Kentik

APRIL 3, 2018

Getting that data has historically been a huge challenge. Traditional tooling is often not deployed where and when the problems occur, and doesn’t retain the details necessary to definitively answer the “was it the network?” Kentik Detect solves both those problems.

Network 40

Network WAN LAN Policies 40

The Citus Data

MARCH 31, 2023

on-demand talk, Citus open source user) 6 Citus engineering talks Citus & Patroni: The Key to Scalable and Fault-Tolerant PostgreSQL , by Alexander Kukushkin who is a principal engineer at Microsoft and lead engineer for Patroni. I will definitely be there as a co-host, along with Pino de Candia. (If

Azure 84

Azure Open Source Virtualization Software Engineering 84

Altexsoft

SEPTEMBER 9, 2022

Definitely, there are many more metadata types distinguished according to different criteria. A metadata policy is a business document that has to be created to guide all metadata management activities and define the key data principles. Alation supports active metadata management with its Data Governance App and Data Catalog tools.

Tools 59

Tools Technical Review Software Review Systems Review 59

AWS Machine Learning - AI

JANUARY 26, 2024

Organizational resiliency draws on and extends the definition of resiliency in the AWS Well-Architected Framework to include and prepare for the ability of an organization to recover from disruptions. Ram Vittal is a Principal ML Solutions Architect at AWS.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Netflix Tech

OCTOBER 18, 2022

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Another dimension of scalability to consider is the size of the workflow.

Data 81

Data UI/UX Systems Review Software Review 81

Netflix Tech

JUNE 6, 2022

Our goal is to manage security risks to Netflix via clear, opinionated security guidance, and by providing risk context to Netflix engineering teams to make pragmatic risk decisions at scale. We’ve also discovered, through interviews with engineers, that self-service guidance doesn’t stand on its own.

Software Review 67

Software Review Software Engineering Scalability Engineering 67

Altexsoft

JANUARY 14, 2021

The variety of data explodes and on-premises options fail to handle it. Apart from the lack of scalability and flexibility offered by modern databases, the traditional ones are costly to implement and maintain. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources.

Backup 115

Backup Azure Software Review Systems Review 115

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 87

Infrastructure Data Technical Review Systems Review 87

Altexsoft

JULY 29, 2022

What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? Under the hood, the framework divides a chunk of Big Data into smaller, digestible parts and allocates them across multiple commodity machines to be processed in parallel. Scalability. Definitely, not.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. All data goes through the middleman — in our case, Kafka — that manages messages and ensures their security.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Netflix Tech

DECEMBER 21, 2020

Some of the optimizations are prerequisites for a high-performance data warehouse. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster. Other Components Iceberg We use Apache Iceberg as the table format.

Storage 81

Storage Data Resources Data Engineering 81

Altexsoft

DECEMBER 14, 2022

While you definitely saw the Docker vs Kubernetes comparison, these two systems cannot be compared directly. Scalability. Containers are highly scalable and can be expanded relatively easily. While Docker is definitely one of a kind, there are several container alternatives out there that may be worth your attention.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes. How systems exchange data.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

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. Great performance and scalability. Connectors.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. Definitely, the topic is way too extensive to be covered in a blog post, so we’re only going to make a succinct overview. What is Big Data and its sources in healthcare?

Big Data 116

Big Data Healthcare Applications Data 116

Apiumhub

AUGUST 29, 2019

Also, after this event, we had a meeting with our Principal Engineer and software development team to discuss this topic as we noticed that in each company it is slightly different. So, in this article, you will find common patterns as well as our definition of Principal Engineer based on our experience.

Engineering 32

Engineering Part-Time VPE Software Engineering Engineering Culture 32

Altexsoft

NOVEMBER 5, 2021

If you’re not familiar with the technological side of data exchange, read the following articles to connect dots: What is EDI: The Main Document Exchange Technology. What is API: Definition, Types, Specifications, Documentation. REST API: Key Concepts, Best Practices, and Benefits. Main Healthcare APIs.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering.

Virtualization 69

Virtualization Tools Data Architecture 69

Altexsoft

SEPTEMBER 23, 2019

When drafting this type of documentation, a business analyst includes the system’s quality attributes, such as usability, security, reliability, performance, availability, and scalability. These are the product features that engineers implement to allow users to achieve their goals. Preparing functional requirements.

Weak Development Team 62

Weak Development Team Software Development Research Project Management 62

O'Reilly Media - Data

MARCH 22, 2018

Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in the algorithmic decision-making (for a more detailed explanation on the definition of transparency in machine learning, see “ Challenges of Transparency ” by Adrian Weller).

Off-The-Shelf 117

Off-The-Shelf Machine Learning Artificial Inteligence Weak Development Team 117

Cloudera

DECEMBER 12, 2018

Yet, there were some limitations in MPP at the time, because some of these systems running Hive were quite large, and the database community thought that instead of the future being Hive on MapReduce or something similar, that we could extend, bend, and change the MPP engines to actually operate in a more scalable manner on such large data.

Data 42

Data Marketing Storage Big Data 42

Cloudera

OCTOBER 26, 2017

Business intelligence (BI) and analytics in the cloud is an area that has gained the attention of many organizations looking to provide a better user experience for their data analysts and engineers. The reason frequently cited for the consideration of BI in the cloud is that it provides flexibility and scalability.

Cloud 43

Cloud Data Storage Analytics 43

Altexsoft

MARCH 30, 2023

Shell, Adobe, Burberry, Columbia, Bayer — you definitely know the names. The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

MARCH 14, 2023

In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support. This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. What is a modern data stack?

Data 59

Data Technical Review Software Review Artificial Inteligence 59