The Pragmatic Engineer

OCTOBER 17, 2024

Storing data: data collected is stored to allow for historical comparisons. Benchmarking: for new server types identified – or ones that need an updated benchmark executed to avoid data becoming stale – those instances have a benchmark started on them.

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Cloud AWS Metadata Cloud Computing 314

Knowledge Hut

AUGUST 19, 2024

A Deloitte survey reveals the following: 49% of the respondents said data analytics helps them make better business decisions. What i s a Data Collection Plan ? A Data collection plan is a detailed document that describes the exact steps and sequence that must be followed in gathering data for a project.

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Edureka

JULY 18, 2024

The secret sauce is data collection. Data is everywhere these days, but how exactly is it collected? This article breaks it down for you with thorough explanations of the different types of data collection methods and best practices to gather information. What Is Data Collection?

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Cloudera

DECEMBER 16, 2022

We are pleased to announce that Cloudera has been named a Leader in the 2022 Gartner ® Magic Quadrant for Cloud Database Management Systems. This helps our customers quickly implement an unified data fabric architecture. 5-Integrated open data collection. This year we’ve been named a Leader.

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Database Cloud Systems Management 92

Precisely

DECEMBER 12, 2024

Key Takeaways : The significance of using legacy systems like mainframes in modern AI. How mainframe data helps reduce bias in AI models. The challenges and solutions involved in integrating legacy data with modern AI systems. The potential benefits of these integrations.

Healthcare 64

Healthcare Algorithm Finance Data Integration 64

AltexSoft

JULY 27, 2021

You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. Personalization and recommender systems in a nutshell. Primarily developed to help users deal with a large range of choices they encounter, recommender systems come into play. Amazon, Booking.com) and.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Netflix Tech

FEBRUARY 14, 2025

It requires a state-of-the-art system that can track and process these impressions while maintaining a detailed history of each profiles exposure. This nuanced integration of data and technology empowers us to offer bespoke content recommendations.

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Kafka Datasets Metadata Utilities 66

Pinterest Engineering

MARCH 26, 2025

Unified Logging System: We implemented comprehensive engagement tracking that helps us understand how users interact with gift content differently from standardPins. Unified Logging System: We implemented comprehensive engagement tracking that helps us understand how users interact with gift content differently from standardPins.

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Building Engineering Algorithm Systems 59

Snowflake

MARCH 12, 2025

For example, ticketing, merchandise, fantasy engagement and game viewership data often reside in separate systems (or with separate entities), making it a challenge to bring together a cohesive view of each fan. Sports entity data teams are often mighty but small making complex technology solutions unrealistic to leverage.

Media 63

Media Cloud Programming Data Collection 63

Scott Logic

AUGUST 5, 2024

The discussion touches on practical aspects of implementing observability and how this approach can lead to faster problem detection and resolution, as well as cost savings by reducing the volume of less useful data collected. Links from this episode What is Observability?

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Systems Data Collection Architecture Government 59

Cloudera

APRIL 13, 2022

It means your company has automated the processes of collecting, understanding and acting on data across the board, from production to purchasing to product development to understanding customer priorities and preferences. Data collection and interpretation when purchasing products and services can make a big difference.

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Pinterest Engineering

AUGUST 8, 2024

In our previous system, which operated on a daily budget allocation model, the system relied on predicting daily budgets for individual users on a daily basis, constraining the flexibility and responsiveness required for dynamic user engagement and content changes. Figure 1 below shows the overview of the system architecture.

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Systems Machine Learning Utilities Architecture 45

Data Engineering Weekly

MARCH 2, 2025

DeepSeek continues to impact the Data and AI landscape with its recent open-source tools, such as Fire-Flyer File System (3FS) and smallpond. The industry relies more or less on S3 as a de facto data storage, and I found the experimentation on optimizing the S3 read optimization to be an excellent reference.

Data Engineering 62

Data Engineering Data Engineer Engineering Datasets 62

Cloudera

MAY 4, 2022

The availability and maturity of automated data collection and analysis systems is making it possible for businesses to implement AI across their entire operations to boost efficiency and agility. AI increasingly enables systems to operate autonomously, making self-corrections automatically as necessary.

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Knowledge Hut

JANUARY 18, 2024

For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data. A Python with Data Science course is a great career investment and will pay off great rewards in the future.

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Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Data Collection Challenge. Factory ID.

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Manufacturing Data Warehouse Kafka Retail 110

Snowflake

JANUARY 18, 2024

A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible. And in many ERP consolidations, historical data from the legacy system is lost, making it challenging to do predictive analytics. Ease of use Snowflake’s architectural simplicity improves ease of use.

Manufacturing 109

Manufacturing Unstructured Data Cloud Architecture 109

Data Engineering Podcast

APRIL 28, 2024

In order to simplify the integration of AI capabilities into developer workflows Tsavo Knott helped create Pieces, a powerful collection of tools that complements the tools that developers already use.

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Rockset

DECEMBER 19, 2023

From his early days at Quora to leading projects at Facebook and his current venture at Fennel (a real-time feature store for ML), Nikhil has traversed the evolving landscape of machine learning engineering and machine learning infrastructure specifically in the context of recommendation systems.

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Edureka

JANUARY 27, 2025

A Red Team is a group of skilled cybersecurity professionals whose primary mission is to simulate real-world cyberattacks on an organization’s IT systems. Enhance Awareness : Help organizations recognize the potential impact of cyberattacks on their systems and operations. What is a Red Team in Cybersecurity?

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Cloudera

FEBRUARY 8, 2021

As advanced use cases, like advanced driver assistance systems featuring lane change departure detection, advanced vehicle diagnostics, or predictive maintenance move forward, the existing infrastructure of the connected car is being stressed. billion in 2019, and is projected to reach $225.16 billion by 2027, registering a CAGR of 17.1%

Manufacturing 108

Manufacturing Machine Learning Data Ingestion Electronics 108

Cloudera

FEBRUARY 8, 2021

To accomplish this, ECC is leveraging the Cloudera Data Platform (CDP) to predict events and to have a top-down view of the car’s manufacturing process within its factories located across the globe. . Having completed the Data Collection step in the previous blog, ECC’s next step in the data lifecycle is Data Enrichment.

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Data Engineering Podcast

NOVEMBER 6, 2022

In this episode Nick King discusses how you can be intentional about data creation in your applications and services to reduce the friction and errors involved in building data products and ML applications. Can you share your definition of "behavioral data" and how it is differentiated from other sources/types of data?

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Striim

MARCH 21, 2025

Your electric consumption is collected during a month and then processed and billed at the end of that period. Stream processing: data is continuously collected and processed and dispersed to downstream systems. Real-time data processing has many use cases. Stream processing is (near) real-time processing.

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Cloudera

NOVEMBER 19, 2020

Furthermore, the same tools that empower cybercrime can drive fraudulent use of public-sector data as well as fraudulent access to government systems. In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud.

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Snowflake

JULY 8, 2024

These select EU deployments will be connected to and will send all usage data to the EU repository and only select usage data will be sent to the global repository. European Union (EU) data sovereignty Snowflake’s first zonal repository outside of the US will be located in the EU to house usage data collected from the region.

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Cloud Google Cloud Education AWS 111

Engineering at Meta

JANUARY 27, 2023

This talk showcases Bifrost and Echo , which are the first networks to directly connect the US and Singapore and will support SGA, Meta’s first APAC data center. Millisampler data allows us to characterize microbursts at millisecond or even microsecond granularity.

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Engineering Software Engineer Software Engineering Transportation 130

Monte Carlo

MARCH 13, 2025

Bank Marketing Data Set: Data collected from a Portuguese marketing campaign related to bank deposit subscriptions for 45,211 clients and 20 features, with an output response of whether an individual subscribed to a term deposit. Consider a fraud detection system for a large e-commerce platform.

Banking 52

Banking Datasets Data Machine Learning 52

Databand.ai

MAY 30, 2023

Data quality refers to the degree of accuracy, consistency, completeness, reliability, and relevance of the data collected, stored, and used within an organization or a specific context. High-quality data is essential for making well-informed decisions, performing accurate analyses, and developing effective strategies.

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Edureka

MARCH 19, 2025

As AI systems get smarter, they need to be able to extend beyond what they’ve seen, and zero-shot learning is great for that. Efficient Model Training: Reduces time and resources spent on collecting and labeling data. Scalable Solutions: Supports expanding systems without frequent retraining.

Entertainment 40

Entertainment Datasets Machine Learning Data Collection 40

Edureka

MARCH 19, 2025

As AI systems get smarter, they need to be able to extend beyond what they’ve seen, and zero-shot learning is great for that. Efficient Model Training: Reduces time and resources spent on collecting and labeling data. Scalable Solutions: Supports expanding systems without frequent retraining.

Entertainment 40

Entertainment Datasets Machine Learning Data Collection 40

Cloudera

APRIL 22, 2022

Part of this emphasis extends to helping enterprises deal with their data and overall cloud connectivity as well as local networks. At the same time, operators are also becoming more data- and cloud-centric themselves. There may be particular advantages for location-specific data collected or managed by operators.

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RandomTrees

NOVEMBER 25, 2024

There are obligations on telecommunications providers to ensure that their systems of AI are accountable and understandable to clients and regulatory authorities. In addition, there are many technological infrastructure expenditures as well as AI management personnel costs that are required in the application of Generative AI.

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Telecommunication IT Unstructured Data Data Mining 52

U-Next

MARCH 7, 2023

Data Integration and Identification Clarification: You can gain helpful insights into previous consumer activities through data unification, also known as identity resolution, which combines data from many sources and links it to specific customer profiles. Real-time customer data aggregation is done via a CDP.

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Bytes Media Data Data Collection 98

Striim

FEBRUARY 26, 2025

new Intercom Reader makes it even easier by enabling seamless real-time data integration from the Intercom platform into your analytics systems. The Intercom Reader allows you to connect directly to your Intercom platform and read data from user-defined tables. Striim 5.0s What Does It Do? How Does Striim Add Value?

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Data Engineering Podcast

MAY 15, 2022

Summary Industrial applications are one of the primary adopters of Internet of Things (IoT) technologies, with business critical operations being informed by data collected across a fleet of sensors. What kinds of analysis are you performing on the collected data? Closing Announcements Thank you for listening!

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Snowflake

JULY 31, 2024

Academic medical centers (AMCs) are a critical keystone of healthcare systems worldwide. alone, there are more than 230 active AMCs , and a significant number are part of a health system. Each of these data types can require specialized software packages, hardware environments and data processing techniques. In the U.S.

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