Erik Bernhardsson

DECEMBER 15, 2020

I had my first job as a software engineer in 1999, and in the last two decades I've seen software engineering changing in ways that have made us orders of magnitude more productive. Much like the classic No Silver Bullet paper on software productivity, none of these things in themselves were a dramatic improvement.

Software Engineering 304

Software Engineering Engineering Tools Software 304

CIO

SEPTEMBER 2, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

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 Artificial Inteligence 52

Xebia

JUNE 9, 2023

How it started out When installing software on my new MacBook Pro M2, I started out with a fresh install instead of restoring from a back-up. This worked out great until I tried to follow a tutorial written by a colleague which used the Azure Python SDK to create a dataset and upload it to an Azure storage account. Well not really.

Azure 130

Azure Architecture Software Storage 130

Altexsoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. 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?

Data 87

Data Data Engineering Big Data Architecture 87

CIO

FEBRUARY 14, 2023

Demand for real-time AI is accelerating Software applications enable businesses to fuel their processes and revolutionize the customer experience. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 284

Artificial Inteligence Strategy Data Machine Learning 284

AWS Machine Learning - AI

JULY 15, 2024

Data intake A user uploads photos into Mixbook. The raw photos are stored in Amazon Simple Storage Service (Amazon S3). The data intake process involves three macro components: Amazon Aurora MySQL-Compatible Edition , Amazon S3, and AWS Fargate for Amazon ECS. AWS enables us to scale the innovations our customers love most.

Generative AI 103

Generative AI Artificial Inteligence AWS Technical Review 103

TechCrunch

MAY 18, 2022

We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data. ” Software developers Malyuk, Maxim Tkachenko, and Nikolay Lyubimov co-founded Heartex in 2019. Who can provide the best results other than your own experts?”

Open Source 203

Open Source Weak Development Team Data Artificial Inteligence 203

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. Here we’ll look at the common architecture and the flow of such a system.

Artificial Inteligence 89

Artificial Inteligence Machine Learning Architecture Training 89

Cloudera

AUGUST 22, 2024

Established in 2014, this center has become a cornerstone of Cloudera’s global strategy, playing a pivotal role in driving the company’s three growth pillars: accelerating enterprise AI, delivering a truly hybrid platform, and enabling modern data architectures.

Innovation 70

Innovation Machine Learning Artificial Inteligence Technical Review 70

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 85

Backup Cloud Architecture Resources 85

AWS Machine Learning - AI

JUNE 21, 2024

Over 100 SOC analysts are now using AI Investigator models to analyze security data and provide rapid investigation conclusions. Solution overview eSentire customers expect rigorous security and privacy controls for their sensitive data, which requires an architecture that doesn’t share data with external large language model (LLM) providers.

Artificial Inteligence 102

Artificial Inteligence Generative AI AWS Serverless 102

Cloudera

DECEMBER 10, 2020

Generally, if five LOB users use the data warehouse on a public cloud for eight hours a day for one month, you pay for the use of the service and the associated cloud hardware resources (compute and storage) for this period. 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

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 126

Artificial Inteligence Generative AI Security Applications 126

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Altexsoft

APRIL 13, 2023

Obviously, it’s all about collecting data from various sources, both external and internal which is possible with specialized technologies. Supply chain visibility software Supply chain visibility software enables real-time tracking of goods and materials throughout the entire supply chain.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

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. Storage provisioning.

Big Data 63

Big Data Data Storage Microservices 63

KitelyTech

FEBRUARY 3, 2021

Data collection tools allow computer programmers to analyze large amounts of data sets obtained from various sources such as databases, spreadsheets and websites. It is a great help in making the software development process faster and easier. . Therefore, the software must have an easily extendable architecture.

Big Data 52

Big Data Data Development Business Intelligence 52

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. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks.

Tools 59

Tools Technical Review Software Review Systems Review 59

Cloudera

SEPTEMBER 1, 2020

By encapsulating Kerberos, it eliminates the need for client software or client configuration, simplifying the access model. The CrunchIndexerTool can use Spark to read data from HDFS files into Apache Solr for indexing, and run the data through a so-called morphline for extraction and transformation in an efficient way.

Data 71

Data Backup Disaster Recovery Storage 71

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

Hu's Place - HitachiVantara

JANUARY 3, 2019

Data curation will be a focus to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need to power the organization.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

RapidValue

JULY 21, 2019

From DevOps to DataOps DataOps can be simply stated as “DevOps for data”. It is a set of practices and technologies that integrate the development and operation of data movement architectures into a continuous process. DataOps aids data practitioners to continuously deliver quality data to applications and business processes.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

Abhishek Tiwari

JULY 12, 2018

Lastly, we will talk about the internal platform and product divide – one key reason why data pipeline initiatives typically fail – and why it is better working backward from the product. Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. A data pipeline is a software which runs on hardware.

Data 63

Data Software Review Technical Review Microservices 63

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

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? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

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 Architecture 115

Altexsoft

OCTOBER 24, 2019

Similar to humans companies generate and collect tons of data about the past. And this data can be used to support decision making. 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. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

FEBRUARY 22, 2022

We’ll talk about the general approach and how software can help you as a fleet manager or owner to cope with your maintenance activities and avoid those costly unplanned repairs. Data is gathered from connected sensors and analyzed so that predictions of possible failures can be generated. Fleet maintenance software features.

Software Review 52

Software Review Technical Review Software Technology 52

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

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Unstructured data is very different.

Big Data 33

Big Data Data Storage Journal 33

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 86

Data Scalability Analytics Quality Assurance 86

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. But AI is going to bring changes to almost every aspect of the software industry. This has been a strange year. What does this mean?

Trends 111

Trends Technical Review Technology Artificial Inteligence 111