LinkedIn Engineering

JANUARY 19, 2024

This multi-entity handover process involves huge amounts of data updating and cloning. Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. Push for eventual success of the request.

Recruitment 88

Recruitment Data Process Process Kafka 88

Netflix Tech

AUGUST 1, 2022

A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A stream processing) is one of the key factors that enable Netflix to maintain its leading position in the competition of entertaining our users.

Process 109

Process Transportation Kafka Entertainment 109

AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. What is Natural Language Processing? Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech.

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Process Deep Learning Datasets Machine Learning 139

Data Engineering Weekly

NOVEMBER 11, 2024

Slack provides an excellent overview of this process. The blog outlines two main approaches for building these models: the Unified Embedding Decoder Architecture and the Cross-Modality Attention Architecture. The blog narrates how LinkedIn achieved Close the gap between allocated and utilized executor memory.

Data Engineering 57

Data Engineering Data Engineer Engineering Datasets 57

Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. If some terminologies in the blog around Machine Learning seems unfamiliar to you, don’t worry we have the Best Data Science courses to help you out.

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

Netflix Tech

NOVEMBER 12, 2024

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Datasets 89

Datasets Computer Science Systems Kafka 89

Cloudera

SEPTEMBER 18, 2024

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making.

Datasets 84

Datasets Retail Healthcare Finance 84

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. It involves bringing together people, processes, and technology to enable data-driven decision making and improve the efficiency of data-related workflows.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI. This is where the processes are filtered and analyzed.

Architecture 52

Architecture Database-centric Process BI 52

Edureka

AUGUST 2, 2023

Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis? What Does a Data Processing Analyst Do? What does a Data Processing Analysts do ?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. A single hospital makes many captures a day, producing terabytes of such data to store and process. Much like Spark, its module ray.data is focused on loading and processing data as scale. width , spec.

Medical 60

Medical Process Cloud Bytes 60

Pinterest Engineering

OCTOBER 11, 2024

In Part 2 of our blog series, we described how we were able to integrate Ray(™) into our existing ML infrastructure. In this blog post, we will discuss a second type of popular application of Ray(™) at Pinterest: offline batch inference of ML models. Dataset execution is pipelined so that multiple execution stages can run in parallel.

Datasets 63

Datasets Software Engineering Software Engineer Metadata 63

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. However, the ultimate goal is simple: to prepare data for immediate use.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. In this blog, we will focus on a PostgreSQL database. Specifically, in this dataset, 1 represents “setosa,” 2 represents “versicolor,” and 3 represents “virginica.”

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Christophe Blefari

APRIL 19, 2024

It was trained on a large dataset containing 15T tokens (compared to 2T for Llama 2). This is super interesting because it details important steps of the generative process. This blog shows how you can use Gen AI to evaluate inputs like translations with added reasons. — A great blog to answer a great question.

MySQL 130

MySQL Data Datasets SQL 130

Data Engineering Weekly

JULY 7, 2024

The blog highlights the advantages of GNN over traditional machine learning models, which struggle to discern relationships between various entities, such as users and restaurants, and edges, such as order. The blog gives an overview of statistical techniques used in drift detection.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

ProjectPro

JANUARY 15, 2021

And honestly, there are a lot of real-world machine learning datasets around you that you can opt to start practicing your fundamental data science and machine learning skills, even without having to complete a comprehensive data science or machine learning course. Table of Contents What is a dataset in machine learning?

Machine Learning 40

Machine Learning Datasets Retail Banking 40

Knowledge Hut

FEBRUARY 29, 2024

Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

phData: Data Engineering

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Efficiency through being able to streamline data storage and retrieval processes.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

Data Integration 52

Data Integration Process Data Validation Data Governance 52

Maxime Beauchemin

JANUARY 7, 2018

Batch data processing  — historically known as ETL —  is extremely challenging. In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. The greater the claim made using analytics, the greater the scrutiny on the process should be.

Data Engineering 183

Data Engineering Data Engineer Data Process Process 183

Cloudyard

NOVEMBER 17, 2024

With built-in and custom metrics, DMFs simplify the process of validating large datasets and identifying anomalies. In this blog, we will explore a practical use case of DMFs to monitor the quality of transactional data. Ensuring data accuracy and validity is critical for downstream analytics and decision-making processes.

Datasets 52

Datasets Data Government Data Validation 52

Data Engineering Weekly

JULY 28, 2024

The blog is an excellent summarization of the common patterns emerging in GenAI platforms. Switching from Apache Spark to Ray improves compact 12X larger datasets than Apache Spark, improves cost efficiency by 91%, and processes 13X more data per hour.

Data Engineering 109

Data Engineering Data Engineer Engineering Database-centric 109

ProjectPro

JANUARY 25, 2022

Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things. Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. Why use PySpark?

Big Data 52

Big Data Data Process Process Kafka 52

Cloudyard

OCTOBER 1, 2024

Read Time: 3 Minute, 57 Second Pandas, a popular Python library, is a fantastic tool for small to moderately sized data, but it struggles with large-scale datasets. This blog will explore the key differences between Pandas DataFrames and Snowpark DataFrames (enhanced by Modin ), demonstrate their respective strengths.

Datasets 52

Datasets Big Data Data Warehouse Cloud 52

ProjectPro

FEBRUARY 16, 2023

At the core of such applications lies the science of machine learning, image processing, computer vision, and deep learning. As an example, consider the Facial Image Recognition System, it leverages the OpenCV Python library for implementing image processing techniques. What is OpenCV Python?

Python 98

Python Process Deep Learning Algorithm 98

Netflix Tech

OCTOBER 8, 2024

In previous blog posts, we introduced the Key-Value Data Abstraction Layer and the Data Gateway Platform , both of which are integral to Netflix’s data architecture. Configurability : TimeSeries offers a range of tunable options for each dataset, providing the flexibility needed to accommodate a wide array of use cases.

Bytes 94

Bytes Datasets Metadata Data 94

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. In the pre-data-lake era, traditional data warehouses were limited by disk space and processing power. This growing demand has found a natural synergy with the rise of the data lake.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Datasets 98

Cloudera

NOVEMBER 13, 2024

Although the benefits of fine tuning are substantial, the process of preparing, training, evaluating, and deploying fine-tuned LLMs is a lengthy LLMOps workflow that organizations handle differently. Fine Tuning Studio enables users to track the location of all datasets, models, and model adapters for training and evaluation.

Datasets 61

Datasets Machine Learning Coding Data Preparation 61

Data Engineering Weekly

JULY 14, 2024

The blog highlights the reasoning behind selecting dbt and Dagster and some of the key improvements while adopting them, such as handling race conditions in dbt incremental update and bulk backfilling with Dagster. Streaming execution to process a small chunk of data at a time. The buffer manager caches as many pages as possible.

Data Engineering 98

Data Engineering Data Engineer Engineering Unstructured Data 98

Engineering at Meta

OCTOBER 3, 2024

The dataset and code are available now on GitHub. Governments in advanced economies can rely on a variety of sources including tax records or census datasets to better estimate their population and make informed decisions on the delivery of services. However, in other parts of the world, accurate population data is hard to come by.

Datasets 65

Datasets Government Banking Programming 65

DareData

JUNE 11, 2024

In this blog post, we are finally going to bring out the big guns and train our first computer vision algorithm. Although we’ll use a simple dataset here (making it accessible for anyone to run this code on their computer), the principles we’ll see can be applied to other image classification algorithms. ok, hard to visualize!

Algorithm 52

Algorithm Datasets Deep Learning Architecture 52

Team Data Science

NOVEMBER 28, 2020

As a data scientist, I always felt a missing link between my developed models and putting them in the production process. During our first week, Andreas helped us navigate the industry that interests each of us, and this is how we picked a dataset to work on for the next following weeks. Stay tuned!

Engineering 130

Engineering Datasets Data Data Engineer 130

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. Get the Dataset. Introduction.

Machine Learning 137

Machine Learning Datasets Data Science Raw Data 137

Team Data Science

MARCH 15, 2020

I am taking you through my recent experience to find a dataset for my project. I defined a few sources in my earlier blog post, which will give a sneak peek of techniques to extract industries. Criteria Define a simple layout to your dataset with elements like size, type of columns, format. Date formatted to yyyy/mm/dd.

Insurance 130

Insurance Datasets Banking Finance 130

Pinterest Engineering

JANUARY 4, 2024

This blog post goes into the details of how we built this massively scalable, highly available wide column database using RocksDB, and provides information about the data model, APIs, and key features. Individual rows constitute a dataset. Row key uniquely identifies a row in a dataset. no in-place modifications are done).

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Database Building Datasets Relational Database 93