Towards Data Science

JUNE 19, 2023

Photo by CHUTTERSNAP on Unsplash This article is about Meerschaum Compose , a tool for defining ETL pipelines in YAML and a plugin for the data engineering framework Meerschaum. Note: Compose will tag pipes with the project name. An example Meerschaum Compose project for ETL on weather data.

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PostgreSQL SQL Python Project 83

LinkedIn Engineering

MARCH 21, 2023

This dual approach helps grow the taxonomy at scale while ensuring the skills data meets our required quality and standards. This can introduce different types of noise and varying data quality. Human curation The connected skills taxonomy is curated by a combination of human taxonomists and machine learning.

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Building Recruitment Machine Learning Deep Learning 85

Netflix Tech

JANUARY 25, 2023

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. Annotations Sometimes people describe annotations as tags but that is a limited definition. Teams should be able to define their data model for annotation.

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Algorithm Media Metadata Data Ingestion 113

François Nguyen

JANUARY 23, 2021

or why you should have a look at Data Observability ! This article is the second part on how Airbnb is managing data quality : “Part 2 — A New Gold Standard” The first part can be found here and it was just good principles about roles and responsabilities. Welcome to this strange way of managing data quality !

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Christophe Blefari

SEPTEMBER 28, 2023

Make your data stack take-off ( credits ) Hello, another edition of Data News. This week, we're going to take a step back and look at the current state of data platforms. What are the current trends and why are people fighting around the concept of the modern data stack. Is the modern data stack dying?

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Ripple Engineering

MARCH 30, 2023

Tracking models and all associated data is helpful in tracking performance over time, backtesting experiments and A/B testing. GitLab also has our CI-CD pipeline to deploy ML services which makes it crucial to have optimal synergy between GitlLab and Databricks. Each cluster has a service account that has access to the requisite data.

Machine Learning 98

Machine Learning AWS Metadata Data Collection 98

Snowflake

DECEMBER 19, 2023

The best marketing is truly data-driven, creating powerful product promotions and offers through an understanding of customer needs and preferences. than reading data insights from a beautiful dashboard. It’s a potentially cumbersome and time-consuming process that too often requires moving or sharing access to sensitive customer data.

Building 77

Building Pipeline-centric Database-centric Digital Media 77

Data Engineering Podcast

DECEMBER 21, 2020

Summary Data governance is a term that encompasses a wide range of responsibilities, both technical and process oriented. One of the more complex aspects is that of access control to the data assets that an organization is responsible for managing. If you hand a book to a new data engineer, what wisdom would you add to it?

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Data Governance Government Data Lake Banking 130

Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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Data Engineering Podcast

JUNE 29, 2020

This was a great conversation about the complexities of working in a niche domain of data analysis and how to build a pipeline of high quality data from collection to analysis. If you hand a book to a new data engineer, what wisdom would you add to it? Can you start by describing what you are building at Audio Analytic?

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Data Collection Management High Quality Data Metadata 100

dbt Developer Hub

JANUARY 23, 2023

Testing the quality of data in your warehouse is an important aspect in any mature data pipeline. One of the biggest blockers for developing a successful data quality pipeline is aggregating test failures and successes in an informational and actionable way. However, ensuring actionability can be challenging.

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Metadata High Quality Data SQL Data Integration 52

Data Engineering Weekly

JUNE 4, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Do you need data/ metrics at all? Perhaps unit test the pipeline?

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Workfall

AUGUST 29, 2023

Python is widely used in web development, data analysis, artificial intelligence, automation, scientific computing, and more, making it a go-to choice for developers worldwide. It simplifies the process of extracting data from web pages, allowing developers to navigate the HTML tree and locate specific elements effortlessly.

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Python Pipeline-centric Programming Language Coding 93

phData: Data Engineering

OCTOBER 12, 2022

This documentation can give different users insight into where data came from, what the profile of the data is, what the SQL looked like, and the DAG to know where the data is being used. It allows you to tag which final models are being used for a particular data product or dashboard.

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Cloud Metadata SQL Data Warehouse 52

Snowflake

OCTOBER 25, 2023

All of these solutions have a common denominator with today’s modern organizations: a robust, transparent and scalable data strategy, and the prerequisite to AI is the heartbeat of modern marketing: customer data. Question #1: What kind of data are you using to train your AI models? And how are you collecting it?

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Government Accessible Accessibility Technology 82

Netflix Tech

SEPTEMBER 29, 2022

years, its usage has increased, and Timestone is now also the priority queueing engine backing Conductor , our general-purpose workflow orchestration engine, and BDP Scheduler , the scheduler for large-scale data pipelines. We then codify this prefix as a Redis hash tag. Over the past 2.5

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Systems Metadata Media Kafka 85

Data Engineering Podcast

DECEMBER 17, 2017

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. How are metrics identified in Siri and is there any support for tagging? What is SiriDB and how did the project get started?

Database 100

Database Data Pipeline Data Engineering Data Engineer 100

Data Engineering Podcast

SEPTEMBER 14, 2020

On top of this foundation, the Hazelcast team has also built a streaming platform for reliable high throughput data transmission. In this episode Dale Kim shares how Hazelcast is implemented, the use cases that it enables, and how it complements on-disk data management systems.

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AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

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Data Lake Architecture IT Amazon Web Services 52

Striim

JANUARY 4, 2023

Companies need to analyze large volumes of datasets, leading to an increase in data producers and consumers within their IT infrastructures. These companies collect data from production applications and B2B SaaS tools (e.g., This data makes its way into a data repository, like a data warehouse (e.g., Mailchimp).

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PostgreSQL Data Warehouse Data Lake Data 52

Grouparoo

MARCH 30, 2021

Teams are centralizing their data in their data warehouse by loading data in and transforming it as necessary. sql files that, when run in the right order, create useful rollup tables or materialized views of the data. Reverse ETL is taking data from the warehouse and writing it back to line-of-business tools.

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Data Warehouse SQL Project Database 52

Data Engineering Podcast

OCTOBER 12, 2020

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it?

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Business Intelligence BI Consulting Data Ingestion 100

Netflix Tech

APRIL 27, 2023

Atlas is an in-memory time-series database that ingests multiple billions of time-series per day and retains the last two weeks of data. Moreover, common database optimizations like caching recently queried data don’t really work for alerting queries because, generally speaking, the last received datapoint is required for correctness.

Database 115

Database Architecture Consulting Systems 115

Cloudera

JUNE 15, 2021

We can run the quickstart environment, which is a Docker container we can run locally or within a pipeline, or we can install the dependencies on a Linux machine in our data center infrastructure. Which security features we wish to enable – Kerberos, TLS, HDFS Transparent Data Encryption , LDAP integration, etc.

Cloud 81

Cloud AWS Kafka Management 81

Monte Carlo

AUGUST 31, 2021

With the rise of data platforms and the data-as-a-product mentality, building more reliable processes and workflows to handle data quality has emerged as a top concern for data engineers. What is a data engineer to do? Maintain a working record of affected data assets or anomalies. The rest is education.

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Data Pipeline Software Engineer Software Engineering Data 52

Netflix Tech

NOVEMBER 13, 2023

Music information retrieval There are a few studio use cases where music activity metadata is important, including quality-control (QC) and at-scale multimedia content analysis and tagging. To evaluate and benchmark our dataset, we manually labeled 20 audio tracks from various TV shows which do not overlap with our training data.

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Datasets Metadata Algorithm Architecture 89

Knowledge Hut

JUNE 20, 2023

A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions. Facial reorganization, social media optimization, etc.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Towards Data Science

APRIL 6, 2023

Today’s post follows the same philosophy: fitting local and cloud pieces together to build a data pipeline. And, when it comes to data engineering solutions, it’s no different: They have databases, ETL tools, streaming platforms, and so on — a set of tools that makes our life easier (as long as you pay for them). not sponsored.

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AWS Data Pipeline Amazon Web Services Python 82

Cloudera

AUGUST 18, 2021

Data Lifecycle Management: The Key to AI-Driven Innovation. The hard part is to turn aspiration into reality by creating an organization that is truly data-driven. That way, the data can continue generating actionable insights. . Rethinking the Data Lifecycle. It requires rethinking the data lifecycle itself. .

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Medical Hospitality Data Lake Healthcare 87

AltexSoft

AUGUST 25, 2021

Specifics of data used in NLP. Both in daily life and in business, we deal with massive volumes of unstructured text data : emails, legal documents, product reviews, tweets, etc. Another way to handle unstructured text data using NLP is information extraction (IE). Rule-based NLP — great for data preprocessing.

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Process Deep Learning Datasets Machine Learning 139

Snowflake

AUGUST 21, 2023

With demonstrable success across a range of industries, organizations are increasingly pursuing cutting-edge data mesh architectures to enhance self-service data use. Data-as-a-product: By considering data resources through a product lens, teams can adopt practices centered around quality and ease of use.

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Pipeline-centric Architecture Government Data Architect 52

Knowledge Hut

MARCH 13, 2024

Wondering what is a big data engineer? As the name suggests, Big Data is associated with ‘big’ data, which hints at something big in the context of data. Big data forms one of the pillars of data science. Big data has been a hot topic in the IT sector for quite a long time.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 13, 2024

Wondering what is a big data engineer? As the name suggests, Big Data is associated with ‘big’ data, which hints at something big in the context of data. Big data forms one of the pillars of data science. Big data has been a hot topic in the IT sector for quite a long time.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. containing data that may have to be used to enrich the streaming data.

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Process Kafka SQL Machine Learning 80

phData: Data Engineering

OCTOBER 4, 2022

You’ve spent a lot of time tagging your code to optimize your data refreshes, and while your refreshes run quickly, your deployments aren’t. Optimize dbt Model Refreshes What about optimizing your build to only run models that actually have data that is more recent than the last run? Our team of data experts are happy to assist.

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Knowledge Hut

DECEMBER 25, 2023

We are also required to know about DevOps, which is a practice of harmonizing development and operations whereby the entire pipeline from development, testing, deployment, continuous integration, and feedback is automated. These frameworks are generally used to create API endpoints, which are used to fetch or store data in the database.

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Java Database PostgreSQL Project 98

Precisely

MAY 22, 2023

Studies show that just over a quarter of victims ultimately choose to make ransom payments to unlock their data. Source: Institute for Security + Technology ) The hackers have a clear understanding of the value of corporate data and of each organization’s ability to pay. The cost of cybersecurity attacks is staggering.

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Accessible Accessibility Systems Technology 52