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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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

Data Engineering Podcast

FEBRUARY 25, 2018

Summary One of the sources of data that often gets overlooked is the systems that we use to run our businesses. This data is not used to directly provide value to customers or understand the functioning of the business, but it is still a critical component of a successful system.

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Cloudera

SEPTEMBER 15, 2021

That’s where you find the ability to empower IoT devices to respond to events in real time by capturing and analyzing the relevant data. Edge computing relies on squeezing the power and functionality of a data center into a micro site as close to data sources as possible to enable real-time tasks. Real-time Demands.

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Medical Retail Datasets Algorithm 125

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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Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

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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.

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Knowledge Hut

MAY 3, 2024

Kafka offers better fault tolerance because of its event-driven processing. Its interoperability with other kinds of systems, however, might appear to be extremely difficult. Processing Type Kafka analyses events as they often take place. A continuous processing model is an outcome.

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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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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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Cloudera

APRIL 15, 2019

While Cloudera Flow Management has been eagerly awaited by our Cloudera customers for use on their existing Cloudera platform clusters, Cloudera Edge Management has generated equal buzz across the industry for the possibilities that it brings to enterprises in their IoT initiatives around edge management and edge data collection.

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Data Engineering Podcast

FEBRUARY 24, 2020

Are you spending too much time maintaining your data pipeline? Snowplow empowers your business with a real-time event data pipeline running in your own cloud account without the hassle of maintenance. We have partnered with organizations such as O’Reilly Media, Corinium Global Intelligence, ODSC, and Data Council.

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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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Netflix Tech

JUNE 4, 2019

We were able to meaningfully improve both the predictability and performance of these containers by taking some of the CPU isolation responsibility away from the operating system and moving towards a data driven solution involving combinatorial optimization and machine learning. can we actually make this work in practice?

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Confluent

JUNE 13, 2019

You might think that data collection in astronomy consists of a lone astronomer pointing a telescope at a single object in a static sky. While that may be true in some cases (I collected the data for my Ph.D. thesis this way), the field of astronomy is rapidly changing into a data-intensive science with real-time needs.

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U-Next

OCTOBER 20, 2022

For instance, if you’re marketing premium spirits and only train your AI using data that mimics beer drinkers’ behavior, the results will be highly wrong and distorted. The data utilized to train the ML models is a major contributor to these biases. The source material is not the only way bias can enter data.

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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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AltexSoft

MAY 12, 2022

The approach finds application in security systems for user authentication. Systems like Audio Analytic ‘listen’ to the events inside and outside your car, enabling the vehicle to make adjustments in order to increase a driver’s safety. It offers a non-invasive type of remote patient monitoring to detect events like falling.

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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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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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Data Engineering Podcast

SEPTEMBER 19, 2021

This brings with it a unique set of challenges for data collection, data management, and analytical capabilities. In this episode Jillian Rowe shares her experience of working in the field and supporting teams of scientists and analysts with the data infrastructure that they need to get their work done.

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Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. You need to think about the whole model lifecycle.

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Towards Data Science

APRIL 3, 2023

From Enormous Data back to Big Data Say you are tasked with building an analytics application that must process around 1 billion events (1,000,000,000) a day. and what you are processing (what does the data look like)? Enabling these capabilities all began with the declaration of the system scenario. reference).

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DoorDash Engineering

AUGUST 15, 2023

But these signals almost entirely rely on application-level instrumentation, which can leave gaps or conflicting semantics across different systems. Here we will take a look at how we built BPFAgent, the process of building and maintaining its probes, and how various DoorDash teams have used the data collected.

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Workfall

MARCH 7, 2023

Reading Time: 6 minutes In order to create a Yew web application, one must create mechanisms to allow end users to interact with the system and provide data via online forms. Yew offers Rust’s rich type ecosystem which can be a great tool when it comes to ensuring data integrity on the client side. What Is Form Handling?

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PostgreSQL Database AWS Data Collection 79

Engineering at Meta

NOVEMBER 12, 2024

We’re sharing insights into our own cryptographic monitoring system, including challenges faced in its implementation, with the hope of assisting others in the industry aiming to deploy cryptographic monitoring at a similar scale. From there, data persists in Scuba and Hive , Meta’s short-term and long term data stores, respectively.

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Algorithm Datasets Coding Java 90

ProjectPro

JUNE 28, 2016

To explain Apache Kafka in a simple manner would be to compare it to a central nervous system than collects data from various sources. This data is constantly changing, and is voluminous. This data can be anything from clickstream data, activity/ web logs, consumer data, etc.

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Monte Carlo

APRIL 27, 2023

The Rise and Fall of CDPs Legacy CDPs are bundled solutions that collect and consolidate customer event data into a single user profile. They then give marketing teams an easy way to visually define custom audiences and map customer data to downstream systems.

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Striim

SEPTEMBER 11, 2024

Here are six key components that are fundamental to building and maintaining an effective data pipeline. Data sources The first component of a modern data pipeline is the data source, which is the origin of the data your business leverages. Continuous replication via CDC is an event driven architecture.

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Data Engineering Podcast

SEPTEMBER 18, 2022

In this episode Tommy Yionoulis shares his experiences working in the service and hospitality industries and how that led him to found OpsAnalitica, a platform for collecting and analyzing metrics on multi location businesses and their operational practices. Can you describe how the OpsAnalitica system is implemented?

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Knowledge Hut

JUNE 4, 2024

Objectives of Cyber Security Planning Most business operations run on the internet, revealing their data and resources to various cyber threats. Since the data and system resources are the pillars upon which the Organization operates, it goes without saying that a threat to these entities is indeed a threat to the Organization itself.

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Knowledge Hut

JUNE 26, 2023

Use Stack Overflow Data for Analytic Purposes Project Overview: What if you had access to all or most of the public repos on GitHub? As part of similar research, Felipe Hoffa analysed gigabytes of data spread over many publications from Google's BigQuery data collection. Which queries do you have?

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Knowledge Hut

MAY 31, 2023

These projects typically involve a collaborative team of software developers, data scientists, machine learning engineers, and subject matter experts. The development process may include tasks such as building and training machine learning models, data collection and cleaning, and testing and optimizing the final product.

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Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use. Infrastructure.

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Knowledge Hut

JANUARY 18, 2024

Artificial Intelligence, at its core, is a branch of Computer Science that aims to replicate or simulate human intelligence in machines and systems. These streams basically consist of algorithms that seek to make either predictions or classifications by creating expert systems that are based on the input data.

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Netflix Tech

MARCH 25, 2019

Finally, imagine yourself in the role of a data platform reliability engineer tasked with providing advanced lead time to data pipeline (ETL) owners by proactively identifying issues upstream to their ETL jobs. Let’s review a few of these principles: Ensure data integrity ?—?Accurately Enable seamless integration?—?

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Knowledge Hut

JULY 4, 2023

By analyzing historical patterns and trends in the data, algorithms can learn and make predictions about future outcomes or events. It involves extracting meaningful features from the data and using them to make informed decisions or predictions. Prediction and Forecasting: It can be used for predictive modeling and forecasting.

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