, X12N specification is used for insurance and reimbursement transactions by third-party payers and government health plans. Supported data formats.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

OCTOBER 8, 2021

Data integration process. On the enterprise level, data integration may cover a wider array of data management tasks including. application integration — the process of enabling individual applications to communicate with one another by exchanging data. Data profiling and cleansing. Data profiling and cleansing.

Tools 52

Tools Data Software Review Open Source 52

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics.

Data Engineering 115

Data Engineering Engineering Data Storage 115

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.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” Our data shows that they’re getting the message.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

Cloudera

FEBRUARY 22, 2021

Providing a comprehensive set of diverse analytical frameworks for different use cases across the data lifecycle (data streaming, data engineering, data warehousing, operational database and machine learning) while at the same time seamlessly integrating data content via the Shared Data Experience (SDX), a layer that separates compute and storage.

Data 81

Data Analytics Government Technical Review 81

DataRobot

FEBRUARY 2, 2022

DataRobot enables entire teams — from data scientists to data engineers and from IT to business users — to collaborate on a unified platform. Every organization is under growing pressure to transform this sea of data into valuable insights. AI is how to turn data into insight and impact — and a competitive edge.

Cloud 52

Cloud Innovation Google Cloud Azure 52