Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

O'Reilly Media - Ideas

MAY 1, 2019

Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20.

Course 46

Course Training Artificial Inteligence Machine Learning 46

OpenCredo

JULY 13, 2018

The Power of the Architecture-driven Organisation. Project Datatron: Architecture-driven Collaboration. This isn’t the only organisational problem an engineering consultant may encounter. At first it looked like a fairly straightforward data engineering problem. The answer, of course, is that it depends.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40

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. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Confluent

JULY 11, 2019

To inspire and help developers embrace this fantastic event streaming technology, Stéphane Maarek and I authored a new KSQL course. For a KSQL newbie the practical exercises show you how to process data in Apache Kafka using an interactive SQL interface. Either way, we are thrilled to be able to offer the course for USD $9.99

Training 83

Training Course Exercises IoT 83

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data 89

Data Analytics Open Source Architecture 89

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Data Innovation Summit is here to help you hear cutting-edge content, meet and engage with peers and find solutions to your most pressing challenges. Focus on Data-Ops, ML Ops, Auto ML, Cloud ML, Fast Data, data pipeline, data lineage, modeling, data flow monitoring, feature extraction and much more.

Innovation 83

Innovation Data Technical Review Artificial Inteligence 83

Capgemini

JANUARY 17, 2023

Here are four resolutions to make your data strategy pay off this year. Reassess your data architecture. Most executives (72 percent) say that data, both fragmented and with poor quality, is likely to be the biggest issue when aspiring to achieve AI goals. Stay the course to be prepared for a happy new year!

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

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

Mobilunity

MAY 8, 2023

It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Ingestion zone is where data is collected from various sources and ingested into the data lake.

Engineering 52

Engineering Data Storage AWS 52

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

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 - Ideas

MARCH 6, 2019

Learn new topics and refine your skills with more than 170 new live online training courses we opened up for March and April on the O'Reilly online learning platform. Certified Blockchain Solutions Architect (CBSA) Certification Crash Course , April 2. Data science and data tools. Data Structures in Java , April 1.

Course 10

Course Artificial Inteligence Training Machine Learning 10

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Cloudera

FEBRUARY 25, 2021

They need strong data exploration and visualization skills, as well as sufficient data engineering chops to fix the gaps they find in their initial study. The project launches an interactive visualization for exploring the quality of representations extracted using multiple model architectures.

Machine Learning 81

Machine Learning Artificial Inteligence Telecommunications Enterprise 81

TIBCO - Connected Intelligence

SEPTEMBER 22, 2020

For today’s most mature enterprise cloud architectures, ultra-quick querying capabilities on petabytes of data is what the modern pace of business demands. And for enterprises running AWS, Amazon Redshift is most certainly a part of the data warehousing picture given its size, flexibility, and scale. Reading Time: 2 minutes.

AWS 48

AWS Analytics Cloud Analysis 48

Altexsoft

APRIL 13, 2023

But of course, you can only share data you have yourself – so higher visibility leads to higher transparency. Supply chain control tower architecture: main components, integrations, and data sources As we mentioned, an SCCT is typically comprised of multiple components that handle various aspects of supply chain management.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

TIBCO - Connected Intelligence

DECEMBER 11, 2020

“We have been working with TIBCO for over 18 years, initially focused on enterprise application integration, service-oriented architecture, events, messaging, and other capabilities that optimize our client’s operations.

Business Transformation 52

Business Transformation Data Analytics Hotels 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

AI and Data technologies in the cloud. Building a Serverless Big Data Application on AWS”. Architecture and Algorithms for End-to-End Streaming Data Processing”. Running multidisciplinary big data workloads in the cloud”. Many universities are offering courses; some like UC Berkeley have multiple courses.

Big Data 84

Big Data Technology Tools Cloud 84

High Scalability

APRIL 14, 2020

Learn to balance architecture trade-offs and design scalable enterprise-level software. Check out Educative.io's bestselling new 4-course learning track: Scalability and System Design for Developers. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes.

Education 42

Education System Design Scalability Software Engineering 42

High Scalability

MAY 12, 2020

Learn to balance architecture trade-offs and design scalable enterprise-level software. Check out Educative.io's bestselling new 4-course learning track: Scalability and System Design for Developers. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes.

Education 41

Education System Design Scalability Software Engineering 41

High Scalability

APRIL 28, 2020

Learn to balance architecture trade-offs and design scalable enterprise-level software. Check out Educative.io's bestselling new 4-course learning track: Scalability and System Design for Developers. Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes.

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. Check out Educative.io 's bestselling new 4-course learning track: Scalability and System Design for Developers. Learn the Good Parts of AWS. Join more than 300,000 other learners.

Education 40

Education System Design AWS Scalability 40

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

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Cloudera

SEPTEMBER 1, 2020

Although not elaborated on in this blog post, it is possible to use a CDP Data Hub Data Engineering cluster for pre-processing data via Spark, and then post to Solr on DDE for indexing and serving. The advantage with cloud is of course the transient allocation of resources. Click Provision Cluster.

Data 66

Data Backup Disaster Recovery Storage 66

Apiumhub

AUGUST 12, 2021

His current technical expertise focuses on integration platform implementations, Azure DevOps, and Cloud Solution Architectures. Evgenii Vinogradov – Director, Analytical Solutions Department @YooMoneyon Evgenii is the Head of Data Engineering and Data Science team at YooMoney, the leading payment service provider on the CIS Market.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

O'Reilly Media - Ideas

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Trends in software architecture, infrastructure, and operations.

Technical Review 137

Technical Review Microservices Data Engineering Architecture 137

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. But research is that way.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

There’s no clear problem formulation, no clear loss function, lots of various data sets to use. Of course you’re going to waste too much time doing something that turns out to nothing. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. But research is that way.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Existek

SEPTEMBER 28, 2023

Therefore, it’s required to obtain good skills in data science. Model selection and design: AI developers choose appropriate machine learning algorithms and neural network architectures based on the problem at hand. Besides, their responsibilities include considering such factors as data type, volume, complexity, etc.

Artificial Inteligence 52

Artificial Inteligence Development How To Artificial Intelligence 52

O'Reilly Media - Ideas

JULY 28, 2020

As we mentioned in the first article of this series, an AI application for product recommendations can make a lot of mistakes before anyone notices (ignoring concerns about bias); this has business impact, of course, but doesn’t cause life-threatening harm. Data Quality and Standardization. Modeling and Evaluation.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

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 114

Trends Technical Review Technology Artificial Inteligence 114

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

SEPTEMBER 9, 2022

It aims at making data assets understandable and discoverable for users. In our library analogy, metadata management (in its simplest form, of course) would involve creating a book catalog and a user guide to navigate visitors around. Alation supports active metadata management with its Data Governance App and Data Catalog tools.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Kentik

DECEMBER 5, 2016

Kentik NPM monitors network performance by capturing samples of live traffic with nProbe and sending the enhanced flow data to the Kentik Data Engine (KDE; Kentik’s distributed big data backend). So of course we turned to Kentik Detect to answer the age-old question: “Is it the network or the application?”.

Network 40

Network Performance Metrics Software Review 40