Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Forbes notes that a full transition to the cloud has proved more challenging than anticipated and many companies will use hybrid cloud solutions to transition to the cloud at their own pace and at a lower risk and cost. This will be a blend of private and public hyperscale clouds like AWS, Azure, and Google Cloud Platform.

Cloud 78

Cloud Google Cloud Azure AWS 78

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

ParkMyCloud

JANUARY 17, 2020

Following the Azure learning path under Microsoft, there are certifications available that allow you to demonstrate your expertise in Microsoft cloud-related technologies and advance your career by earning one of the new Azure role-based certifications or an Azure-related certification in platform, development, or data.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Kentik

APRIL 11, 2016

It has since gone on to become a key technology for running many web-scale services and products, and has also landed in traditional enterprise and government IT organizations for solving big data problems in finance, demographics, intelligence, and more. For more on how we make it work, see Inside the Kentik Data Engine.).

Big Data 40

Big Data Analytics Network Architecture 40

Perficient

FEBRUARY 28, 2023

In the first article in this series, I explained the five components necessary to prevent a Data Lake from Becoming a Data Swamp. Data lakes work on the concept of load first and use later, which means the data stored in the repository doesn’t necessarily have to be used immediately for a specific purpose.

Data 110

Data Analytics Google Cloud Cloud 110

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so?

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Read why the future of data lakehouses is open. Enhanced multi-function analytics.

Cloud 80

Cloud Data Analytics Machine Learning 80

Altexsoft

APRIL 26, 2022

Before we start with the Snowflake technology, it’s important to deal with the key concepts of data warehousing for a common understanding. The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g., CRMs, OLAP/OLTP databases, enterprise applications, etc.) What is Snowflake?

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

MAY 13, 2021

Bursting to the public cloud for other workloads such as Hive or Spark are planned for future WM releases. In this blog, we walk through the Impala workloads analysis in iEDH, Cloudera’s own Enterprise Data Warehouse (EDW) implementation on CDH clusters. Fixed Reports / Data Engineering jobs . Report Format.

Data Engineering 72

Data Engineering Cloud Weak Development Team Resources 72

O'Reilly Media - Ideas

JANUARY 25, 2024

Our data shows that most topics in software architecture and design are down year-over-year. While software architecture is down 3.9% (a relatively small decline), enterprise architecture is up 8.9%. Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%.

Trends 118

Trends Technical Review Technology Artificial Inteligence 118

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. This could be a transactional database or any other storage we take data from. Data extraction.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

JULY 19, 2022

Through all these shifts, data mesh is called to solve the problems of centralized data platforms by giving more flexibility and independence, agility and scalability, cost-effectiveness, and cross-functionality. Data mesh principles and architecture. And it’s their job to guarantee data quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

DECEMBER 4, 2020

Here, we’ll focus on tools that can save you the lion’s share of tedious tasks — namely, key types of data migration software, selection criteria, and some popular options available in the market. Types of data migration tools. There are three major types of data migration software to choose from. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?—?in i.e. plan and apply in addition to remote state management?—?now

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A topic, in turn, is divided into partitions — the smallest units of storage space, hosting an ordered sequence of messages. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Cloudera

DECEMBER 12, 2018

For example, Impala uses the Hive metastore catalog as its data dictionary and it operates directly on data existing in HDFS, which is found through the Namenode API. So, they have the same components: a catalog, query compilation, query execution, and file management and storage, yet they’re independent of each other.

Data 42

Data Marketing Storage Big Data 42

Altexsoft

MARCH 30, 2023

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JANUARY 25, 2022

While our customers include many individual developers, contractors, and hobbyist programmers, commercial (enterprise) software developers are very heavily represented—although there are certainly areas into which we’d like more visibility, such as the crucial Asia-Pacific software development community.

Trends 110

Trends Technical Review Technology Artificial Inteligence 110

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