O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 145

Weak Development Team Data Technical Review Survey 145

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Apiumhub

APRIL 8, 2021

Borba has been named a top Big Data and data science influencer and expert several times. He has also been named a top influencer in machine learning, artificial intelligence (AI), business intelligence (BI), and digital transformation. Jen Stirrup is a top influencer in Big Data and Business Intelligence.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

Altexsoft

DECEMBER 9, 2020

But, of course, the transition is very gradual and sometimes the typical inherent peculiarities of one level are adopted by businesses at a different level. Hard to believe, but even now there are businesses that do not use technology and manage their operations with pen-and-paper. Analytics maturity model.

Analytics 102

Analytics Technical Review Technology Applications 102

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. More formats, more engines, more interoperability.

Data 94

Data Analytics Open Source Architecture 94

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Altexsoft

NOVEMBER 22, 2019

Of course, the potential of well-structured guest data goes far beyond this and we’ll talk about the opportunities it offers in one of the next sections devoted to analyzing data. Procurement data. Some solutions are equipped with analytical features to show how your online reputation changes in the course of time.

Hotels 18

Hotels Data Technical Review Systems Review 18

Altexsoft

OCTOBER 29, 2020

Here, we introduce you to ETL testing – checking that the data safely traveled from its source to its destination and guaranteeing its high quality before it enters your Business Intelligence reports. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

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. Data analytics and business intelligence: drawing insights from data. Data Management Platforms.

Strategy 64

Strategy Database Administration Data Technical Review 64

TIBCO - Connected Intelligence

SEPTEMBER 22, 2020

And for enterprises running AWS, Amazon Redshift is most certainly a part of the data warehousing picture given its size, flexibility, and scale. Fast, fully-managed warehousing services make it simple and cost-efficient to analyze all your data right within your business intelligence (BI) and analytics platforms.

AWS 48

AWS Analytics Cloud Analysis 48

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Learn Apache Kafka.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. ELT vs ETL. Order of process phases.

Tools 52

Tools Software Review Systems Review Testing 52

Apiumhub

AUGUST 12, 2021

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. Also, he serves as the Program Director for Data science/Data Engineering Educational Program at Skillbox.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

OCTOBER 24, 2019

With a data warehouse, an enterprise is able to manage huge data sets, without administering multiple databases. Such practice is a futureproof way of storing data for business intelligence (BI) , which is a set of methods/technologies of transforming raw data into actionable insights. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. BTW, we have an engaging video explaining how data engineering works. Pricing page.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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 Artificial Inteligence 52

OpenCredo

JULY 13, 2018

We were asked to iron out some of the creases in a new Data Producer platform involving one of the Data Consumer pipelines (let’s call it Project Datatron). At first it looked like a fairly straightforward data engineering problem. We were introduced to the relevant Consumer, namely the Business Data team.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40

Altexsoft

JULY 19, 2022

It’s often used by internal apps managing business processes — ERPs, accounting software, and medical practice management systems , to name just a few. The analytical plane embraces data that is collected and transformed for analytical purposes such as enterprise reporting, business intelligence , data science , etc.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

SEPTEMBER 10, 2021

So, why does anyone need to integrate data in the first place? Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications. Middleware data integration.

Tools 52

Tools Data Software Review Technical Review 52

Agile Engine

DECEMBER 27, 2023

A data analytics consultancy has a team of specialists and engineers who perform data analytics for companies that don’t have the capacity to do it in-house. Prescriptive analytics 
Prescriptive analytics goes beyond predicting what might happen by pointing to a specific course of action to take.

Big Data 52

Big Data Analytics Data Analysis 52

Mobilunity

DECEMBER 9, 2024

Google Professional Machine Learning Engineer implies developers knowledge of design, building, and deployment of ML models using Google Cloud tools. It includes subjects like data engineering, model optimization, and deployment in real-world conditions. Data engineer.

Engineering 52

Engineering Artificial Inteligence Machine Learning Artificial Intelligence 52

Altexsoft

APRIL 13, 2023

But of course, you can only share data you have yourself – so higher visibility leads to higher transparency. Supply chain mapping means gathering information about your suppliers and partners and creating a map of your business network. to develop all the data architecture and analytics solutions.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Artificial Inteligence 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.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Altexsoft

DECEMBER 14, 2022

If you are a programmer, a DevOps , a data engineer , or any other specialist who wants to use Docker in projects, you should have a clear roadmap of how to get started with this technology. Complete the Docker certification course. There are quite a few academies that offer online courses with certifications.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

NOVEMBER 9, 2021

Traditionally, analytics is associated with business intelligence and data visualization that are focused on studying past events and current processes. Also known as predictive analytics, it’s about discovering hidden patterns and dependencies, forecasting future events, and supporting decisions with data. Extract data.

Analytics 52

Analytics Software Review Systems Review Technical Review 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

O'Reilly Media - Ideas

JANUARY 14, 2025

The data in each graph is based on OReillys units viewed metric, which measures the actual use of each item on the platform. It accounts for different usage behavior for different media: text, courses, and quizzes. In each graph, the data is scaled so that the item with the greatest units viewed is 1.

Trends 130

Trends Technology Security Artificial Inteligence 130

TechCrunch

APRIL 6, 2022

-based businesses said they accelerated their AI implementation over the past two years, while 20% said they’d boosted their usage of business analytics compared with the global average. Of course, the benefits haven’t been evenly distributed. “This is an exciting time for data engineering.

Data 230

Data Technical Cofounder Weak Development Team Data Engineering 230

Altexsoft

JULY 29, 2022

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Robust community.

Big Data 59

Big Data Data Google Cloud Open Source 59