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. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 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

Cloudera

FEBRUARY 1, 2024

The other half of the equation requires your team’s emphasis to shift to sustained excellence in managing and optimizing your data ecosystem — better known as Day 2 operations. In this blog, we’ll cover the highlights of our recently published Day 2 Operations Guide and why it matters to enterprises.

Backup 81

Backup Cloud Architecture Resources 81

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 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

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

CDW includes two highly scalable and performant Apache open-source engines – Impala and Hive LLAP – that have proven themselves in hundreds of enterprises for business-critical data warehousing. 150 for storage use = $15 / TB / month x 10 TB. 150 for storage use = $15 / TB / month x 10 TB.

Data 98

Data Technical Review Storage Systems Review 98

d2iq

FEBRUARY 19, 2021

Except in many enterprises. There is a lot more to machine learning in the enterprise than just the model, which is what many people think of when they hear artificial intelligence. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model. AI is everywhere.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Existek

JANUARY 11, 2022

And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

AWS Machine Learning - AI

JANUARY 26, 2024

Reviews can be performed using tools like the AWS Well-Architected Tool , or with the help of your AWS team through AWS Enterprise Support. Protect all data in transit between services using AWS Certificate Manager and/or AWS Private CA , and keep it within VPCs using AWS PrivateLink.

Artificial Inteligence 118

Artificial Inteligence Generative AI Security Applications 118

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Metadata storage usually implies developing a specialized repository. Metadata storage. What is metadata management?

Tools 59

Tools Technical Review Software Review Systems Review 59

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

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action. into the digital twin.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

TechCrunch

NOVEMBER 4, 2022

Ashish Kakran , principal at Thomvest Ventures , is a product manager/engineer turned investor who enjoys supporting founders with a balance of technical know-how, customer insights, empathy with challenges and market knowledge. Here’s where MLOps is accelerating enterprise AI adoption. More posts by this contributor.

Data 218

Data Storage Analytics Data Engineering 218

CIO

JUNE 14, 2023

Start with storage. Before you can even think about analyzing exabytes worth of data, ensure you have the infrastructure to store more than 1000 petabytes! Going from 250 PB to even a single exabyte means multiplying storage capabilities four times. Focus on scalability. So, how do we achieve scalability?

Data 159

Data Scalability Storage Big Data 159

Cloudera

NOVEMBER 28, 2023

Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 78

Data Scalability Analytics Quality Assurance 78

Cloudera

APRIL 26, 2023

At its core, CDP Private Cloud Data Services (“the platform”) is an end-to-end cloud native platform that provides a private open data lakehouse. It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment.

Cloud 63

Cloud Data Load Balancer Storage 63

Cloudera

MARCH 23, 2022

Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. By being a truly open table format, Apache Iceberg fits well within the vision of the Cloudera Data Platform (CDP). 1: Multi-function analytics .

Data 88

Data Open Source Storage Machine Learning 88

CIO

JULY 15, 2022

The forecasting systems DTN had acquired were developed by different companies, on different technology stacks, with different storage, alerting systems, and visualization layers. Working with his new colleagues, he quickly identified rebuilding those five systems around a single forecast engine as a top priority. The merger playbook.

Systems Review 276

Systems Review Fractional CTO System Development Team Review 276

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

OCTOBER 24, 2019

While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

Cloudera

FEBRUARY 22, 2022

This unprecedented level of big data workloads hasn’t come without its fair share of challenges. The data architecture layer is one such area where growing datasets have pushed the limits of scalability and performance. Apache Iceberg is a new open table format targeted for petabyte-scale analytic datasets.

Data 103

Data Analytics Disaster Recovery Travel 103

Cloudera

SEPTEMBER 28, 2021

Cloudera Data platform ( CDP ) provides a Shared Data Experience ( SDX ) for centralized data access control and audit in the Enterprise Data Cloud. The Ranger Authorization Service (RAZ) is a new service added to help provide fine-grained access control (FGAC) for cloud storage.

Groups 61

Groups Cloud AWS Data 61

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

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. Performance and scalability. Read why the future of data lakehouses is open.

Cloud 76

Cloud Data Analytics Machine Learning 76

ParkMyCloud

JANUARY 17, 2020

Individuals in an associate solutions architect role have 1+ years of experience designing available, fault-tolerant, scalable, and most importantly cost-efficient, distributed systems on AWS. Must prove knowledge of deploying, operating and managing highly available, scalable and fault-tolerant systems on AWS. Azure Fundamentals.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Cloudera

AUGUST 30, 2022

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . Towards Data Science ). Forrester ).

Architecture 75

Architecture Data Artificial Inteligence Artificial Intelligence 75

Altexsoft

MARCH 18, 2021

The primary difference resides in WHERE and WHEN data transformation and loading happens. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g The data flow of both ETL and ELT relies on three core stages. Just like with extraction, data can be loaded either fully or partially.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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

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. Data Generation at Scale.

Data 98

Data Storage Architecture Big Data 98

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 ).

Data 83

Data Analytics Machine Learning Artificial Inteligence 83

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. CRMs, OLAP/OLTP databases, enterprise applications, etc.)

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Kentik

MAY 31, 2023

Reliability is a massive burden for network operators While DevOps teams and their SREs focus on the reliability of the application environment, an enterprise’s network concerns often extend well beyond the uptime of a suite of customer-facing web and mobile apps.

Network 52

Network Cloud Load Balancer Firewall 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

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. Introduction.

Strategy 94

Strategy Data Technical Review Weak Development Team 94

Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Data Model. Conventional enterprise data types. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Basic Architecture for Real-Time Data Warehousing. Tech Preview).

Data 90

Data Analytics Storage Big Data 90