Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. 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

CIO

FEBRUARY 13, 2023

Now, as more faculty, staff, and students are accessing information on-premises and in the cloud, IT has a borderless network and the team is implementing a zero-trust network architecture, says CIO Mugunth Vaithylingam. These network, security, and cloud changes allow us to shift resources and spend less on-prem and more in the cloud.”

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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 90

Analytics Machine Learning Artificial Inteligence Telecommunications 90

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

Mentormate

JANUARY 11, 2022

Only the largest engineering organizations have the scale to make this kind of continuous investment. Human-Centered Design, Composable Architectures, and Citizen Builders. Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

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 103

Engineering Comparison Open Source Scalability 103

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 118

Artificial Inteligence Generative AI Security Applications 118

Capgemini

JANUARY 17, 2023

Here are four resolutions to make your data strategy pay off this year. Reassess your data architecture. Most executives (72 percent) say that data, both fragmented and with poor quality, is likely to be the biggest issue when aspiring to achieve AI goals. REASSESS YOUR DATA ARCHITECTURE.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 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. Overview of Cloudera Data Warehouse. Benchmark Description.

Performance 97

Performance Cloud Data Storage 97

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

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 98

Data Virtualization Banking Data Engineering 98

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

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

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

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

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

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

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

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 65

Cloud Data Load Balancer Storage 65

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 84

Data Scalability Analytics Quality Assurance 84

Altexsoft

SEPTEMBER 9, 2022

Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Ensure its scalability and integrability.

Tools 59

Tools Technical Review Software Review Systems Review 59

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 97

Conference Artificial Inteligence UI/UX Machine Learning 97

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. The out-of-band architecture also provides the option to utilize hybrid mitigation techniques that are tailored to specific needs and objectives. These issues are rooted in the inherent compute and storage limitations of scale-up detection architectures.

Scalability 40

Scalability Architecture Big Data Analytics 40

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.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

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. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Agile Engine

APRIL 2, 2024

Unlike other outsourcing models that spread resources across multiple clients, a dedicated team focuses solely on one project at a time. On the other hand, time and material model charges are based on actual time and resources spent, offering greater flexibility for adjustments as the project progresses.

UI/UX 52

UI/UX Development Software Development Quality Assurance 52

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

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. Airflow architecture.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

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. A Robust Security Framework.

Strategy 99

Strategy Data Technical Review Weak Development Team 99

Altexsoft

FEBRUARY 8, 2021

Planning mostly concerns demand forecasting and resource planning. This approach demands significant investments in software, equipment, and human resources to create advanced data architecture, but the resulting accuracy and visibility are worth paying for. Supply chain management process.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

APRIL 13, 2021

These steps are absolutely critical to helping you break down barriers across the ML lifecycle, so you can take ML capabilities from research to production in a scalable and repeatable manner. Your data scientists will want a platform and tools that give them practical access to data, compute resources, and libraries.

Machine Learning 98

Machine Learning Artificial Inteligence Enterprise eBook 98

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

Altexsoft

MARCH 18, 2021

This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type. Cloud data warehouses such as Snowflake, Redshift, and BigQuery also support ELT, as they separate storage and compute resources and are highly scalable.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

DECEMBER 14, 2022

The Docker engine acts as an interface between the containerized application and the host operating system. It allocates the operating system resources to the containers and ensures that the containers are isolated from one another. Docker architecture core components. Docker Architecture. Low resource consumption.

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 101

Data Storage Architecture Big Data 101

Netflix Tech

DECEMBER 21, 2020

This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture. Some of the optimizations are prerequisites for a high-performance data warehouse. More processing resources. Increase in storage space.

Storage 81

Storage Data Resources Data Engineering 81