CIO

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Organization 278

Organization Technical Review Data Artificial Inteligence 278

O'Reilly Media - Ideas

MAY 1, 2019

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. Data Visualization with Matplotlib and Seaborn , June 4. Real-time Data Foundations: Kafka , June 11.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Altexsoft

JANUARY 22, 2020

Similar to a real world stream of water, continuous transition of data received the name streaming , and now it exists in different forms. Media streaming is one of them, but it’s only a visible part of an iceberg where data streaming is used. Data visualization as a part of data representation and analytics.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

FEBRUARY 8, 2021

A single comment in social media can have a tremendous impact, so traditional methods are not always effective. This approach demands significant investments in software, equipment, and human resources to create advanced data architecture, but the resulting accuracy and visibility are worth paying for. Cost control.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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

MARCH 16, 2021

It’s referred to as big data, since, for example, just a single complete human genome sequence produces about 200 Gb of raw data. Now, we know where big data in healthcare originates. Check our article on data engineering to get a detailed understanding of the data pipeline and its components.

Big Data 116

Big Data Healthcare Applications Data 116

O'Reilly Media - Ideas

MARCH 6, 2019

Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. Foundational Data Science with R , March 26-27. What You Need to Know About Data Science , April 1. Real-Time Data Foundations: Flink , April 17.

Course 10

Course Artificial Inteligence Training Microservices 10

Apiumhub

APRIL 5, 2022

Apiumhub has become a Media partner of the Data Innovation Summit – the most influential data, AI and advanced analytics event in the Nordics and beyond. . 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 52

Innovation Data Artificial Inteligence Case Study 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

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

BPM

JANUARY 18, 2019

Now we’re seeing AI dominating the conversations (without a lot of actual adoption in the early majority), and RPA creating a lot of buzz, though companies adopting it are starting to realize that scaling an RPA based automation architecture is flawed by design. This requires a new architecture capable of true scale and speed.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. What is data virtualization?

Virtualization 69

Virtualization Tools Data Architecture 69

Altexsoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes. No wonder only 0.5

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

OCTOBER 26, 2022

To enable this conversion, a CDO uses digital information and modern technologies such as the cloud, the Internet of Things , mobile apps, social media, machine learning-based products, and digital marketing. Today, the CIO’s focus is primarily on a company’s IT architecture and infrastructure. Attract talent. Business acumen.

CTO 52

CTO Organization Technical Review Culture 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. Apache Hadoop.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake data management processes. Ensure data accessibility.

Database Administration 64

Database Administration Strategy Data Technical Review 64

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

Kentik

JUNE 4, 2019

For the ISP’s executive and engineering teams, these variations increase the complexity of meeting two main operational goals: Ensuring the high throughput required for a good user experience. To succeed at these goals, an ISP needs to define a robust, performant architecture and also a set of best practices.

Video 56

Video Network Internet Groups 56

Altexsoft

DECEMBER 9, 2020

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102

Agile Engine

DECEMBER 27, 2023

Case study: leveraging AgileEngine as a data solutions vendor 11. Key takeaways Any organization that operates online and collects data can benefit from a data analytics consultancy, from blockchain and IoT, to healthcare and financial services The market for data analytics globally was valued at $112.8

Big Data 52

Big Data Analytics Data Analysis 52

Hu's Place - HitachiVantara

JANUARY 15, 2019

When the formation of Hitachi Vantara was announced, it was clear that combining Hitachi’s broad expertise in OT (operational technology) with its proven IT product innovations and solutions, would give customers a powerful, collaborative partner, unlike any other company, to address the burgeoning IoT market.

Systems Review 72

Systems Review Storage System Software Review 72

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

Data 59

Data Technical Review Software Review Artificial Inteligence 59