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 Machine Learning Artificial Inteligence Technical Review 81

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Cloud-based spending will reach 60% of all IT infrastructure and 60-70% of all software, services, and technology spending by 2020. They require highly modernized digital application and service environments running on true cloud platforms like Hitachi Enterprise Cloud.

Cloud 78

Cloud Google Cloud Azure AWS 78

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. After all, machine learning with Python requires the use of algorithms that allow computer programs to constantly learn, but building that infrastructure is several levels higher in complexity. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 82

Innovation Data Technical Review Artificial Inteligence 82

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. 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

DataRobot

MARCH 10, 2022

DataRobot and Snowflake Jointly Unleash Human and Machine Intelligence Across the Industrial Enterprise Landscape. This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). IoT Empowered Assembly Lines: Predictive Maintenance.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Altexsoft

JULY 23, 2020

Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. In other words, they dedicate a quarter of their efforts to infrastructure — instead of doing what they can do best. MLOps lies at the confluence of ML, data engineering, and DevOps. Data validation.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JUNE 25, 2019

However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. Data and analytics. Hybrid cloud and infrastructure. Internet of Things.

Azure 52

Azure AWS Cloud How To 52

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. Batch processing.

Analytics 20

Analytics Data IoT Analysis 20

Apiumhub

SEPTEMBER 20, 2023

Tech Conferences Compass Tech Summit – October 5-6 Compass Tech Summit is a remarkable 5-in-1 tech conference, encompassing topics such as engineering leadership, AI, product management, UX, and data engineering that will take place on October 5-6 at the Hungarian Railway Museum in Budapest, Hungary.

Conference 95

Conference Artificial Inteligence UI/UX Machine Learning 95

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. Cloud Consultants.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

MARCH 31, 2020

Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data? You need to have infrastructure, hardware and/or software, that will allow you to do that. You need an efficient data pipeline. What is a data pipeline?

Data 76

Data Storage Analytics Data Center 76

ParkMyCloud

JANUARY 17, 2020

Azure Data Engineer Associate. For individuals that design and implement the management, security, monitoring, and privacy of data – using the full stack of Azure data services – to satisfy business needs. . Azure IoT Developer Specialty. Available certifications include : Associate Cloud Engineer.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Kentik

MAY 31, 2023

Reliability is a massive burden for network operators While DevOps teams and their SREs focus on the reliability of the application environment, an enterprise’s network concerns often extend well beyond the uptime of a suite of customer-facing web and mobile apps.

Network 52

Network Cloud Load Balancer Firewall 52

Altexsoft

OCTOBER 24, 2019

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. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

JULY 19, 2022

It’s easiest to understand the concept of a data mesh by looking at the core principles behind it which we’re going to uncover more extensively later on. They are: domain-oriented decentralized data ownership and architecture, data as a product, self-serve data infrastructure as a service, and. But not only.

Architecture 52

Architecture Data Analytics Data Engineering 52

Datavail

JUNE 15, 2023

“It unifies the business model across all the different types of analytics workloads, whether they’re SQL, machine learning – whatever job you want, you can use the same compute infrastructure. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

Azure 52

Azure Analytics Storage Generative AI 52

Altexsoft

OCTOBER 26, 2022

This is how Deloitte defines this role, “The CDO is a catalyst and driver of change, bringing a new culture and mindset, and new ways of working to the enterprise, that would otherwise not have happened or would have happened too slowly.”. Today, the CIO’s focus is primarily on a company’s IT architecture and infrastructure.

CTO 52

CTO Organization Technical Review Culture 52

Hu's Place - HitachiVantara

MARCH 18, 2019

City of Istanbul Governorship: Safe, Smart Campus The challenge was to secure the governorship campus and include multiple existing video and IoT systems. Pentaho unlocked mapR to enable data science and enabled business users to operationalize data through self-service.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

OCTOBER 2, 2020

Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Fitting into wider enterprise architecture, it outlines how data is collected, integrated, transformed, stored, and used. Data Governance includes Master Data Management.

Database Administration 64

Database Administration Strategy Data Technical Review 64

BPM

JANUARY 18, 2019

Enterprises must consider where and when to apply RPA, to achieve the expected value returns. As we move into a world that is more and more dominated by technologies such as big data, IoT, and ML, more and more processes will be started by external events. Steven Stanton FCB Partners [link]. Lloyd Dugan BPM.com [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

AUGUST 22, 2022

The landscape of enterprise data is fragmented. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 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. A single cluster can span across multiple data centers and cloud facilities.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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

By correlating an ever-wider set of traffic data into a single, instantly-queryable dataset (the Kentik Data Engine, aka KDE), we’re able to generate technical and business insights with direct, powerful relevance to your network operations. To what extent does it host content-serving cache servers on its own infrastructure?

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

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 127

Architecture Data Security Technical Review 127

CIO

AUGUST 3, 2022

Because of this, redesigning the enterprise for the data economy is the chief remit CEOs have for today’s leading-edge CIOs. . When Cargill started putting IoT sensors into shrimp ponds, then CIO Justin Kershaw realized that the $130 billion agricultural business was becoming a digital business. The cloud.

SDLC 363

SDLC IoT Machine Learning Artificial Inteligence 363

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

Cloudera

MAY 18, 2021

Infrastructure cost optimization by enabling container-based scalability for compute resources based on processing load and by leveraging object storage that has lower price point than compute-attached storage. Technology and infrastructure costs . data streaming, data engineering, data warehousing etc.),

Cloud 86

Cloud Technical Review Storage Backup 86

Altexsoft

MARCH 14, 2023

A modern data stack can help the company manage and analyze this data effectively by using cloud-based data warehouses like Snowflake , data integration tools like Stitch, and data visualization software like Power BI. Built around a cloud data warehouse, data lake, or data lakehouse.

Data 59

Data Technical Review Software Review Artificial Inteligence 59