Knowledge Hut

FEBRUARY 29, 2024

Being a data scientist means constantly growing, enabling businesses to become more data-propelled, and learning newer trends and tools. There are various excellent resources in data science that can help you to develop your skillset. So, having the right knowledge of tools and technology is important for handling such data.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Christophe Blefari

MARCH 22, 2024

Friday routine ( credits ) It's Friday and it's Data News. I don't go into too much detail about the magic of Data News, but every Friday is the same. Exploration, Friday morning I read the last 7 days of 2 Twitter lists ( MDS , Data voices ) and I open interesting stuff in tabs. on April 10.

Electronics 130

Electronics Media Data Python 130

Precisely

DECEMBER 20, 2022

Trusted data fuels stronger financial services. With that data, organizations in this sector are able to better understand customers and improve experiences, fight financial crimes, reduce compliance risks, optimize branch performance, and stay ahead of the competition. Data governance provides the answer.

Data Governance 52

Data Governance Government Hadoop Big Data 52

KDnuggets

NOVEMBER 30, 2023

The blog discusses five platforms designed for data scientists with specialized capabilities in managing large datasets, models, workflows, and collaboration beyond what GitHub offers.

Data Science 118

Data Science Project Datasets Data 118

Christophe Blefari

AUGUST 4, 2023

Summer Edition ( credits ) This is the first article of the Data News Summer Edition: how to build a data platform. The modern data stack has been criticised a lot, a few are saying it's dead other are saying we are in the post-modern era. In this article we will try to design the fancy data stack for a batch usage.

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Google Cloud MongoDB NoSQL Data 225

Christophe Blefari

JANUARY 7, 2024

This edition of Data News will focus on the end of 2023 with a good retrospective about me and my activities—content and freelancing. My only target is, to be honest, to grow my blog, having 4000 people who trusted my enough to enter their email and validate the subscription is just crazy. More about on this soon.

Data 130

Data SQL Python Data Engineering 130

DataKitchen

MAY 10, 2024

Harnessing Data Observability Across Five Key Use Cases The ability to monitor, validate, and ensure data accuracy across its lifecycle is not just a luxury—it’s a necessity. Data Evaluation Before new data sets are introduced into production environments, they must be thoroughly evaluated and cleaned.

Data Ingestion 58

Data Ingestion Datasets Data Coding 58

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Raw Data 51

Raw Data Data Ingestion Datasets Data 51

DareData

FEBRUARY 28, 2024

In this post of the PyTorch Introduction, we’ll learn how to use custom datasets with PyTorch, particularly tabular, vision and text data PyTorch is one of the hottest libraries in the Deep Learning field right now. We’ve used few custom datasets in our examples and previous blog posts. Let’s start!

Datasets 52

Datasets Deep Learning Data Machine Learning 52

Pinterest Engineering

SEPTEMBER 12, 2023

Behind the scenes, hundreds of ML engineers iteratively improve a wide range of recommendation engines that power Pinterest, processing petabytes of data and training thousands of models using hundreds of GPUs. transformers) became standardized, ML engineers started to show a growing appetite to iterate on datasets.

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Data Process Process Datasets Scala 88

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. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

Data Engineering Weekly

APRIL 7, 2024

Poor data quality and unlcear data ownership remains the top challenges for the data teams. Data Mesh continuously gaining popularity among the enterprises. It is a stark difference from the Gartner report about data mesh. I guess only the time will tell who wins in the data mesh vs data fabric war.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

KDnuggets

AUGUST 24, 2022

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

Datasets 159

Datasets Data Machine Learning 159

Towards Data Science

JANUARY 7, 2024

Streamline Data Pipelines: How to Use WhyLogs with PySpark for Effective Data Profiling and Validation Photo by Evan Dennis on Unsplash Data pipelines, made by data engineers or machine learning engineers, do more than just prepare data for reports or training models. It lets you log all sorts of data.

Data Pipeline 81

Data Pipeline Hospitality Data Validation Datasets 81

Team Data Science

MARCH 15, 2020

I am taking you through my recent experience to find a dataset for my project. Industry Search To work with data, I need to narrow down the industry like health care, finance, insurance or other. I defined a few sources in my earlier blog post, which will give a sneak peek of techniques to extract industries.

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Insurance Datasets Banking Finance 130

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. This thought led me to my data engineering adventure. I am confident that learning data engineering will make me a better data scientist. Where did I start? Stay tuned!

Engineering 130

Engineering Datasets Data Data Engineering 130

Christophe Blefari

DECEMBER 31, 2023

Before moving on to the Data News, a bit of personal news, in December, I took part in the MotherDuck meetup in Berlin. End of January, on the 31st I'll speak at a Modern Data Stack conf in Paris, still about DuckDB, but this time in French. Enjoy this last 2023 Data News. How to know if your data team is successful?

Data 100

Data Cloud Storage Datasets Python 100

Data Engineering Weekly

MARCH 10, 2024

Editor’s Note: Chennai Meetup Wrap-Up & Preparation work started for DEWCon I am so grateful for the enthusiastic participants who made our Chennai Data Heroes- Community for Data Folks meetup vibrant! Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Fast, Safe Development and Deployment (#4) Introduction The integrity and functionality of new code, tools, and configurations during the development and deployment stages are crucial. This process is critical as it ensures data quality from the onset. Will I Create A Failed Deploy?

Data Ingestion 51

Data Ingestion Datasets Coding Data 51

ProjectPro

JANUARY 15, 2021

Undoubtedly, everyone knows that the only best way to learn data science and machine learning is to learn them by doing diverse projects. But yes, there is definitely no other alternative to data science and machine learning projects. Table of Contents What is a dataset in machine learning?

Datasets 40

Datasets Machine Learning Retail Banking 40

Uber Engineering

FEBRUARY 23, 2023

Data quality is of paramount importance at Uber, powering critical decisions and features. In this blog learn how we automated column-level drift detection in batch datasets at Uber scale, reducing the median time to detect issues in critical datasets by 5X.

Systems 93

Systems Datasets Data 93

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring (#2) Introduction Ensuring the accuracy and timeliness of data ingestion is a cornerstone for maintaining the integrity of data systems. This process is critical as it ensures data quality from the onset.

Data Ingestion 54

Data Ingestion Transportation High Quality Data Data Schemas 54

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Christophe Blefari

JUNE 9, 2023

Rethinking the newsletter ( credits ) Here's a new edition of the Data News newsletter. I can tease you that I'll create content about "Create a data platform in 2023", with live examples. The French version will be a bit different than Minds of data. Writing the newsletter was not an easy exercise.

Data 130

Data Government SQL Coding 130

databricks

MARCH 26, 2023

In today's business landscape, secure and cost-effective data sharing is more critical than ever for organizations looking to optimize their internal and external.

Datasets 73

Datasets Data 73

Workfall

JULY 18, 2023

Behind the scenes, a team of data wizards tirelessly crunches mountains of data to make those recommendations sparkle. As one of those wizards, we’ve seen the challenges we face: the struggle to transform massive datasets into meaningful insights, all while keeping queries fast and our system scalable.

Datasets 77

Datasets Entertainment Data Workflow Data 77

Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

Data Cleanse 52

Data Cleanse Data Pipeline Datasets Data Validation 52

Uber Engineering

AUGUST 5, 2021

Uber delivers efficient and reliable transportation across the global marketplace, which is powered by hundreds of services, machine learning models, and tens of thousands of datasets.

Transportation 145

Transportation Datasets Machine Learning Data 145

RandomTrees

FEBRUARY 2, 2024

GPT-based data engineering accelerators make the working of data more accessible. These accelerators use GPT models to do data tasks faster, fix any issues, and save a lot of time. GPT models change data in simple language and also provide summaries and explanations. It is the first AI-powered conversational data analyst.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Christophe Blefari

DECEMBER 30, 2022

💡 You can also read the 2021's must-read that I've done one year and half ago or how to learn data engineering that contains key articles to understand the field. Once again thank you everyone for your support this year and see you next week for the first Data News of 2023. Now let's jump to my selection.

Data Warehouse 130

Data Warehouse BI Data Machine Learning 130

Data Engineering Weekly

DECEMBER 10, 2023

RudderStack, one of the leading alternatives to Segment , is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Lackluster AI/ML results often stem from poor data quality. Visit rudderstack.com to learn more.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Data Engineering Weekly

MARCH 3, 2024

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

Rockset

JANUARY 19, 2024

Data mutability is the ability of a database to support mutations (updates and deletes) to the data that’s stored inside it. It’s a critical feature, especially in real-time analytics where data constantly changes and you need to present the latest version of that data to your customers and end users.

SQL 59

SQL Data Datasets Database 59

Databand.ai

AUGUST 30, 2023

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date.

Building 52

Building Data Cleanse Data Governance Datasets 52

Databand.ai

AUGUST 30, 2023

8 Data Quality Monitoring Techniques & Metrics to Watch Niv Sluzki August 30, 2023 What Is Data Quality Monitoring? Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Knowledge Hut

APRIL 25, 2024

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. It is especially true in the world of big data. It is especially true in the world of big data. What Are Big Data T echnologies?

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Big Data Technology NoSQL Hadoop 98

Pinterest Engineering

JULY 25, 2023

Soam Acharya | Data Engineering Oversight; Keith Regier | Data Privacy Engineering Manager Background Businesses collect many different types of data. Each dataset needs to be securely stored with minimal access granted to ensure they are used appropriately and can easily be located and disposed of when necessary.

Big Data 95

Big Data Accessible Accessibility Hadoop 95