Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Altexsoft

JANUARY 22, 2020

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data.

Analytics 20

Analytics Data IoT Analysis 20

CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. The data industry is growing fast, and Strata + Hadoop World has grown right along with it. Data scientists. Data engineers. Product managers.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

Altexsoft

FEBRUARY 8, 2021

Supply chain practitioners and CEOs surveyed by 6river share that the main challenges of the industry are: keeping up with the rapidly changing customer demand, dealing with delays and disruptions, inefficient planning, lack of automation, rising costs (of transportation, labor, etc.), Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

AUGUST 25, 2020

Big data is tons of mixed, unstructured information that keeps piling up at high speed. That’s why traditional data transportation methods can’t efficiently manage the big data flow. Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data.

Big Data 75

Big Data Data Engineering Engineering Data 75

O'Reilly Media - Ideas

MAY 1, 2019

Real-Time Streaming Analytics and Algorithms for AI Applications , May 15. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20. Data Analysis Paradigms in the Tidyverse , May 30. IoT Fundamentals , June 17-18.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

FEBRUARY 22, 2022

Fleet owners in trucking , car rental , delivery, and other transportation companies know that poorly maintained vehicles burn more fuel, require frequent oiling, and go kaput every other mile. Data is gathered from connected sensors and analyzed so that predictions of possible failures can be generated.

Software Review 52

Software Review Technical Review Software Technology 52

Hu's Place - HitachiVantara

MARCH 18, 2019

As a megacity Istanbul has turned to smart technologies to answer the challenges of urbanization, with more efficient delivery of city services and increasing the quality and accessibility of such services as transportation, energy, healthcare, and social services. This improved lead time from 2 days to less than 10 minutes.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59