Perficient

FEBRUARY 13, 2025

Breaking down silos has been a drumbeat of data professionals since Hadoop, but this SAP <-> Databricks initiative may help to solve one of the more intractable data engineering problems out there. SAP has a large, critical data footprint in many large enterprises. However, SAP has an opaque data model.

Government 64

Government Open Source Machine Learning Artificial Inteligence 64

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

Altexsoft

APRIL 22, 2020

quintillion bytes of data generated daily, data scientists get busier than ever. And data science provides us with methods to make use of this data. So while you search for a definition of “quintillion”, Google probably learns that you have this knowledge gap. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Xebia

FEBRUARY 3, 2023

You start out really small, perhaps a Proof of Concept, a small app or data engineering pipeline. Point 1 you most likely cannot learn from a blog post, but point 2 is definitively something we can tackle here. Architecture rules are defined in simple Pytest test cases and can run as part of a CI/CD pipeline.

How To 130

How To Architecture Data Engineering Applications 130

AWS Machine Learning - AI

MARCH 13, 2025

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

Artificial Inteligence 96

Artificial Inteligence Systems Review System Generative AI 96

CIO

AUGUST 5, 2022

Data visualization definition. Data visualization is the presentation of data in a graphical format such as a plot, graph, or map to make it easier for decision makers to see and understand trends, outliers, and patterns in data. Maps and charts were among the earliest forms of data visualization.

Data 214

Data Analytics Travel Business Intelligence 214

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. A dedicated team of data scientists or people with a business domain would define the data that will be used for training.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

Netflix Tech

FEBRUARY 14, 2025

Architecture Overview The first pivotal step in managing impressions begins with the creation of a Source-of-Truth (SOT) dataset. This refined output is then structured using an Avro schema, establishing a definitive source of truth for Netflixs impression data.

Systems Review 66

Systems Review Technical Review Data Metrics 66

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 174

Artificial Inteligence Strategy Data Machine Learning 174

Altexsoft

AUGUST 21, 2019

Data obsession is all the rage today, as all businesses struggle to get data. But, unlike oil, data itself costs nothing, unless you can make sense of it. Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data.

Development 44

Development Software Engineering Data Engineering Architecture 44

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 Architecture 115

Apiumhub

APRIL 1, 2021

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning, and much more. Top Data science books you should definitely read.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

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

AWS Machine Learning - AI

MARCH 18, 2025

Streamlit This open source Python library makes it straightforward to create and share beautiful, custom web apps for ML and data science. In just a few minutes you can build powerful data apps using only Python. The following diagram shows the solution architecture. About the Author Rajendra Choudhary is a Sr.

Artificial Inteligence 92

Artificial Inteligence Applications Generative AI Off-The-Shelf 92

Netflix Tech

SEPTEMBER 10, 2019

Our data scientists often want to apply their knowledge of the business and statistics to fully understand the outcome of an experiment. Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute.

Analysis 88

Analysis Metrics Software Review Testing 88

TIBCO - Connected Intelligence

AUGUST 10, 2020

Your data demands, like your data itself, are outpacing your data engineering methods and teams. You’ll discover that they all have identified data virtualization as a must-have addition to your data integration tooling and a critical enabler to a more modern, distributed data architecture.

Virtualization 69

Virtualization Data How To Data Engineering 69

OpenCredo

JULY 13, 2018

The Power of the Architecture-driven Organisation. Engineers in an agile development team generally do not have much control over this scenario, but as a consultant it is something I would definitely want to highlight in order to give Project Positron the best chance of success in its organisation. – Melvin Conway.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Learning stuff is what matters and kind of by definition you have to do stupid s**t before you learned it. What do you wish you knew earlier about being a data scientist? I don’t consider myself a data scientist so not sure :).

Data 101

Data Big Data Machine Learning Artificial Inteligence 101

Netflix Tech

OCTOBER 18, 2022

Meson was based on a single leader architecture with high availability. We want users to rely on shared templates and reuse their workflow definitions across their team, saving time and effort on creating the same functionality. Figure 1 shows the high-level architecture. With the high growth of workflows in the past few years?

Data 84

Data UI/UX Systems Review Software Review 84

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Learning stuff is what matters and kind of by definition you have to do stupid s**t before you learned it. What do you wish you knew earlier about being a data scientist? I don’t consider myself a data scientist so not sure :).

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Cloudera

JULY 27, 2021

While billing used to be one of two critical things for any successful telco (the other being the network), today’s digital service providers prioritise channels, ecosystems, payments and cloud service architectures in enterprise architecture. Edge analytics by definition require in-network deployment.

Telecommunications 64

Telecommunications Data Architecture Big Data 64

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 90

Infrastructure Data Technical Review Systems Review 90

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. Who wants to learn about design patterns or software architecture when some AI application may eventually do your high-level design?

Trends 142

Trends Technical Review Technology Artificial Inteligence 142

Kentik

APRIL 4, 2023

Highly available networks are resistant to failures or interruptions that lead to downtime and can be achieved via various strategies, including redundancy, savvy configuration, and architectural services like load balancing. Resiliency. Resilient networks can handle attacks, dropped connections, and interrupted workflows.

Network 104

Network Load Balancer Cloud Backup 104

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

ChatGPT 64

ChatGPT Education Data Comparison 64

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

O'Reilly Media - Ideas

MARCH 18, 2020

One-sixth of respondents identify as data scientists, but executives—i.e., The survey does have a data-laden tilt, however: almost 30% of respondents identify as data scientists, data engineers, AIOps engineers, or as people who manage them. All told, more than 70% of respondents work in technology roles.

Enterprise 139

Enterprise Survey Technical Review Weak Development Team 139

Xebia

OCTOBER 23, 2024

Adhering to the don’t repeat yourself (DRY) principle, we say: similar datastore -> similar ingestion pipeline KISS (Keep It Simple, Stupid) KISS is a design and development principle that advocates for simplicity in software design, architecture, and implementation. Imagine the benefits when there are hundreds of tables!

Azure 130

Azure Software Review Technical Review Resources 130

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

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

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.

Big Data 63

Big Data Data Storage Microservices 63

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 69

Virtualization Tools Data Architecture 69

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 59

Big Data Data Google Cloud Open Source 59

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

Altexsoft

APRIL 26, 2022

We’ll dive deeper into Snowflake’s pros and cons, its unique architecture, and its features to help you decide whether this data warehouse is the right choice for your company. Data warehousing in a nutshell. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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. We store the MSE and N for each partition in Redis for later use.

Storage 84

Storage Data Resources Data Engineering 84