Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

Apiumhub

JUNE 22, 2021

We are super excited to participate in the biggest and the most influential Data, AI and Advanced Analytics event in the Nordics! Data Innovation Summit ! There our Gema Parreño – Data Science expert at Apiumhub gives a talk about Alignment of Language Agents for serious video games. Data Innovation Summit topics.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Watch our video to better understand their roles. Who does what in a data science team. Machine learning engineer vs. data scientist.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Confluent

JULY 11, 2019

KSQL has a heap of terrific features, so we wanted to keep a good pace during the video lessons. Simon Aubury is a data geek on all things from databases to event streaming, architecture, IoT, and cloud. A data engineer architect from Sydney, Australia, he lives with his wife, two kids, and a grumpy cat.

Training 83

Training Course Exercises IoT 83

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. Feature engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

O'Reilly Media - Ideas

JULY 1, 2019

One area I’m particularly interested in is the application of AI and automation technologies in data science, data engineering, and software development. For a typical data scientist, data engineer, or developer, there is an explosion of tools and APIs they now need to work with and “master.”

Software Development 61

Software Development Artificial Inteligence Software Machine Learning 61

O'Reilly Media - Data

JULY 18, 2018

My goal was to remind the data community about the many interesting opportunities and challenges in data itself. Because large deep learning architectures are quite data hungry, the importance of data has grown even more. Economic value of data. Data liquidity in an age of privacy: New data exchanges.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

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. For instance: internet first created DVD-by-mail, but the real internet-native innovation was streaming video.). The great productivity inequality.

Software Engineering 304

Software Engineering Engineering Tools Software 304

UruIT

JUNE 8, 2019

Transform a system’s UX by automatically tagging uploaded images and videos. Identify specific elements in images or videos, i.e. face or object recognition, in order to streamline processes. Data Collection and Preparation. We worked in the front and back end , especially on the app’s component-oriented architecture.

Machine Learning 40

Machine Learning Artificial Inteligence Systems Review Software Review 40

High Scalability

APRIL 14, 2020

T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Essilen Research Free Video Series on Hiring. Make your job search O (1), not O ( n ).

Education 42

Education System Design Scalability Software Engineering 42

High Scalability

MAY 12, 2020

T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Essilen Research Free Video Series on Hiring. Make your job search O (1), not O ( n ).

Education 41

Education System Design Scalability Software Engineering 41

High Scalability

APRIL 28, 2020

T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Essilen Research Free Video Series on Hiring. Make your job search O (1), not O ( n ).

Education 41

Education System Design Scalability Software Engineering 41

High Scalability

MAY 26, 2020

Created by former senior-level AWS engineers of 15 years. Learn to balance architecture trade-offs and design scalable enterprise-level software. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Learn the Good Parts of AWS.

Education 40

Education System Design AWS Scalability 40

Apiumhub

AUGUST 12, 2021

An International speaker, books & video author, and writer for Java Magazine, IBM Developer, Oracle, and InfoQ. His current technical expertise focuses on integration platform implementations, Azure DevOps, and Cloud Solution Architectures. a Java Champion, An Oracle Groundbreaker Ambassador, a JCP member, 3 JSRs EG, EGJUG leader.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Kentik

AUGUST 29, 2016

Kentik CEO Avi Freedman gave an overview of our company and of our post-Hadoop Big Data engine, which ingests billions of NetFlow, sFlow, IPFIX, BGP, and SNMP data records, offers ad-hoc analyses, alerting, dashboarding, and provides open API integration.

Analytics 40

Analytics Banking Data Engineering Policies 40

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 96

Architecture Innovation Data Open Source 96

Cloudera

DECEMBER 10, 2020

Drawing on more than a decade of experience in building and deploying massive scale data platforms on economical budgets, Cloudera has designed and delivered a cost-cutting cloud-native solution – Cloudera Data Warehouse (CDW), part of the new Cloudera Data Platform (CDP). Watch this video to get an overview of CDW. .

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

AUGUST 31, 2021

It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes. Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. To learn more about CDP & the Smart Data Transition Toolkit: .

Data 80

Data Analytics Cloud Technical Review 80

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Coforge

AUGUST 31, 2020

According to a recent research by EY Insurance Consumer Research, more than 80% of customers are willing to use digital and remote contact channels (including web chat, email, mobile apps, video or phone) in place of interacting with insurers via agents or brokers.

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

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 architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Airflow architecture.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Strategy Driven

AUGUST 27, 2015

Big Data involves not just the structured data (customer name and details, products purchased, how much was spent and when, etc.) that every company is used to capturing, but also unstructured data (data scraped from the Internet and social media channels that may come in a wide variety of formats, from video to voice).

Big Data 33

Big Data Data Storage Journal 33

Altexsoft

JUNE 6, 2019

If you change your mind about that cupcake, just put it back – our technology will update your virtual cart automatically,” explains the official video. Visual search engines use artificial neural networks (ANN) – computing systems which architecture was inspired by the way human brains work.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. For this, we have a short, engaging video.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

FEBRUARY 8, 2021

Here’s also a video for an overview of demand forecasting and predictive analytics. There are two main approaches to demand planning: Traditional statistical methods make forecasts based on historical data and assume the continuation of existing trends. Develop business-specific analytics platform. A few more tips to consider.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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 Software Review 93

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

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

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

John Snow Labs

MAY 24, 2023

LabelBox LabelBox is an efficient AI Data Engine platform for AI assisted labeling, data curation, model training, and more. It annotates images, videos, text documents, audio, and HTML, etc. We can analyze multiple types of content such as text, image, audio, video, etc.

Tools 52

Tools Machine Learning Artificial Inteligence Software Review 52

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 Storage 59

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

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. Online Analytical Processing Architecture. So let’s analyze OLAP workflow in such architecture.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

DECEMBER 14, 2022

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. Docker also offers video explainers for those who prefer to listen and watch instead of reading.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Data Model. Conventional enterprise data types. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Basic Architecture for Real-Time Data Warehousing.

Data 90

Data Analytics Storage Big Data 90

CTOvision

FEBRUARY 12, 2015

Any data can be explored, from Excel spreadsheets to Hadoop big data. Here is a video that goes into detail about Tableau Desktop: Their website puts it into much better terms: Tableau Desktop is data analysis that keeps up with you. Or do both, for 2, 3, or even 10 different data sources and blend them all together.

Software 110

Software Data Analysis Big Data 110