Towards Data Science

JUNE 16, 2023

How to Identify Your Business-Critical Data Practical steps to identifying business-critical data models and dashboards and drive confidence in your data Source: synq.io This article has been co-written with Lindsay Murphy Not all data is created equal. There’s a good reason for this. Source: synq.io

BI 80

BI Data ETL Tools Machine Learning 80

Knowledge Hut

FEBRUARY 1, 2024

Today, we’ll talk about how Machine Learning (ML) can be used to build a movie recommendation system - from researching data sets & understanding user preferences all the way through training models & deploying them in applications. Let’s begin with all the aspects of movie recommendation using ML.

Systems 98

Systems Entertainment Algorithm Datasets 98

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?

Cloud Storage 147

Cloud Storage Big Data Hadoop SQL 147

Cloudera

OCTOBER 30, 2023

The legacy IT infrastructure to run the business operations — mainly data centers — has a deadline to shift to cloud-based services. The public cloud is increasingly becoming the preferred platform to host data analytics – related projects, such as business intelligence, machine learning (ML), and AI applications.

Cloud 80

Cloud Finance Cloud Computing Government 80

ProjectPro

JANUARY 24, 2023

SpaCy comes with two powerful functionalities, namely, Parts-of-speech (POS) Tagging and Named-Entity Recognition Tagging. Project Idea: NLP Project to Build a Resume Parser in Python using Spacy Gensim Gensim is the Python library used for vectorizing textual data before passing the data at the input of a machine learning model.

Python 52

Python Project Programming Language Data Mining 52

Snowflake

APRIL 29, 2024

Identification of potential threats through data analysis and risk assessment processes to shift toward more proactive risk management. This strategy must incorporate business impact analyses as well as backup and recovery plans in the event of a security incident or loss of access to data. or better) for data in transit.

Transportation 83

Transportation Data Governance Government Consulting 83

LinkedIn Engineering

MARCH 21, 2023

The Skills Graph uses the taxonomy to facilitate skills-first experiences across various models and products at LinkedIn. This includes several standardizers/models (e.g., This dual approach helps grow the taxonomy at scale while ensuring the skills data meets our required quality and standards.

Building 85

Building Recruitment Machine Learning Deep Learning 85

Yelp Engineering

APRIL 19, 2023

We need to tag, organize and rank online content to attain this goal. For this purpose, Yelp engineers have started using general embeddings on different data. It improves usability and efficiency for all kinds of model development. Yelp aims to offer easily accessible high-quality content.

Deep Learning 59

Deep Learning Accessible Accessibility Engineering 59

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.

Algorithm 113

Algorithm Media Metadata Data Ingestion 113

The Pragmatic Engineer

JANUARY 12, 2023

We cover one and a half out of eight topics in today’s subscriber-only issue, Inside Pollen's Transparent Compensation Data. In this week’s The Scoop, I analyzed this information and dissected it, going well beyond the raw data. To get this newsletter every week, subscribe here. Tech compensation numbers.

Software Engineer 181

Software Engineer Software Engineering Engineering Raw Data 181

Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. There was only one data team, two at most.

Data Pipeline 84

Data Pipeline SQL Data Architecture Data 84

Knowledge Hut

APRIL 24, 2024

React Portal is a first-class technique to render children into a Document Object Model (DOM) node existing outside the parent component's DOM hierarchy. Here are a few benefits of using React portals: React portals use context to streamline data transfer seamlessly. Let’s Start! What is React Portal?

Transportation 52

Transportation Coding Accessible Accessibility 52

Snowflake

APRIL 4, 2023

At Snowflake, we like data. And we appreciate people who also like data—and like working with it. Snowflake Marketplace is designed with that in mind: giving people and organizations a place to easily find, try, and buy data and applications that can help them build more and do more with data.

Cloud 52

Cloud Accessible Accessibility Project 52

Ripple Engineering

MARCH 30, 2023

Summary Managing the entire lifecycle of a machine learning (ML) model from inception to deployment in production can be a daunting task involving multiple systems and lots of moving parts. and we needed a managed solution that would help us deliver models to product use cases within a short amount of time, which led us to choose Databricks.

Machine Learning 98

Machine Learning AWS Metadata Data Collection 98

AltexSoft

AUGUST 25, 2021

Specifics of data used in NLP. Tools you can use to build NLP models. 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). Language modeling.

Process 139

Process Deep Learning Datasets Machine Learning 139

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It enables everything from reliable business logic to insightful decision-making and robust machine learning modeling. It is now the norm for tech companies to have a well-developed data platform. What and Where is Data Quality?

Big Data 84

Big Data Metadata Data Warehouse Data 84

Snowflake

OCTOBER 25, 2023

With the release of ChatGPT late last year, OpenAI supercharged the conversation around large language models (LLMs), marking 2023 as “the year of AI.” The protection of the brand’s customer data is paramount – customer data privacy, compliance, and governance should be the bedrock of a brand’s modern martech stack.

Government 87

Government Accessible Accessibility Technology 87

Precisely

DECEMBER 6, 2023

The European Union’s General Data Protection Regulation (commonly known as GDPR) came into effect on the 25th May 2018. It is important to any user or processor of personally identifiable information (PII) as this new law marks a seismic change in the way that organizations must protect consumers’ data.

Retail 64

Retail Data Systems Data Integration 64

LinkedIn Engineering

APRIL 6, 2023

This included tools like our internal LinkedIn Generative AI Playground, which allows engineers to explore Linkedin data with the advanced generative AI models from OpenAI and other sources. These are two really crucial tools that accelerated our generative AI exploration, and that we look forward to sharing more about in the future.

Accessible 94

Accessible Accessibility Technology Engineering 94

DareData

NOVEMBER 28, 2023

In today's data-driven world, machine learning has emerged as a transformative force, empowering organizations to extract valuable insights from vast amounts of data. As the scope of the models and the data continues to scale, the role of a Data Scientist has evolved accordingly in the last years.

Data Science 52

Data Science Medical Machine Learning Data 52

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. on BigQuery.

Metadata 52

Metadata High Quality Data SQL Data Integration 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.

Datasets 89

Datasets Metadata Algorithm Architecture 89

Snowflake

SEPTEMBER 13, 2023

Building your data product is only the beginning. Or maybe you just have some really unique data that you think might be of use to someone. As the data economy began to take off, “ What’s my data worth? Board members and company executives salivated at the thought of putting a line item for data on the balance sheet.

Food 100

Food Retail Hospitality Data 100

AltexSoft

AUGUST 3, 2021

No matter how big or small your machine learning (ML) project might be, the overall output depends on the quality of data used to train the ML models. Data annotation plays a pivotal role in the process. That said, data annotation is key in training ML models if you want to achieve high-quality outputs.

Datasets 59

Datasets High Quality Data Metadata Raw Data 59

Cloudera

DECEMBER 21, 2020

In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. In our data adventure we assume the following: . Company data exists in the data lake.

Banking 98

Banking Data Lake Data Data Warehouse 98

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

ETL Tools 79

ETL Tools Programming Language Datasets Data Pipeline 79

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?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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 80

Building Pipeline-centric Database-centric Digital Media 80

Cloudera

JUNE 27, 2023

During the COVID-19 pandemic, telcos made unprecedented use of data and data-driven automation to optimize their network operations, improve customer support, and identify opportunities to expand into new markets. There are savings to be made in modernizing the data stack itself, in addition to applying data across the enterprise.

Data Architecture 64

Data Architecture Architecture Data Governance Government 64

phData: Data Engineering

OCTOBER 12, 2022

The real power is the ability to run your models and view the outputs, or even have your SQL compiled to verify that your Jinja or SQL compiles into the correct model. This can be very useful when troubleshooting your models and is far easier than digging through the compiled models in the target folder.

Cloud 52

Cloud Metadata SQL Data Warehouse 52

Data Science Blog: Data Engineering

NOVEMBER 18, 2020

R programming is mostly preferred by statisticians, data miners, and software programmers who want to develop statistical software. Step 1- Select the website & the data you want to scrape. I picked this website “ [link] ” and want to scrape data of Top 50 sites in India.

R (Programming) 52

R (Programming) Programming Language Data Science Programming 52

Netflix Tech

OCTOBER 19, 2020

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. Traces collected from various microservices are ingested in a stream processing manner into the data store.

Building 93

Building Transportation Metadata Java 93

Snowflake

JUNE 14, 2023

Komodo Health is a technology platform company creating the new standard for real-world data and analytics by pairing the industry’s most complete view of patient encounters with enterprise software and machine learning that connects the dots between individual patient journeys and large-scale health outcomes.

Healthcare 52

Healthcare SQL Algorithm Architecture 52

AltexSoft

MARCH 18, 2022

In a nutshell, semi-supervised learning (SSL) is a machine learning technique that uses a small portion of labeled data and lots of unlabeled data to train a predictive model. Supervised learning is training a machine learning model using the labeled dataset. Supervised learning has a few limitations. This process is.

Datasets 52

Datasets Machine Learning Algorithm Raw Data 52

Netflix Tech

NOVEMBER 11, 2022

Here are just a few examples: We maintain a growing suite of video understanding models that categorize characters, storylines, emotions, and cinematography. These timecode tags enable efficient discovery, freeing our creators from hours of categorizing footage so they can focus on creative decisions instead.

Media 95

Media Machine Learning Algorithm Deep Learning 95

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. These labels provide context and meaning to the data, enabling machine learning algorithms to learn and make predictions. What is Data Labeling for Machine Learning?

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

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? If you hand a book to a new data engineer, what wisdom would you add to it?

Data Collection 100

Data Collection Management High Quality Data Metadata 100