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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

AWS Machine Learning - AI

JANUARY 26, 2024

If you are unfamiliar with the overall AI and ML workflow, start by reviewing 7 ways to improve security of your machine learning workloads to increase familiarity with the security controls needed for traditional AI/ML systems. There are many other AWS Security training and certification resources available.

Artificial Inteligence 117

Artificial Inteligence Generative AI Security Applications 117

Cloudera

DECEMBER 20, 2022

This is due to an improvement in plant uptime, supported by predictive maintenance applications, coupled with optimization of the fuel consumption that powers these plants, as well as fine-grained performance monitoring that eliminates over-production. . These actors are at both ends of the chain, as they produce and consume at the same time.

Energy 80

Energy Analytics Data Machine Learning 80

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Metadata storage usually implies developing a specialized repository. Metadata storage. What is metadata management?

Tools 59

Tools Technical Review Software Review Systems Review 59

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 81

Data Analytics Cloud Technical Review 81

CIO

JULY 15, 2022

Over the years, DTN has bought up several niche data service providers, each with its own IT systems — an environment that challenged DTN IT’s ability to innovate. “We Very little innovation was happening because most of the energy was going towards having those five systems run in parallel.”. The merger playbook.

Systems Review 278

Systems Review Fractional CTO System Development Team Review 278

Existek

JANUARY 11, 2022

It might be challenging as it requires a detailed analysis of the business-specific needs and a deeper understanding of the overall market situation. . In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. So how do companies choose the cloud service provider?

Azure 52

Azure AWS Cloud How To 52

Altexsoft

APRIL 13, 2023

Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions. The ultimate goal of an SCCT is to support efficient, data-based decision-making, planning, and risk management, as well as quick and effective reactions to disruption.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Hu's Place - HitachiVantara

JANUARY 3, 2019

” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Altexsoft

OCTOBER 29, 2020

When data is subjective and accurate, it gives us a better understanding than we can fathom with our human brains. Because as any system, data processing is subject to mistakes. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. This greatly increases data processing capabilities.

Big Data 75

Big Data Data Engineering Engineering Data 75

O'Reilly Media - Ideas

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Imagine you are a data scientist at Disney.

Product Management 141

Product Management Artificial Inteligence Machine Learning Software Review 141

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. Data analysis.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

MARCH 18, 2021

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g The data flow of both ETL and ELT relies on three core stages.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Mobilunity

NOVEMBER 24, 2021

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. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. Data engineering explained in 14 minutes.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 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. Let’s take a quick look at the big data infrastructure. Big Data infrastructure in healthcare.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

NOVEMBER 9, 2021

Accounts payable are most vulnerable to errors (whether deliberate or not) due to disconnected and inaccurate information, especially if you have to deal with a big amount of documentation and process multiple transactions. The market is constantly changing due to a myriad of factors. Contract management to review and audit agreements.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Kentik

MAY 31, 2023

For NetOps, this mandate includes a wide range of tasks, including monitoring and identifying top talkers, careful capacity planning, resource availability and consumption, path analysis, security and infrastructure monitoring and management, and more. This is no small feat and can lead to significant overhead and resource consumption.

Network 52

Network Cloud Load Balancer Firewall 52

Kentik

OCTOBER 12, 2015

Only, in network monitoring, there are limits to what can be done by the smart, individual engineer. Here’s a common practice: SNMP gets dumped into RRDTool, an open source data logging and graphing system for time series data. Simply put, it’s not cost effective to store flow data (e.g. Why is this so?

Analysis 40

Analysis Open Source Storage Network 40

Cloudera

MAY 13, 2021

In this blog, we walk through the Impala workloads analysis in iEDH, Cloudera’s own Enterprise Data Warehouse (EDW) implementation on CDH clusters. If you burst this user to the cloud how much pressure will it relieve from your on premises system? Fixed Reports / Data Engineering jobs . Batched and scripted.

Data Engineering 68

Data Engineering Cloud Weak Development Team Resources 68

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. 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. It depends on the volume of incoming data.

Big Data 59

Big Data Data Google Cloud Storage 59

O'Reilly Media - Ideas

JANUARY 25, 2024

And the real question that will change our industry is “How do we design systems in which generative AI and humans collaborate effectively?” Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%. So the software development world is changing. We also saw 9.8%

Trends 121

Trends Technical Review Technology Artificial Inteligence 121

Altexsoft

FEBRUARY 22, 2022

And breakdowns are just too expensive, especially at a fleet-wide scale (not to mention risking drivers’ lives, losses due to unfulfilled contracts and related downtime, and customer dissatisfaction). You can adopt a comprehensive fleet management system that has vehicle maintenance as one of its modules. So, what’s the alternative?

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

SEPTEMBER 10, 2021

These systems can be hosted on-premises, in the cloud, and on IoT devices, etc. Logically, each system stores information differently: in the structured, unstructured, and semi-structured formats. The problem is, the information you have is scattered across different systems isolated from one another including.

Tools 52

Tools Data Software Review Technical Review 52

Altexsoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. 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.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

APRIL 26, 2022

Semi-structured data is somewhere in the middle, meaning it is partially structured but doesn’t fit the tabular models of relational databases. The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Hu's Place - HitachiVantara

MARCH 18, 2019

Smart cities also offer great opportunities for transformation and optimization of the urban economy with production systems based on information and technology. The requirement was to centralize and archive the data collected from these endpoint devices while keeping with regulation requirements.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

NOVEMBER 5, 2021

The stage involves activities related to data quality management , data integration , support for healthcare data standards , and optimum information flow design. Data analysis, transformation, and decision support revolve around deriving knowledge and insights critical for enhancing patient care.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

OCTOBER 2, 2020

Data is a valuable source that needs management. If your business generates tons of data and you’re looking for ways to organize it for storage and further use, you’re at the right place. Read the article to learn what components data management consists of and how to implement a data management strategy in your business.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. What does the high-performance data project have to do with the real Franz Kafka’s heritage? process data in real time and run streaming analytics. How Apache Kafka streams relate to Franz Kafka’s books.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

OCTOBER 24, 2019

Similar to humans companies generate and collect tons of data about the past. And this data can be used to support decision making. While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50