ParkMyCloud

MAY 29, 2019

There is exponential growth in the cloud computing industry, so it’s no surprise that the demand for cloud computing intellect and skills is also increasing, with no slowing down in the foreseeable future. Business Intelligence Analyst. IoT Engineer. Here are some trends we’re seeing. Cloud Consultants.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

FEBRUARY 22, 2022

Such an approach requires a great deal of investment since a whole ecosystem has to be created, including IoT sensors installation, acquiring specialized software, creating and maintaining machine learning (ML) models, engaging IT and data science specialists , and so on. Collecting data from connected sensors and external sources.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data pipeline components. When do you need a data pipeline?

Data 76

Data Storage Analytics Data Center 76

Mobilunity

DECEMBER 28, 2022

Machine Learning is a rapidly-growing field that is revolutionizing the way businesses work and collect data. The process of machine learning involves teaching computers to learn from data without being explicitly programmed. It’s used in a variety of industries to improve efficiency and accuracy. Business intelligence.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

Altexsoft

JULY 19, 2022

That’s exactly what every data-driven organization has been trying to find for years,” someone would come up with a new, better solution. Data mesh is another hot trend in the data industry claiming to be able to solve many issues of its predecessors. Decentralized data ownership by domain.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Stream processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc. Source: Marriott.

Big Data 78

Big Data Analytics Tools Applications 78

TIBCO - Connected Intelligence

DECEMBER 20, 2021

Given the wealth of enhancements and new products TIBCO has announced this year, we want to offer a recap of 2021 innovations to the TIBCO Connected Intelligence platform. The Connect Portfolio’s Multiple Innovations Spark Growth and Industry Recognition from Four Analysts.

Innovation 26

Innovation Analytics Virtualization Cloud 26

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

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Following this logic, any other writer with a short and memorable name — say, Gogol, Orwell, or Tolkien — could have become a symbol of endless data streams. How Apache Kafka streams relate to Franz Kafka’s books.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Apiumhub

APRIL 8, 2021

With the Data Science industry continually evolving, there can be a lot to keep up with. Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. As the director of Advertisement, he works to help data-driven businesses be more successful.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

Altexsoft

DECEMBER 9, 2020

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Introducing data engineering and data science expertise.

Analytics 102

Analytics Technical Review Technology Applications 102

Agile Engine

DECEMBER 27, 2023

Data analytics use cases by industry 7. The data analytics process 8. What to look for when hiring a data analytics consultancy 10. Case study: leveraging AgileEngine as a data solutions vendor 11. This article is an all-encompassing guide for all things related to data analytics and consultancies.

Big Data 52

Big Data Analytics Data Analysis 52

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers. Conclusion.

Data 40

Data Nonprofit Quality Assurance Education 40