Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities.

Data Process 78

Data Process Process Raw Data Data 78

Christophe Blefari

MARCH 15, 2024

Saying mainly that " Sora is a tool to extend creativity " Last point Mira has been mocked and criticised online because as a CTO she wasn't able to say on which public / licensed data Sora has been trained on. Pandera, a data validation library for dataframes, now supports Polars. This is Croissant.

Metadata 272

Metadata Datasets Data Data Warehouse 272

Precisely

MARCH 7, 2024

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. By harnessing the power of machine learning and natural language processing, sophisticated systems can analyze and prioritize claims with unprecedented efficiency and timeliness.

Insurance 72

Insurance Process Medical Data Governance 72

Knowledge Hut

FEBRUARY 1, 2024

While building predictive models, if your results aren’t satisfactory, then the two things that can go wrong are data or models. Choosing the right data is the first step in any data science application. Then comes the data format. Data cleaning in data science plays a pivotal role in your analysis.

Data Science 52

Data Science Process Data Cleanse Datasets 52

LinkedIn Engineering

JANUARY 19, 2024

Figure 1: Talent pool report for recruiters - LinkedIn Talent Insights During mergers and acquisitions, the source company’s user licenses and data are transferred to the acquiring company. This multi-entity handover process involves huge amounts of data updating and cloning. A typical merger & acquisition scenario.

Recruitment 88

Recruitment Data Process Process Kafka 88

Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

Data Process 52

Data Process Process Hadoop Scala 52

Data Engineering Podcast

JUNE 26, 2022

Summary The proliferation of sensors and GPS devices has dramatically increased the number of applications for spatial data, and the need for scalable geospatial analytics. Atlan is the metadata hub for your data ecosystem. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Datasets 130

Datasets Unstructured Data Metadata MongoDB 130

KDnuggets

NOVEMBER 8, 2021

It's not trivial to become familiar with NLP and these open-source data sets can help you increase your skills. With a lot of excitement and research around NLP, there are growing opportunities to apply these technologies to real-world scenarios.

Datasets 123

Datasets Process Technology IT 123

Ascend.io

MAY 23, 2023

The data engineering world is full of tips and tricks on how to handle specific patterns that recur with every data pipeline. A prime example of such patterns is orphaned datasets. Typically, these orphaned datasets are addressed with ad-hoc manual protocols and after-the-fact garbage collection processes.

Datasets 52

Datasets Data Pipeline Metadata Database 52

Christophe Blefari

APRIL 19, 2024

easy ( credits ) Hey, new Friday, new Data News. 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 week, I feel like the selection is smaller than usual, so enjoy the links.

MySQL 130

MySQL Data Datasets SQL 130

Monte Carlo

APRIL 16, 2024

Today, the term “data-driven” is everywhere. Every company is “data-driven,” every decision is “data-driven,” even our daily lives, complete with recommendations and notifications from our wearable watches, rings, and phones, are driven by the data we create and consume. But what does reliable data actually look like?

Process 52

Process Government Data Data Engineering 52

Data Engineering Podcast

NOVEMBER 20, 2021

Summary One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. With the improvements in streaming engines it is now possible to perform all of your data integration in near real time, but it can be challenging to understand the proper processing patterns to make that performant.

Data Lake 100

Data Lake Data Integration Lambda Architecture Process 100

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Big Data is a large and complex dataset generated by various sources and grows exponentially. It is so extensive and diverse that traditional data processing methods cannot handle it. The volume, velocity, and variety of Big Data can make it difficult to process and analyze.

Big Data Tools 234

Big Data Tools Big Data Datasets Data 234

Robinhood

FEBRUARY 7, 2024

from Robinhood Data Infrastructure Robinhood adheres to a data-first philosophy. Every decision we make here (or every decision at the company), from feature rollouts to operational changes, is backed by data. When dealing with large-scale data, we turn to batch processing with distributed systems to complete high-volume jobs.

Process 75

Process Hadoop Architecture Accessible 75

Towards Data Science

MARCH 29, 2023

Turbo and GPT-4 for Predicting Humanitarian Data Categories Image created by Stable Diffusion with prompt ‘Predicting Cats’. Turbo and GPT-4 to categorize datasets without the need for labeled data or model training, by prompting the model with data excerpts and category definitions. Using GPT-3.5-Turbo

Datasets 64

Datasets Food Retail Hospitality 64

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.

Architecture 52

Architecture Database-centric Process BI 52

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

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. What Does a Data Processing Analyst Do?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Precisely

JULY 25, 2023

Organizations that run SAP can use Excel-to-SAP automation to do more with less, while also increasing agility and improving their SAP master data management process automation. We bring automation closer to the business users who own the data and the day-to-day processes that drive the business.

Data Process 52

Data Process Process Data Data Integration 52

Data Engineering Weekly

MAY 8, 2023

Your colleague, Helen from finance, optimistically informs you that this should be easy since all the data has been entered into the company's databases. Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone.

Process 52

Process Banking Raw Data Finance 52

Striim

NOVEMBER 17, 2023

In today’s data-driven world, the ability to leverage real-time data for machine learning applications is a game-changer. Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. Aggregation of data is useful in this situation.

Process 59

Process Data Mining Aggregated Data Portfolio 59

Monte Carlo

MAY 16, 2024

At what level does it make sense to deploy your data monitoring coverage? For most traditional data quality tools the answer has been by table. Data teams are onboarding datasets quickly and with the power of modern platforms, that process has only been getting faster and volumes only getting bigger.

Datasets 52

Datasets Data Finance AWS 52

AltexSoft

OCTOBER 18, 2022

Everyday the global healthcare system generates tons of medical data that — at least, theoretically — could be used for machine learning purposes. Regardless of industry, data is considered a valuable resource that helps companies outperform their rivals, and healthcare is not an exception. Medical data labeling. Let’s sum up.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Monte Carlo

JANUARY 29, 2024

Too many teams approach data incident management like a game of group whack-a-mole. Multiple stakeholders from multiple teams swinging wildly at whatever pops up from the incident hole—and occasionally hitting each other in the process. That makes the need for a data incident management process inevitable as well.

Process 69

Process Management IT Data 69

Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

Data Storage 185

Data Storage Big Data Hadoop Datasets 185

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake?

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

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

Process 97

Process Lambda Architecture Kafka Datasets 97

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

Knowledge Hut

MARCH 22, 2024

Reverse engineering software is the process of dissecting it to understand its components, functionality, and workflow without having access to the source code. Reverse engineering can help recover or migrate data to more modern systems, ensuring that no critical information is lost. What is Reverse Engineering in Software Engineering?

Process 52

Process Engineering Electronics Software Engineer 52

Christophe Blefari

OCTOBER 20, 2023

Read my dbt multi-project guide 📺 On the content side I'll also present next week the Fancy Data Stack project at the Data Engineering And Machine Learning Summit 2023 organised by Seattle Data Guy. a lea prepare command that creates database objects that needs to be created (dataset, schema, etc.).

Generalist 130

Generalist Entertainment NoSQL Datasets 130

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. Specifics of data used in NLP. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life. Main NLP use cases.

Process 139

Process Deep Learning Datasets Machine Learning 139

Knowledge Hut

APRIL 23, 2024

In today's data-driven world, the volume and variety of information are growing unprecedentedly. As organizations strive to gain valuable insights and make informed decisions, two contrasting approaches to data analysis have emerged, Big Data vs Small Data.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

APRIL 23, 2024

Big data and data mining are neighboring fields of study that analyze data and obtain actionable insights from expansive information sources. Big data encompasses a lot of unstructured and structured data originating from diverse sources such as social media and online transactions.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Towards Data Science

AUGUST 29, 2023

Data Quality Chronicles Missing data, missing mechanisms, and missing data profiling Missing Data prevents data scientists to see the entire story the data has to tell. One of them was, unsurprisingly, Missing Data. Photo by Ronan Furuta on Unsplash. Image by Author. Image by Author.

Datasets 106

Datasets Machine Learning Data Data Science 106

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