Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Datavail

JUNE 8, 2023

Attendees were able to explore solutions and strategies to help them unlock the power of their data and turn it into actionable insights. The event tackles topics on artificial intelligence, machine learning, data science, data management, predictive analytics, and business analytics.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Apiumhub

APRIL 1, 2021

Business Analytics: The Science Of Data – Driven Decision Making by U Dinesh Kumar. It will show you how to treat data as a business asset that requires careful investment if you’re to gain real value. Designing data-intensive applications by Martin Kleppmann.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

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 Systems Review 115

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer? Data modeling.

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Develop business-specific analytics platform. A few more tips to consider.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

O'Reilly Media - Ideas

MARCH 1, 2023

Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence. growth over 2021.

Trends 133

Trends Technical Review Technology Software Review 133

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

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

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Cloudera

FEBRUARY 22, 2021

The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. This category describes the unique ability of CDP to accelerate deployment of use cases (and, as a result, the associated business value) by: .

Data 76

Data Analytics Government Technical Review 76