Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

Mobilunity

AUGUST 3, 2021

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 requires a unique engineering approach. Big Data Engineer vs Data Scientist.

Big Data 52

Big Data Data Engineering Engineering Data 52

CIO

APRIL 27, 2023

The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management. Solutions architect Solutions architects are responsible for building, developing, and implementing systems architecture within an organization, ensuring that they meet business or customer needs.

Technical Review 285

Technical Review Software Review Systems Review Software Engineering 285

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

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

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. About George Trujillo: George is principal data strategist at DataStax.

Artificial Inteligence 331

Artificial Inteligence Artificial Intelligence Machine Learning Agile 331

CIO

AUGUST 2, 2023

So Thermo Fisher Scientific CIO Ryan Snyder and his colleagues have built a data layer cake based on a cascading series of discussions that allow IT and business partners to act as one team. Martha Heller: What are the business drivers behind the data architecture ecosystem you’re building at Thermo Fisher Scientific?

Data 211

Data Architecture Government Strategy 211

Cloudera

JANUARY 15, 2021

With the ability to quickly provision on-demand and the lower fixed and administrative costs, the costs of operating a cloud data warehouse are driven mostly by the price-performance of the specific data warehouse platform. CDW is one of several managed services that comprise the broader Cloudera Data Platform (CDP).

Performance 96

Performance Cloud Data Storage 96

Abhishek Tiwari

FEBRUARY 26, 2020

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup.

Architecture 81

Architecture MVC Engineering Technology 81

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

DECEMBER 6, 2018

As the use of machine learning and analytics become more widespread, we’re beginning to see tools that enable data scientists and data engineers to scale and tackle many more problems and maintain more systems. Continue reading Tools for generating deep neural networks with efficient network architectures.

Network 58

Network Architecture Tools Machine Learning 58

Perficient

MARCH 23, 2023

Databricks Streaming and Apache Flink are two popular stream processing frameworks that enable developers to build real-time data pipelines, applications and services at scale. Comparison Databricks is an integrated platform for data engineering, machine learning, data science and analytics built on top of Apache Spark.

Data 83

Data Machine Learning Artificial Inteligence Data Engineering 83

CIO

SEPTEMBER 18, 2023

IDC analyst Jason Leigh says Verizon made the right move to build a tool to facilitate customer migrations, but adds that there will be challenges whenever a CIO or C-suite move their data and traffic to new environments. Network Alpha Factory also provides data intelligence and the ability to decommission legacy devices.

Telecommunications 243

Telecommunications Network Systems Review Software Review 243

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

Confluent

JUNE 18, 2019

As soon as the number of data points involved in your search feature increases, typically we’ll introduce a broker in between all the involved components. This architectural pattern provides several benefits: Better scalability by allowing multiple data producers and consumers to run in parallel.

Scalability 96

Scalability Architecture Machine Learning Artificial Inteligence 96

Altexsoft

AUGUST 22, 2022

What’s more, Gartner identifies data fabric implementation as one of the top strategic technology trends for 2022 and expects that by 2024, data fabric deployments will increase the efficiency of data use while halving human-driven data management tasks. What is data fabric? Data fabric architecture example.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

CIO

SEPTEMBER 29, 2022

Collectively, the scope spans about 1,600 data analytics professionals in the company and we work closely with our technology partnersâ??more that cover areas of software engineering, infrastructure, cybersecurity, and architecture, for instance. But we have to bring in the right talent. more than 3,000 of themâ??that

Machine Learning 310

Machine Learning Artificial Inteligence Travel Technical Review 310

CIO

JUNE 28, 2023

The initial stage involved establishing the data architecture, which provided the ability to handle the data more effectively and systematically. “We To support this, we provided data-backed evidence and examples that demonstrated the positive impact of utilizing these technologies.”

Technical Review 215

Technical Review Analytics Innovation Artificial Intelligence 215

Altexsoft

MAY 27, 2020

But, in any case, the pipeline would provide data engineers with means of managing data for training, orchestrating models, and managing them on production. Machine learning production pipeline architecture. One of the key requirements to the ML pipeline is to have control over the models, their performance, and updates.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

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. Planning the architecture: design the system architecture, considering factors like scalability, security, and performance.

Backup 82

Backup Architecture Cloud Resources 82

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

TechCrunch

JANUARY 26, 2022

Firebolt’s pitch is that it has built a SQL-based architecture that handles this challenge better than anything that has come before it, using new techniques in compression that can connect data lakes and result in smaller cloud capacity requirements, resulting in lower costs and better performance, up to 182 times faster than that of other data (..)

Analytics 218

Analytics Data Big Data Business Intelligence 218

CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 276

Artificial Inteligence Strategy Data Machine Learning 276

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

CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. Users have freedom to slice and dice the data without technical know-how,” he says.

Analytics 336

Analytics Metrics Government Business Intelligence 336

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

Cloudera

MAY 8, 2023

Out of the box Cloudera Data platform (CDP) performs superbly but over time, if data architecture, data engineering, and DevOps best practices are not maintained, you can get stuck maintaining the wild, wild west. In this six-part series, we’re focused on improving the health of your environment.

Data Engineering 77

Data Engineering Microservices DevOps Architecture 77

Cloudera

FEBRUARY 12, 2024

Get it wrong and your deployment may become wholly unusable with users unable to access and use the Cloudera data services. If the DNS is set up less ideal than it could be, connectivity and performance issues may arise. There is at present no option to disable private DNS zones for data engineering.

Azure 52

Azure Firewall Data Engineering Storage 52

CIO

MARCH 12, 2024

Gen AI is playing a role in assisting with performing code reviews and early detection of potential issues.” Additionally, we are looking into training LLMs [large language models] on our code base to unlock further productivity boosts for our developers and data engineers. One example is with document search and summarization.

Software Development 323

Software Development Software Review Weak Development Team Software 323

Cloudera

OCTOBER 4, 2023

Every organization has some data that happens in real time, whether it is understanding what our users are doing on our websites or watching our systems and equipment as they perform mission critical tasks for us. This real-time data, when captured and analyzed in a timely manner, may deliver tremendous business value.

Analytics 89

Analytics Machine Learning Artificial Inteligence Telecommunications 89

Cloudera

APRIL 24, 2023

Unwelcome… … are platform instability, downtime, hardware failure, poor performance, cluster resource contention, repeated process failures, runaway live queries, critical services alarms, invisibility into alarm cacophony… the list goes on. Cloudera Data Platform (CDP) must be configured properly to function well with high performance.

Case Study 81

Case Study Hardware Guidelines Performance 81

Cloudera

AUGUST 3, 2022

In the coming months we will enhance this to make it even easier with minimal to no code changes in your applications, while being performant and without limiting the Spark APIs used. So, a second mode was introduced called “Direct Access,” which overcame the performance bottleneck but with one key downside – the inability to apply FGAC.

Policies 90

Policies Machine Learning Artificial Inteligence Data Engineering 90

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. The roles and duties traditionally performed by DBAs have changed as cloud adoption and automation become commonplace. Plus, we gave away an awesome LEGO NASA Space Shuttle!

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Kentik

APRIL 25, 2016

Database design for Web-scale ad hoc queries In a previous post, Beyond Hadoop , we looked at how the MapReduce approach to database design runs up against performance limits when queries can’t be defined in advance, and we introduced Google’s response to those limits: Dremel/BigQuery.

Data Engineering 40

Data Engineering Engineering Data Sport 40

Cloudera

OCTOBER 5, 2020

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. Compared to previous CPU-based architectures, CDP 7.1 with Spark 3.0

Enterprise 93

Enterprise Cloud Data Machine Learning 93

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. Success in digital business requires maximum availability and performance, which depends in turn on effective, comprehensive DDoS defense. These issues are rooted in the inherent compute and storage limitations of scale-up detection architectures. Big data to the rescue.

Scalability 40

Scalability Architecture Big Data Network 40