Architecture, Data Engineering, Definition and Scalability

Fundamentals of Data Engineering

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

Data Engineering

Data Engineering Engineering Data Technical Review

Unlocking the Power of AI with a Real-Time Data Strategy

CIO

FEBRUARY 14, 2023

Here, I’ll focus on why these three elements and capabilities are fundamental building blocks of a data ecosystem that can support real-time AI. DataStax Real-time data and decisioning First, a few quick definitions. Real-time data involves a continuous flow of data in motion.

Artificial Inteligence

Artificial Inteligence Strategy Data Machine Learning

DataOps Gives You an Advantage—We Know Because We do it Ourselves

Hu's Place - HitachiVantara

JUNE 5, 2019

This was a major accomplishment due to the lack of documentation, legacy tribal knowledge, lack of awareness of the differences between operational and analytic reporting, multiple definitions from different domains, lack of basic data discipline, and whole new technology stacks for volume and scale processing.

Technical Review

Technical Review Analytics Data Engineering Scalability

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

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

Artificial Inteligence Generative AI Security Applications

Big Data Engineer: Role, Responsibilities, and Job Description

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

Big Data Data Engineering Engineering Data

Kubernetes for Big Data Workloads

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

Big Data Data Storage Microservices

Kentik Detect for FinServ Networks: Real-World Use Cases

Kentik

APRIL 3, 2018

Networking teams no longer need to be limited by unresponsive tools, aggregated stats, and data deadends. 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?”

Network

Network WAN LAN Policies

Metadata Management: Process, Tools, Use Cases, and Best Practices

Altexsoft

SEPTEMBER 9, 2022

Definitely, there are many more metadata types distinguished according to different criteria. Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. It also documents the relationship between assets. Such policies outline.

Tools

Tools Technical Review Software Review Systems Review

Altexsoft - Untitled Article

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

Backup Azure Software Review Systems Review

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

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. Meson was based on a single leader architecture with high availability.

Data

Data UI/UX Systems Review Software Review

The Good and the Bad of Snowflake Data Warehouse

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

Weak Development Team Data Storage Technical Review

The Good and the Bad of Apache Kafka Streaming Platform

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. Kafka architecture. Kafka cluster architecture. Scalability.

Weak Development Team

Weak Development Team Technical Review Systems Review Software Review

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

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

Infrastructure Data Technical Review Systems Review

The Good and the Bad of Hadoop Big Data Framework

Altexsoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Big Data

Big Data Data Google Cloud Storage

The Good and the Bad of Docker Containers

Altexsoft

DECEMBER 14, 2022

While you definitely saw the Docker vs Kubernetes comparison, these two systems cannot be compared directly. Docker architecture core components. Docker Architecture. Docker uses a client-server architecture where the Docker client communicates with the Docker daemon via a RESTful API, UNIX sockets, or a network interface.

Weak Development Team

Weak Development Team Linux Operating System Virtualization

Data Collection for Machine Learning: Steps, Methods, and Best Practices

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

Machine Learning Artificial Inteligence Data Systems Review

Big Data in Healthcare: Sources and Real-World Applications

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

Big Data Healthcare Applications Data

Optimizing data warehouse storage

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. Other Components Iceberg We use Apache Iceberg as the table format.

Storage

Storage Data Resources Data Engineering

Data Virtualization: Process, Components, Benefits, and Available Tools

Altexsoft

NOVEMBER 23, 2021

To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization. This post is a perfect place to learn about this approach, its architecture components, differences, benefits, tools, and more. What is data virtualization?

Virtualization

Virtualization Tools Data Architecture

Health Information Management: Concepts, Processes, and Technologies Used

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. Amazon also possesses tools to build HIPAA-compliant architecture with AWS services.

Technical Review

Technical Review Technology Software Review Healthcare

Rethinking Data Marts in the Cloud

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. 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. Architecture patterns for the cloud.

Cloud

Cloud Data Storage Analytics

The Good and the Bad of Databricks Lakehouse Platform

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

Weak Development Team Machine Learning Artificial Inteligence Software Review

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Altexsoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? Cloud-first.

Data

Data Technical Review Software Review Artificial Inteligence

CTO Universe

Fundamentals of Data Engineering

Unlocking the Power of AI with a Real-Time Data Strategy

Trending Sources

DataOps Gives You an Advantage—We Know Because We do it Ourselves

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Big Data Engineer: Role, Responsibilities, and Job Description

Kubernetes for Big Data Workloads

Kentik Detect for FinServ Networks: Real-World Use Cases

Metadata Management: Process, Tools, Use Cases, and Best Practices

Altexsoft - Untitled Article

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Good and the Bad of Snowflake Data Warehouse

The Good and the Bad of Apache Kafka Streaming Platform

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Good and the Bad of Hadoop Big Data Framework

The Good and the Bad of Docker Containers

Data Collection for Machine Learning: Steps, Methods, and Best Practices

Big Data in Healthcare: Sources and Real-World Applications

Optimizing data warehouse storage

Data Virtualization: Process, Components, Benefits, and Available Tools

Health Information Management: Concepts, Processes, and Technologies Used

Rethinking Data Marts in the Cloud

The Good and the Bad of Databricks Lakehouse Platform

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

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