Hu's Place - HitachiVantara

MAY 10, 2019

A Big Data Analytics pipeline– from ingestion of data to embedding analytics consists of three steps Data Engineering : The first step is flexible data on-boarding that accelerates time to value. This will require another product for data governance. This is colloquially called data wrangling.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

Altexsoft

APRIL 13, 2023

If we speak about end-to-end visibility, we mean that we should be able to have a granular view of all the main components of a supply chain: transportation – which entails control over the actual delivery process, tracking shipments , predicting ETA , etc.; increase customer satisfaction by giving real-time status updates; and so on.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

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

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. 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.

Big Data 59

Big Data Data Google Cloud Storage 59

Cloudera

JANUARY 20, 2021

This story will show how data is collected, enriched, stored, served, and then used to predict events in the car’s manufacturing process using Cloudera Data Platform.

Data 103

Data Artificial Inteligence Analytics Machine Learning 103

Trigent

NOVEMBER 3, 2022

Experts unanimously agree data analytics is here to stay, considering 98% of 3PLs and 93% of shippers believe in having data-driven decision-making capabilities to manage supply chain activities. In comparison, 71% of 3PLs think process quality and performance can be significantly improved with the help of big data.

Analytics 52

Analytics Data IoT Trends 52

Altexsoft

JUNE 11, 2021

Process mining offers a lot of optimization opportunities to the compex, multifaceted supply chain industry, including such aspects as manufacturing, warehousing , transportation , inventory management , retail management, etc. Establishing secure data exchange between systems would facilitate information collection and analysis.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. 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.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data 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 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

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.), Analytics in logistics and transportation.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Data 52

Data Transportation Scalability Systems Review 52

Altexsoft

MARCH 18, 2021

As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Basically, ELT inverts the last two stages of the ETL process, meaning that after being extracted from databases data is loaded straight into a central repository where all transformations occur. Data size and type.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

DECEMBER 14, 2022

During shipment, goods are carried using different types of transport: trucks, cranes, forklifts, trains, ships, etc. What’s more, the goods come in different sizes and shapes and have different transportation requirements. Then came standardized intermodal containers that revolutionized the transportation industry.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Netflix’s diverse data landscape made it challenging to capture all the right data and conforming it to a common data model.

Infrastructure 87

Infrastructure Data Technical Review Systems Review 87

Altexsoft

NOVEMBER 23, 2020

Data migration is a one-way journey that ends once all the information is transported to a target location. Integration, in contrast, can be a continuous process, that involves streaming real-time data and sharing information across systems. Data migration vs data replication. Data migration vs data replication.

Data 104

Data Transportation Backup Storage 104

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. It’s an awful lot of data, so it has to be processed with special tools. Processing data.

Software Review 52

Software Review Technical Review Software Technology 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

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

NOVEMBER 9, 2021

Indirect spend is any expenses that are needed to operate the business, such as office supplies, utilities, transportation, insurance, marketing, business travel, warehousing costs, wages, and so on. Meanwhile, we’ll describe the process of turning raw data around you into actionable insights. Extract data. Consolidate data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

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. Extract, Transform, Load, or ETL process batches information and moves it from source systems to a data warehouse. Ensure data accessibility.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 23, 2019

Tech Alpharetta hosts regular events for tech-focused executives, with engineering-related activities. The events cover domains such as big data, cybersecurity, blockchain, and cryptocurrency. MODEX 2020 will cover a broader spectrum of transportation, logistics, supply management, and fulfillment. TechAlpharetta.

Security 13

Security Artificial Inteligence Conference Data Center 13

TIBCO - Connected Intelligence

NOVEMBER 13, 2019

These applications are delivering data management and analytics insights and actions, across healthcare, energy, CPG, retail, high tech manufacturing, transportation and logistics. Ready to take charge of your analytics strategy and remove the grunt work of time-consuming data prep?

Data 4

Data Artificial Inteligence Analytics Healthcare 4

Altexsoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. 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