CIO

SEPTEMBER 18, 2023

Inside the ‘factory’ Aside from its core role as a migration platform, Network Alpha Factory also delivers network scalability and a bird’s-eye view of an enterprise’s entire network landscape, including where upgrades may be needed. Private 5G, Robotic Process Automation, Telecommunications, Telecommunications Industry

Telecommunications 278

Telecommunications Network Systems Review Software Review 278

InnovationM

APRIL 25, 2024

Engineered to harness the power of GPU and CPU resources within Pods, it offers a seamless blend of efficiency and flexibility through serverless computing options. Setup Environment: Ensure that your RunPod environment is properly set up with the necessary dependencies and resources to run the LLM. How to approach it?

Artificial Inteligence 52

Artificial Inteligence Serverless Scalability Resources 52

Cloudera

FEBRUARY 1, 2024

Day 0 — Design and Preparation: Focuses on designing and preparing for your installation, including gathering requirements, planning architecture, allocating resources, setting up network and security, and documentation creation. Resource allocation: determine the hardware and cloud resources required for the installation.

Backup 81

Backup Architecture Cloud Resources 81

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. What will be the cost of rolling out the winning cell of an AB test to all users?

Infrastructure 73

Infrastructure Scalability Cloud Data 73

CIO

FEBRUARY 13, 2023

These network, security, and cloud changes allow us to shift resources and spend less on-prem and more in the cloud.” That also requires investing more in cloud infrastructure for storage and compute power resources so data scientists can process data, understand it, and be able to translate it “for benefits at the bedside,’’ Fleischut says.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

DataRobot

JUNE 1, 2022

Through a series of virtual keynotes, technical sessions, and educational resources, learn about innovations for the next decade of AI, helping you deliver projects that generate the most powerful business results while ensuring your AI solutions are enterprise ready—secure, governed, scalable, and trusted.

Virtualization 119

Virtualization Artificial Inteligence Machine Learning Artificial Intelligence 119

CIO

JULY 18, 2023

“If we’re looking to build, train, and run models at scale to run in parallel to each of our products, we need talent who can help us unbundle the data by refactoring apps and data, and building a scalable data fabric that is flexible to feed to a generative AI platform,” says Kocherlakota, who is seeking AI experience and generative AI knowledge.

Technical Advisors 246

Technical Advisors Artificial Inteligence Generative AI How To 246

Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision.

Analytics 84

Analytics Machine Learning Artificial Inteligence Telecommunications 84

Mentormate

JANUARY 11, 2022

Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration. The Rise of Data. The most common impediment to the composable architecture and citizen builder trend is accessing the data itself.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

TechCrunch

OCTOBER 7, 2021

If your customers are data engineers, it probably won’t make sense to discuss front-end web technologies. EveryDeveloper focuses on content, which I believe is the most scalable way to reach developers. The educational and inspirational content you use to attract developers will depend on who is the best fit for your product.

Weak Development Team 231

Weak Development Team Software Development Marketing Technical Advisors 231

Cloudera

MAY 13, 2021

Importing data from one or multiple systems to apply transformations and then export results to another system is becoming increasingly common—which means these kinds of activities must become more automated and easily repetitive. When evaluating a stream processing engine, consider its processing abstraction capabilities.

Engineering 101

Engineering Comparison Open Source Scalability 101

Cloudera

FEBRUARY 16, 2021

Cloudera Operational Database (COD) plays the crucial role of a data store in the enterprise data lifecycle. You can use COD with: Cloudera DataFlow to ingest and aggregate data from various sources. Cloudera Data Engineering to ingest bulk data and data from mainframes. Cloudera Data Engineering.

Machine Learning 82

Machine Learning Artificial Inteligence Data Engineering Policies 82

Netflix Tech

MARCH 7, 2024

In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. Occasionally, these use cases involve terabytes of data, so we have to pay attention to performance. Internally, we use a production workflow orchestrator called Maestro.

System 90

System Machine Learning Artificial Inteligence Training 90

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Xebia

MARCH 10, 2021

For example: – New libraries can be installed as required; – Multiple versions of software packages can be used; – All cloud services can be used on personal basis; – No limits regarding resources. Data & Analytics adopting DevOps principles. The production environment has a predefined configuration.

DevOps 130

DevOps Data Analytics Policies 130

Cloudera

DECEMBER 21, 2020

Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist. The Data Engineer.

Data 97

Data Virtualization Banking Data Engineering 97

Exadel

FEBRUARY 20, 2023

Vertex AI leverages a combination of data engineering, data science, and ML engineering workflows with a rich set of tools for collaborative teams.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Apps Associates

JULY 28, 2022

Fully Control Scalability Dynamically. Data Lakehouse based implementations. Leverage data for AI/ML Data Science/ Big Data use cases. Verify the resource details and click “ Create” to create the VCN. ODI Marketplace is preferred in cases of: You don’t want to maintain local infrastructure.

Infrastructure 52

Infrastructure Cloud Data Linux 52

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

Continuous resource consumption in the cloud (billable on-demand by a running clock) makes no sense today because a better option is available: resource consumption that starts when you need it and stops when you don’t. Therefore, optimizing the performance of the cloud-native data warehouse saves time and money.

Data 98

Data Technical Review Storage Systems Review 98

Capgemini

JANUARY 17, 2023

By creating a lakehouse, a company gives every employee the ability to access and employ data and artificial intelligence to make better business decisions. Many organizations that implement a lakehouse as their key data strategy are seeing lightning-speed data insights with horizontally scalable data-engineering pipelines.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

KitelyTech

FEBRUARY 3, 2021

Database management is what your database administrator uses to store, organize, and access computer data. It often includes three main components like the database schema, database application, and data engine. Database management systems must be flexible enough to handle large amounts of data in a short period of time.

Big Data 52

Big Data Data Development Business Intelligence 52

Cloudera

JANUARY 15, 2021

Cloudera Data Warehouse is a highly scalable service that marries the SQL engine technologies of Apache Impala and Apache Hive with cloud-native features to deliver best-in-class price-performance for users running data warehousing workloads in the cloud.

Performance 91

Performance Cloud Data Storage 91

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 325

Analytics Data Engineering Machine Learning Artificial Inteligence 325

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

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

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

AWS Machine Learning - AI

JANUARY 26, 2024

To simplify implementation of security and privacy best practices, consider using reference designs and infrastructure as code resources such as the AWS Security Reference Architecture (AWS SRA) and the AWS Privacy Reference Architecture (AWS PRA). There are many other AWS Security training and certification resources available.

Artificial Inteligence 117

Artificial Inteligence Generative AI Security Applications 117

TechCrunch

MARCH 7, 2023

The barrier to success for these projects often resides in the time and resources it takes to get them into development and then into production. With little understanding of the engineering environment, the first logical step should be hiring data scientists to map and plan the challenges that the team may face.

Weak Development Team 246

Weak Development Team ChatGPT Case Study Data Engineering 246

Altexsoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

TechCrunch

NOVEMBER 4, 2022

I know this because I used to be a data engineer and built extract-transform-load (ETL) data pipelines for this type of offer optimization. Part of my job involved unpacking encrypted data feeds, removing rows or columns that had missing data, and mapping the fields to our internal data models.

Data 218

Data Storage Analytics Data Engineering 218

Kentik

JANUARY 3, 2018

Return query results against all this data in seconds. Appliance-based network management solutions are too resource-constrained to handle the vast volume of data generated by IoT infrastructure. This leads us to a big data approach to capture and report on this unstructured IoT data.

IoT 40

IoT Network Tools Big Data 40

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 79

Data Scalability Analytics Quality Assurance 79

Cloudera

APRIL 26, 2023

It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment. The platform offers advanced capabilities for data warehousing (DW), data engineering (DE), and machine learning (ML), with built-in data protection, security, and governance.

Cloud 63

Cloud Data Load Balancer Storage 63

CIO

JUNE 14, 2023

Going from petabytes (PB) to exabytes (EB) of data is no small feat, requiring significant investments in hardware, software, and human resources. This can be achieved by utilizing dense storage nodes and implementing fault tolerance and resiliency measures for managing such a large amount of data. Focus on scalability.

Data 162

Data Scalability Storage Big Data 162

Altexsoft

SEPTEMBER 9, 2022

Or you might want to add certain tags or keywords to your data assets to facilitate search (especially for business users). In this case, additional metadata is created (again, either manually or automatically) and linked to digital resources. Ensure its scalability and integrability. Metadata quality assurance.

Tools 59

Tools Technical Review Software Review Systems Review 59

CIO

JULY 15, 2022

I am a firm believer in in-house resources. When you think about what skill sets do you need, it’s a broad spectrum: data engineering, data storage, scientific experience, data science, front-end web development, devops, operational experience, and cloud experience.”. “I

Systems Review 279

Systems Review Fractional CTO System Development Team Review 279