Cloudera

JUNE 7, 2022

In our very own Enterprise Data Maturity research surveying over 3,000 IT and senior business leaders, we found that 40% of organizations are currently running hybrid but mostly on-premises, and 36% of respondents expect to shift to hybrid multi-cloud in the next 18 months. Where data flows, ideas follow.

Data 108

Data Architecture Analytics Government 108

Cloudera

JANUARY 19, 2022

We have been working hard to build our cloud-native data services on Cloudera Data Platform (CDP), which include CDP Data Warehouse, CDP Operational Database, CDP Machine Learning, CDP Data Engineering and CDP Data Flow. Download the reports to see the detailed scores .

Report 87

Report Technical Advisors Cloud Analytics 87

Cloudera

SEPTEMBER 21, 2021

Many customers looking at modernizing their pipeline orchestration have turned to Apache Airflow, a flexible and scalable workflow manager for data engineers. Take a test drive of Airflow in Cloudera Data Engineering yourself today to learn about its benefits and how it could help you streamline complex data workflows.

Off-The-Shelf 95

Off-The-Shelf Data Engineering Virtualization Cloud 95

KitelyTech

FEBRUARY 3, 2021

It often includes three main components like the database schema, database application, and data engine. The consistent operation between those three components will facilitate data integrity, reliability, consistency, and transaction maintainability. Therefore, the software must have an easily extendable architecture.

Big Data 52

Big Data Data Development Business Intelligence 52

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 120

Artificial Inteligence Generative AI Security Applications 120

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Data 63

Data Software Review Technical Review Microservices 63

Cloudera

DECEMBER 10, 2020

Drawing on more than a decade of experience in building and deploying massive scale data platforms on economical budgets, Cloudera has designed and delivered a cost-cutting cloud-native solution – Cloudera Data Warehouse (CDW), part of the new Cloudera Data Platform (CDP). Watch this video to get an overview of CDW. .

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 97

Architecture Innovation Data Open Source 97

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

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

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Native frameworks.

Big Data 63

Big Data Data Storage Microservices 63

CIO

JULY 29, 2022

For example, if a data team member wants to increase their skills or move to a data engineer position, they can embark on a curriculum for up to two years to gain the right skills and experience. The bootcamp broadened my understanding of key concepts in data engineering.

Groups 246

Groups Security Development Data Engineering 246

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. Iceberg is designed to be open and engine agnostic allowing datasets to be shared.

Data 88

Data Open Source Storage Machine Learning 88

Apiumhub

SEPTEMBER 20, 2023

From software architecture to artificial intelligence and machine learning, ​​these conferences offer unparalleled insights, networking opportunities, and a glimpse into the future of technology. In this article, we´ll be your guide to the must-attend tech conferences set to unfold in October. For more information, visit the event site here.

Conference 96

Conference Artificial Inteligence UI/UX Machine Learning 96

Cloudera

APRIL 26, 2023

Can you achieve similar outcomes with your on-premises data platform? Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. This is exactly where cloud native architectures excel, and why they are so popular.

Cloud 63

Cloud Data Load Balancer Storage 63

Datavail

JUNE 8, 2023

From DBA to Data Engineer—The Strategic Role of DBAs in the Cloud Over the past few years, the IT landscape has experienced significant disruptions. Doughty also discussed how automation and cloud adoption are changing traditional DBA duties as well as providing a platform for greater efficiency and scalability.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

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.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Data 105

Data Analytics Disaster Recovery Travel 105

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Source: Apache Airflow.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). But the current data lakehouse architectural pattern is not enough.

Data 84

Data Analytics Machine Learning Artificial Inteligence 84

Altexsoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. Plus the name sounded cool for an open-source project.”.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 94

Strategy Data Technical Review Weak Development Team 94

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. Source: Allied Market Research.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

DECEMBER 14, 2022

Docker is an open-source containerization software platform: It is used to create, deploy and manage applications in virtualized containers. Launched in 2013 as an open-source project, the Docker technology made use of existing computing concepts around containers, specifically the Linux kernel with its features.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data 98

Data Storage Architecture Big Data 98

Netflix Tech

OCTOBER 18, 2022

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Meson was based on a single leader architecture with high availability.

Data 81

Data UI/UX Systems Review Software Review 81

Altexsoft

OCTOBER 8, 2021

Usually, data integration software is divided into on-premise, cloud-based, and open-source types. On-premise data integration tools. As the name suggests, these tools aim at integrating data from different on-premise source systems. Open-source data integration tools. Source: Snaplogic.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

MARCH 18, 2021

The approach is possible thanks to the modern technologies that allow for storing and processing huge volumes of data in any format. This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. Data warehousing in a nutshell.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

DECEMBER 20, 2023

We see AI applications like chatbots being built on top of closed-source or open source foundational models. Those models are trained or augmented with data from a data management platform. The data management platform, models, and end applications are powered by cloud infrastructure and/or specialized hardware.

Artificial Inteligence 70

Artificial Inteligence Artificial Intelligence Enterprise Machine Learning 70

Kentik

MARCH 7, 2023

So far in this series , I’ve outlined how a scaling enterprise’s accumulation of data (data gravity) struggles against three consistent forces: cost, performance, and reliability. As datasets scale and networks become distributed to free their data, the data gravity story begins to morph into a data complexity story.

Network 99

Network Cloud Data Case Study 99

Altexsoft

MAY 14, 2021

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

MARCH 16, 2021

In general, a data infrastructure is a system of hardware and software tools used to collect, store, transfer, prepare, analyze, and visualize data. Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Hu's Place - HitachiVantara

MARCH 18, 2019

They used a time series data base (TSDB) which is optimized for measuring change over time and makes time series data very different than other data workloads. Open-source monitoring solutions such as openTSDB lack analytics and smart alerting. This improved lead time from 2 days to less than 10 minutes.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

O'Reilly Media - Ideas

MARCH 1, 2023

Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence. growth over 2021.

Trends 136

Trends Technical Review Technology Software Review 136

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake provides computing resources scalable for different workloads.

Database Administration 64

Database Administration Strategy Data Technical Review 64