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Data Analysis / Big Data

Data Analysis / Big Data

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Лучшие посты по анализу данных и работе с Big Data на русском и английском языке Разместить рекламу: @tproger_sales_bot Правила общения: https://tprg.ru/rules Другие каналы: @tproger_channels

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Improve reusability and security using Amazon Athena parameterized queries Read: https://aws.amazon.com/blogs/big-data/improv
Improve reusability and security using Amazon Athena parameterized queries Read: https://aws.amazon.com/blogs/big-data/improve-reusability-and-security-using-amazon-athena-parameterized-queries/

Day 3/100 Deltalake - [ Intro and Quick Start ] key features - ACID transactions schema enforcement on writes Unification of
Day 3/100 Deltalake - [ Intro and Quick Start ] key features - ACID transactions schema enforcement on writes Unification of batch and streaming - A table in Delta Lake is a batch table as well as a streaming source and sink. Time travel Supports merge, upd... Read: https://rawdatareaders.hashnode.dev/day-3100

Federated access to Amazon Redshift clusters in AWS China Regions with Active Directory Federation Services Read: https://aws
Federated access to Amazon Redshift clusters in AWS China Regions with Active Directory Federation Services Read: https://aws.amazon.com/blogs/big-data/federated-access-to-amazon-redshift-clusters-in-aws-china-regions-with-active-directory-federation-services/

kNN Model Complexity Introduction K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on the Supervi
kNN Model Complexity Introduction K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on the Supervised Learning technique. It assumes the similarity between the new case/data and available cases and puts the new case into the category that is mo... Read: https://blog.learnml.xyz/knn-model-complexity

Histogram - Visualize how frequently data in each class occur in the dataset Introduction In this article are going to see ab
Histogram - Visualize how frequently data in each class occur in the dataset Introduction In this article are going to see about what is a histogram graph and different interpretations of the histogram graphs. Histograms group the data in bins and are the fastest way to get an idea about the distribution of each attribute in ... Read: https://blog.learnml.xyz/histogram-visualize-how-frequently-data-in-each-class-occur-in-the-dataset

End-to-end data engineering project - batch edition Read: https://www.startdataengineering.com/post/data-engineering-project-
End-to-end data engineering project - batch edition Read: https://www.startdataengineering.com/post/data-engineering-project-e2e/

Как в PayPal разработали Dione — Open-source-библиотеку индексирования данных для HDFS и Spark Maksym Kaharlytsky on Unsplash Команда VK Cloud Solutions перевела историю о том, как инженеры PayPal столкнулись с проблемой обработки данных. Если пользователю требовалось получить определенную строку или выполнить многострочный запрос, данные нужно было дублировать, а для их обработки использовать отдельный стек технологий. Чтобы этого избежать, в PayPal разработали новую Open-source-библиотеку, которая позволяет быстрее выполнять многострочные и однострочные выборки из больших данных. Во время работы над библиотекой они создали новый формат хранения индексов Avro B-Tree и для пользователей Spark реализовали API на Scala и Python. Читать: https://habr.com/ru/post/656777/

Types of MEAN - ( Measure of Central Tendency ) Introduction To represent a dataset as a 1-number summary, we use the central
Types of MEAN - ( Measure of Central Tendency ) Introduction To represent a dataset as a 1-number summary, we use the central tendency measure. There exist three central tendency measures i.e. Mean, Median & Mode. Why was there a need for these three measures when only one (Mean) could have done t... Read: https://blog.learnml.xyz/types-of-mean-measure-of-central-tendency

Визуализация данных с помощью веб-фреймворка Dash (часть 2) В предыдущей части статьи мы разбирали, что такое dash в общем, и создавали одностраничный дэшборд, взяв за основу датасет драгоценных камней с kaggle. Но! Задачи, которые падают на нас ,не всегда просты и не всегда возможно ограничить себя  одной страницей на Дашборде. В этой статье я покажу, как создать многостраничный дэшборд, используя sidebar в качестве навигационного элемента, и наполнить страницы разного рода контентом. Читать: https://habr.com/ru/post/656621/

Day 2/100 HDFS [Hadoop Distributed File System] - Part 2 Snapshots Snapshots lets you save the current state of filesystem, s
Day 2/100 HDFS [Hadoop Distributed File System] - Part 2 Snapshots Snapshots lets you save the current state of filesystem, so that rollbacks while upgrade are possible. Only one snapshot can exists, basically it reads existing and creates new checkpoint with... Read: https://rawdatareaders.hashnode.dev/day-2-of-100

Загрузка stage слоя DWH. Часть 3 Каждый разработчик потоков Nifi сталкивается с тем, что через некоторое время потоки начинают повторятся. Бизнес хочет получать данные по одному расписанию, а к определённым моментам времени. И возникает ситуация, когда управлять большим разросшимся потоком становится неудобно, сложно. Устранять ошибку проектирования приходится в десятках процессоры групп. И так далее... Рассмотрим подход к параметризованному потоку загрузки, универсальному в сложившемся окружении, при обкатанных правилах формирования DWH, выполнения запросов к источникам, интервалам загрузки. Читать: https://habr.com/ru/post/656891/

Normalization Vs Standardization Introduction Feature Scaling is one of the most important data preprocessing steps in machin
Normalization Vs Standardization Introduction Feature Scaling is one of the most important data preprocessing steps in machine learning. Algorithms that compute the distance between the features are biased towards numerically larger values if the data is not scaled. Tree-based algor... Read: https://blog.learnml.xyz/normalization-vs-standardization

Getting started with a Data Challenge: Thinking like an Analyst Probelem Scenario: Excited about a data analytics challenge, you signed up and ready to put your analytics skills into good use. But halfway through the process, you blank out. You have no idea how to proceed with the challenge and how to position y... Read: https://aviatorifeanyi.hashnode.dev/getting-started-with-a-data-challenge-thinking-like-an-analyst-cl11irayo017xlgnvch9kfloz

Permutation Importance -Machine Learning Explainability Introduction Machine learning models often act as black boxes, meanin
Permutation Importance -Machine Learning Explainability Introduction Machine learning models often act as black boxes, meaning that they can make good predictions but it is difficult to fully comprehend the decisions that drive those predictions. Gaining insights from a model is not an easy task, despite ... Read: https://blog.learnml.xyz/permutation-importance-machine-learning-explainability

Day 1/100 HDFS - [Hadoop Distributed File System] HDFS architecture looks like this - NameNode holds all the metadata about f
Day 1/100 HDFS - [Hadoop Distributed File System] HDFS architecture looks like this - NameNode holds all the metadata about files and directory structure and then there are DataNodes which basically hold files in the form of blocks so DataNode holds blocks o... Read: https://rawdatareaders.hashnode.dev/day-1

Interview Jitters Recently I was shortlisted for a data analyst position interview, and I felt it is important to share the e
Interview Jitters Recently I was shortlisted for a data analyst position interview, and I felt it is important to share the experience to familiarize you with some of the questions they asked me to confirm my competence and level of skills. Before we get into it, do y... Read: https://chalo.hashnode.dev/interview-jitters

Accelerate your data warehouse migration to Amazon Redshift – Part 5 Read: https://aws.amazon.com/blogs/big-data/part-5-accel
Accelerate your data warehouse migration to Amazon Redshift – Part 5 Read: https://aws.amazon.com/blogs/big-data/part-5-accelerate-your-data-warehouse-migration-to-amazon-redshift/

Machine Learning | Underfitting and Overfitting [Theory] Introduction Let us consider that we are designing a machine learnin
Machine Learning | Underfitting and Overfitting [Theory] Introduction Let us consider that we are designing a machine learning model. A model is said to be a good machine learning model if it generalizes any new input data from the problem domain in a proper way. This helps us to make predictions in the fu... Read: https://blog.learnml.xyz/machine-learning-or-underfitting-and-overfitting-theory

Insertion Sorting Algorithm Introduction Insertion sort is a simple and efficient comparison sort. In this algorithm, each it
Insertion Sorting Algorithm Introduction Insertion sort is a simple and efficient comparison sort. In this algorithm, each iteration removes an element from the input data and inserts it into the correct position in the list is sorted. Insertion Sort repeatedly invokes an inser... Read: https://blog.learnml.xyz/insertion-sorting-algorithm

Эволюция рекомендаций ресторанов в Delivery Club. Часть 1 Всем привет! Меня зовут Иван Максимов, я работаю Lead Data Scientist’ом в команде рекомендаций и A/B-тестирования Delivery Club. Это первая из серии статей про нашу рекомендательную систему. Я расскажу о том, как мы определили проблемы предыдущего подхода к рекомендациям, и как начали строить новый: с оптимизацией рекомендаций сразу под несколько бизнес-метрик. Статья будет интересна data scientist’ам и менеджерам продуктов, которые хотят с нуля построить систему рекомендации контента. Читать: https://habr.com/ru/post/656505/