CIO

JUNE 22, 2023

There’s a high demand for software engineers, data engineers, business analysts and data scientists, as finance companies move to build in-house tools and services for customers.

Industry 183

Industry UI/UX Telecommunications Quality Assurance 183

CIO

FEBRUARY 14, 2023

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

Hu's Place - HitachiVantara

APRIL 11, 2019

Few if any data management frameworks are business focused, to not only promote efficient use of data and allocation of resources, but also to curate the data to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need.

Data Engineering 81

Data Engineering Artificial Inteligence Machine Learning Technical Review 81

Altexsoft

JANUARY 22, 2020

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data. Sales region: Northern California.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

MAY 18, 2021

Second, since IaaS deployments replicated the on-premises HDFS storage model, they resulted in the same data replication overhead in the cloud (typical 3x), something that could have mostly been avoided by leveraging modern object store. Storage costs. using list pricing of $0.72/hour hour using a r5d.4xlarge

Cloud 86

Cloud Technical Review Storage Backup 86

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Cloudera

NOVEMBER 1, 2022

In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage.

Cloud 89

Cloud Government Analytics Storage 89

Cloudera

JANUARY 20, 2021

Managing the collection of all the data from all factories in the manufacturing process is a significant undertaking that presents a few challenges: Difficulty assessing the volume and variety of IoT data: Many factories utilize both modern and legacy manufacturing assets and devices from multiple vendors, with various protocols and data formats.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

Hu's Place - HitachiVantara

JANUARY 3, 2019

Data curation will be a focus to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need to power the organization.

Trends 86

Trends Artificial Inteligence Machine Learning Data Center 86

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces.

Cloud 78

Cloud Google Cloud Azure AWS 78

Hu's Place - HitachiVantara

MARCH 18, 2019

The requirement was to centralize and archive the data collected from these endpoint devices while keeping with regulation requirements. Hitachi Vantara provided HCP object storage to replace traditional storage for ease of access, search and index, privacy regulations and hybrid cloud.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams.

Virtualization 69

Virtualization Data How To Data Engineering 69

Altexsoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. Virtually, Hadoop puts no limits on the storage capacity. What is Hadoop.

Big Data 98

Big Data Tools Data Storage 98

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

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

Altexsoft

JUNE 14, 2021

InsureApp is another company that contextualizes behavior and translates it into personalized insurance by combining and interpreting data from smartphone sensors and IoT devices. You can start investing in data infrastructure and analytical pipelines to automate data collection and analysis mechanisms.

Insurance 88

Insurance Artificial Inteligence Machine Learning Policies 88

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

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage Data Engineering 52

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

Datavail

JUNE 15, 2023

Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources. Synapse Data Engineering : A Spark authoring experience that includes instant start with live pools and collaboration features. It triggers notifications and actions when it finds specified patterns in the data.

Azure 52

Azure Analytics Storage Generative AI 52

Cloudera

DECEMBER 20, 2022

Today, the costs of sensors, data capture, and information storage have significantly decreased and are one tenth of what they were 10 years ago, leading to the proliferation of data that enables advanced analytics-driving efficiencies. Explore operational efficiencies with our Federated Learning Machine Learning Prototype.

Energy 81

Energy Analytics Data Artificial Inteligence 81

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

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.

Strategy 64

Strategy Database Administration Data Technical Review 64

Altexsoft

SEPTEMBER 10, 2021

These systems can be hosted on-premises, in the cloud, and on IoT devices, etc. With the right data integration strategy, companies can consolidate the needed data into a single place and ensure its integrity and quality for better and more reliable insights. How data consolidation works. Middleware data integration.

Tools 52

Tools Data Software Review Technical 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. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

ParkMyCloud

JANUARY 17, 2020

Following the Azure learning path under Microsoft, there are certifications available that allow you to demonstrate your expertise in Microsoft cloud-related technologies and advance your career by earning one of the new Azure role-based certifications or an Azure-related certification in platform, development, or data. Azure Fundamentals.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Cloudera

MARCH 6, 2018

A shared data catalog and data context including definitions, permissions, and governance, offered as part of our Cloudera Altus platform to simplify configurations in the cloud, makes it easy to consolidate all data into a single, well-defined, persistent repository in object storage.

Analytics 40

Analytics Cloud Big Data AWS 40

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 Artificial Inteligence 52

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

TIBCO - Connected Intelligence

MARCH 5, 2020

Time-to-solution expectations for new data-driven solutions are even faster – With better data-driven solutions often the competitive battlefield, victory goes to the swift. Data Is The Wisest Bet for 2020.

Technology 42

Technology Trends Games IoT 42

Existek

JANUARY 11, 2022

In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. They provided a few services like computing, Azure Bob storage, SQL Azure, and Azure Service Bus. The new structure enabled the opportunity to meet such customer needs in computing as storage, networking, and services.

Azure 52

Azure AWS Cloud How To 52

Kentik

MAY 31, 2023

For many enterprises, applications represent only a portion of a much larger reliability mandate, including offices, robotics, hardware, and IoT, and the complex networking, data, and observability infrastructure required to facilitate such a mandate. This is no small feat and can lead to significant overhead and resource consumption.

Network 52

Network Cloud Load Balancer Systems Review 52

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

JULY 19, 2022

Decentralized data ownership by domain. Zhamak Dehghani divides the data into the “two planes”: The operational plane presents the data from the source systems where it originates — for example, front-desk apps, IoT systems , point of sales systems , etc. And it’s their job to guarantee data quality.

Architecture 52

Architecture Data Analytics Data Engineering 52

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. Find sources of relevant data.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52