Hu's Place - HitachiVantara

MAY 10, 2019

Rules based systems become unwieldy as more exceptions and changes are added and are overwhelmed by today’s sheer volume and variety of new data sources. For this reason, many financial institutions are converting their fraud detection systems to machine learning and advanced analytics and letting the data detect fraudulent activity.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. ARMONK, NY - 15 Jun 2015: IBM (NYSE:IBM) today announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

TIBCO - Connected Intelligence

DECEMBER 1, 2020

A TIBCO analytics user, LeadMind, CAF´s data-driven platform, provides hi-tech solutions to improve the operations and maintenance of those trains. Its clients include public transport giants around the globe: Renfe, SNCF, CPTM, STC in Mexico, Northern, Wales and Borders, Transport for London and Auckland Transport among many others.

Training 34

Training Transportation Analytics IoT 34

O'Reilly Media - Data

APRIL 3, 2018

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Temporal data and time-series analytics.

Big Data 85

Big Data Technology Tools Cloud 85

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 103

Data Artificial Inteligence Analytics Machine Learning 103

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. Speakers have a laser-sharp focus on the data issues shaping all aspects of business, including verticals such as finance, media, retail and transportation, and government.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

CTOvision

JANUARY 28, 2015

Our speakers have a laser-sharp focus on the data issues shaping all aspects of business, including verticals such as finance, media, retail and transportation, and government. The data industry is growing fast, and Strata + Hadoop World has grown right along with it. Data scientists. Data engineers.

Big Data 109

Big Data Case Study Conference Study 109

Altexsoft

FEBRUARY 8, 2021

Supply chain practitioners and CEOs surveyed by 6river share that the main challenges of the industry are: keeping up with the rapidly changing customer demand, dealing with delays and disruptions, inefficient planning, lack of automation, rising costs (of transportation, labor, etc.), Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

AUGUST 25, 2020

Big data is tons of mixed, unstructured information that keeps piling up at high speed. That’s why traditional data transportation methods can’t efficiently manage the big data flow. Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data.

Big Data 75

Big Data Data Engineering Engineering Data 75

Altexsoft

JUNE 11, 2021

Process analytics takes place. Here, KPIs can be created and monitored to uncover potential improvement areas, data mining and/or ML algorithms can be used to detect hidden patterns and dependencies, or conformance checking techniques can be applied to compare the process to a certain ideal model. Process mining and supply chain.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. 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

Altexsoft

NOVEMBER 9, 2021

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

O'Reilly Media - Ideas

MAY 1, 2019

Real-Time Streaming Analytics and Algorithms for AI Applications , May 15. 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. AI and machine learning.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Marcusoft

SEPTEMBER 10, 2019

He is a brilliant programmer, data engineer, agile aficionado and he keeps my argumentation sharp with his analytic abilities. Lars needs to go places and transport things. It was a powerful lesson on true value, customer focus and lead vs flow time for me. The story. I have a good friend called Lars. Same feeling.

Agile 40

Agile Transportation Coaching Data Engineering 40

Kentik

MAY 9, 2017

Without the visibility and analytics provided by tracking data, there would be no way to know, nor any way to leverage that data to improve delivery times, reduce cost, or allocate load across the paths and system components that serve various customers. Or maybe that would happen more than just “sometimes.”

Internet 40

Internet Analysis Network Analytics 40

CIO

JULY 15, 2022

Its weather-related services can be as simple as helping utilities predict short-term demand for energy, or as complex as advising maritime transporters on routing ocean-going cargo ships around developing storms. Analytics, Data Management To combat that, Ewe emphasized the potential for growth from the start. “We

Systems Review 279

Systems Review Fractional CTO System Development Team Review 279

Altexsoft

NOVEMBER 27, 2020

Just like any industry, transportation is experiencing a difficult year. In the transportation process, such companies are called shippers, even if they employ third-parties to ship their goods. Finding the most efficient route, choose the transport mode(s), assigning vehicles, drivers, and balancing the load.

Software 69

Software Transportation Analytics System 69

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

AWS Machine Learning - AI

JANUARY 26, 2024

Conversely, the data in your model may be extremely sensitive and highly regulated, so deviation from AWS Key Management Service (AWS KMS) customer managed key (CMK) rotation and use of AWS Network Firewall to help enforce Transport Layer Security (TLS) for ingress and egress traffic to protect against data exfiltration may be an unacceptable risk.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

Altexsoft

JANUARY 27, 2022

In the last decades, many cities adopted intelligent transportation systems (ITS) that support urban transportation network planning and traffic management. Transportation, delivery, field service, and other businesses have to accurately schedule their operations and create the most efficient routes. National/local authorities.

Machine Learning 69

Machine Learning Artificial Inteligence Transportation Network 69

Altexsoft

FEBRUARY 22, 2022

Fleet owners in trucking , car rental , delivery, and other transportation companies know that poorly maintained vehicles burn more fuel, require frequent oiling, and go kaput every other mile. Reporting and analytics is essential to obtain a bird eye view of your fleet and make data-based decisions. Access permissions.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. These are data engineers who are responsible for implementing these processes. Data size and type. ELT comes to the rescue. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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. a suitable technology to implement data lake architecture. a suitable technology to implement data lake architecture. Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Hu's Place - HitachiVantara

MARCH 18, 2019

As a megacity Istanbul has turned to smart technologies to answer the challenges of urbanization, with more efficient delivery of city services and increasing the quality and accessibility of such services as transportation, energy, healthcare, and social services. This improved lead time from 2 days to less than 10 minutes.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

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. Scattered across different storages in various formats, data values don’t talk to each other. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Kentik

SEPTEMBER 5, 2017

To briefly review, Interface Classification enables an organization to quickly and efficiently assign a Connectivity Type and Network Boundary value to every interface in the network, and to store those values in the Kentik Data Engine (KDE) records of each flow that is ingested by Kentik Detect.

Transportation 40

Transportation Network Analysis Groups 40

Kentik

APRIL 18, 2016

This approach would take a little bit less communication and require a lot less work to match templates to data packets. You could take the well-known data types like IPv4 and IPv6 and build a fast path for them. With templates out-of-band, the protocol would also be ‘re-sample-able’ in transport. Kentik KFlow.

Transportation 40

Transportation IPv6 Network Data 40

Altexsoft

OCTOBER 23, 2019

MODEX 2020 will cover a broader spectrum of transportation, logistics, supply management, and fulfillment. MODEX 2020 invites supply chain and transportation entrepreneurs, C-level executives, and higher-level managers, supply chain, logistics, and transportation software providers. However, there are two additional options.

Security 13

Security Artificial Inteligence Conference Data Center 13

Altexsoft

NOVEMBER 22, 2019

Apart from purchasing expenses, there are many other figures to be considered: transportation and freight costs, insurance, customs duty, and the like. Some solutions are equipped with analytical features to show how your online reputation changes in the course of time. Major hotel data sources overview.

Hotels 18

Hotels Data Technical Review Systems Review 18

TIBCO - Connected Intelligence

NOVEMBER 13, 2019

The challenge that many organizations now face is to manage data that is representative of business problems and apply visual analytics and data science to identify insights and drive actions on the business. So how do we put data and AI to work for us; to help us address our business challenges?” .

Data 4

Data Artificial Inteligence Analytics Healthcare 4

Altexsoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59