Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Scalability 92

Scalability Technical Review Data Analytics 92

Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. That is why cloud native solutions which take advantage of the capabilities such as disaggregated storage & compute, elasticity, and containerization are more paramount than ever.

Data Engineering 83

Data Engineering Performance Engineering Data 83

Mobilunity

AUGUST 3, 2021

Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer?

Big Data 52

Big Data Data Engineering Engineering Data 52

Netflix Tech

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 81

Storage Data Resources Data Engineering 81

CIO

SEPTEMBER 2, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. You’ll be required to write code, troubleshoot systems, fix bugs, and assist with the development of microservices.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. You’ll be required to write code, troubleshoot systems, fix bugs, and assist with the development of microservices.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

FEBRUARY 14, 2023

Finally, machine learning is essentially the use and development of computer systems that learn and adapt without following explicit instructions; it uses models (algorithms) to identify patterns, learn from the data, and then make data-based decisions. The storage for these features is referred to as a feature store.

Artificial Inteligence 283

Artificial Inteligence Strategy Data Machine Learning 283

CIO

FEBRUARY 13, 2023

At the same time, Seetharaman says not all legacy technology is cold, and LGA is embracing legacy systems that enable continued business growth. “We We are investing in modernizing and migrating our legacy [systems] so we can leverage the cloud-managed services,’’ he says.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

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

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. 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. Supports Disaggregation of compute and storage.

Data 100

Data Storage Architecture Big Data 100

Cloudera

FEBRUARY 1, 2024

In the fast-paced world of cloud-native products, mastering Day 2 operations is crucial for sustaining the performance and stability of Kubernetes-based platforms, such as CDP Private Cloud Data Services. Day 2 operations are akin to the housekeeping of a software system — vital for maintaining its health and stability.

Backup 82

Backup Architecture Cloud Resources 82

Cloudera

JULY 11, 2023

Along with its speed, consistency, and atomicity, Apache Kudu also supports transactional properties for updates and deletes, enabling use cases that traditionally write once and read multiple times, something distributed file systems were unable to support. Impala) and storage (i.e.

Data 70

Data Virtualization Pharmaceuticals Storage 70

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

Kentik

APRIL 12, 2023

DataOps strategies require a robust data infrastructure, including data warehouses, data lakes, caches, and other data storage and processing systems. DataOps team roles In a DataOps team, several key roles work together to ensure the data pipeline is efficient, reliable, and scalable.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 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

MARCH 18, 2021

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g ETL made its way to meet that need and became the standard data integration method.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Perficient

FEBRUARY 28, 2023

In this blog, we discuss the fifth capability : Having multiple data zones inside the Data Lake A data lake is typically defined as a centralized and scalable storage repository that holds large volumes of raw data from multiple sources and systems in its native format.

Data 110

Data Analytics Google Cloud Cloud 110

Cloudera

MAY 18, 2021

Second, since IaaS deployments replicated the on-premises HDFS storage model, they resulted in the same data replication overhead in the cloud (typical 3x), something that could have mostly been avoided by leveraging modern object store. Storage costs. using list pricing of $0.72/hour hour using a r5d.4xlarge

Cloud 85

Cloud Technical Review Storage Backup 85

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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

Altexsoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Data analysis.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Cloudera

AUGUST 30, 2022

As such, managers at different agencies need to sort through multiple systems to make sure these documents are delivered correctly—even though they all apply to the same individuals.”. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Forrester ).

Architecture 78

Architecture Data Artificial Inteligence Artificial Intelligence 78

Cloudera

SEPTEMBER 28, 2021

The Ranger Authorization Service (RAZ) is a new service added to help provide fine-grained access control (FGAC) for cloud storage. RAZ for S3 and RAZ for ADLS introduce FGAC and Audit on CDP’s access to files and directories in cloud storage making it consistent with the rest of the SDX data entities.

Groups 62

Groups Cloud AWS Data 62

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 ). The data lakehouse is not new to Cloudera or our customers.

Data 86

Data Analytics Machine Learning Artificial Inteligence 86

Kentik

MARCH 7, 2023

The transition from monitoring to observability requires access to as many system signals as possible. Have full data context. Unifying network data onto a single platform provides a single observability interface. With some regularity, one (or multiple) of their internal services inadvertently shut down the network.

Network 99

Network Cloud Data Case Study 99

Cloudera

AUGUST 26, 2020

Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information. Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform.

Data 82

Data Machine Learning Artificial Inteligence Disaster Recovery 82

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. So the cost-efficiency of the system is maximized by dedicating one or more appliances to detection and selectively pushing traffic to mitigation devices. Appliance-based systems are plagued by problems with detection accuracy. Big data to the rescue.

Scalability 40

Scalability Architecture Big Data Network 40

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. Apache Airflow providers are a set of packages allowing services to define operators in their Directed Acyclic Graphs (DAGs) to access external systems.

Off-The-Shelf 97

Off-The-Shelf Data Engineering Virtualization Cloud 97

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. It depends on the volume of incoming data.

Big Data 59

Big Data Data Google Cloud Storage 59

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. Each node has its own disk storage.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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

Altexsoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. scalability. Virtually, Hadoop puts no limits on the storage capacity.

Big Data 98

Big Data Tools Data Storage 98

Altexsoft

MARCH 14, 2023

In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support. This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. What is a modern data stack?

Data 59

Data Technical Review Software Review Artificial Inteligence 59

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. What does the high-performance data project have to do with the real Franz Kafka’s heritage?

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. 150 for storage use = $15 / TB / month x 10 TB.

Data 98

Data Technical Review Storage Systems Review 98