Data Engineering Podcast

NOVEMBER 20, 2021

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. What are the prevailing architectural and technological patterns that are being used to manage these systems?

Data Lake 100

Data Lake Data Integration Lambda Architecture Process 100

Monte Carlo

AUGUST 30, 2023

But there’s a lot to understand in order to both create the most value from your dbt tests and avoid leaning too heavily on a time-intensive process. If your datasets are updated or refreshed daily, you’ll want to run your schema tests on a similar schedule. And one of the most popular approaches is dbt testing.

SQL 52

SQL Datasets Database High Quality Data 52

Towards Data Science

MARCH 29, 2023

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. Especially useful was that the model could provide reasoning for its predictions which helped to identify improvements to the process. Using GPT-3.5-Turbo

Datasets 63

Datasets Food Retail Hospitality 63

U-Next

JULY 2, 2022

Software multitenancy refers to a system design where a single example of a program operates on a host and provides services to several tenants. The definition of multitenancy. It offers a pay-per-use system to the renters. Multiple people share this processing and storage capability. Extensibility: . Dispensing usage: .

Cloud Computing 52

Cloud Computing Cloud Architecture Database 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

Tweag

APRIL 19, 2023

Most training pipelines and systems are designed to handle fairly small, sub-megapixel images. 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.

Medical 60

Medical Process Cloud Bytes 60

Data Engineering Weekly

MAY 26, 2024

link] Chris Riccomini: S3 Is Showing Its Age Building a global scale distributed system with eleven 9s of durability and four 9s of availability is no easy feat. S3 is the state-of-the-art software system of our age. Zillow writes about its approach to building easy-to-use data that adopts certified datasets, aka data products.

Data Engineering 57

Data Engineering Data Engineer Engineering Google Cloud 57

Monte Carlo

MAY 16, 2024

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. That process can also lead to some pretty spotty coverage. It can come from your data sources, transformation code, or ELT systems. No table is an island.

Datasets 52

Datasets Data Finance AWS 52

ProjectPro

FEBRUARY 16, 2023

Whether you’re looking to track objects in a video stream, build a face recognition system, or edit images creatively, OpenCV Python implementation is the go-to choice for the job. At the core of such applications lies the science of machine learning, image processing, computer vision, and deep learning. What is OpenCV Python?

Python 98

Python Process Deep Learning Algorithm 98

ThoughtSpot

MARCH 5, 2024

These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot. The refresh process automatically computes changes in the source data and merges those updates into the dynamic table.

BI 94

BI Datasets Raw Data SQL 94

Christophe Blefari

APRIL 14, 2023

This is just a normal evolution of deep learning systems. But as Robert says "No tool can fix people, behaviors, process, and the semantic layer, however conceptually elegant or impactful, is no exception" ( read here ). That’s why they built this system. Last one because it's funny ).

Datasets 130

Datasets Data Deep Learning SQL 130

ProjectPro

DECEMBER 7, 2021

A data pipeline automates the movement and transformation of data between a source system and a target repository by using various data-related tools and processes. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

U-Next

SEPTEMBER 7, 2022

Recommendation System – Created by Machine Learning . A recommender system, broadly defined, is a system that anticipates the ratings a user would give to a certain item. . These kinds of systems have helped both the users and the services offered. What Are Recommender Systems? .

Machine Learning 40

Machine Learning Systems Algorithm Datasets 40

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?

Datasets 40

Datasets Machine Learning Retail Banking 40

Monte Carlo

AUGUST 9, 2023

This modern approach has been a game-changer for data engineering teams, whose processes have always been prone to breakages. Without data engineering workflows that automate and streamline processes, an ad-hoc approach would wreak havoc on modern organizations. Let’s dive in.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Knowledge Hut

MARCH 27, 2024

An ordered set of data kept in a computer system and typically managed by a database management system (DBMS) is called a database. Table modeling of the data in standard databases facilitates efficient searching and processing. Flexibility: Offers scalability to manage extensive datasets efficiently. What is a Database?

Database 52

Database Algorithm Relational Database PostgreSQL 52

Lyft Engineering

OCTOBER 3, 2023

Data quality is an amorphous term, with various definitions depending on the context. In Verity, we defined data quality as follows: Verity’s Definition of Data Quality The measure of how well data can be used as intended. Five aspects of data quality with the definition in italics and an example in quotes.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Lyft Engineering

NOVEMBER 29, 2023

Introduction At Lyft, we have used systems like Apache ClickHouse and Apache Druid for near real-time and sub-second analytics. Sub-second query systems allow for near real-time data explorations and low latency, high throughput queries, which are particularly well-suited for handling time-series data.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Ascend.io

FEBRUARY 15, 2024

At their core, data replication strategies are methods and practices used to create and maintain copies of your data across different systems and platforms. That can include the creation of historical data that is not available in the source system. Large datasets bring challenges in terms of processing power and storage needs.

Datasets 52

Datasets Database Data Warehouse Data 52

Netflix Tech

NOVEMBER 13, 2023

In this blog post, we will introduce speech and music detection as an enabling technology for a variety of audio applications in Film & TV, as well as introduce our speech and music activity detection (SMAD) system which we recently published as a journal article in EURASIP Journal on Audio, Speech, and Music Processing.

Datasets 89

Datasets Metadata Algorithm Architecture 89

Monte Carlo

APRIL 12, 2022

Data teams love the idea of automating data engineering processes in principle. In this spirit, we got together to brainstorm nine data engineering processes we believe are ripe for automation. For these data engineering processes, there is no need to be a code warrior. We’ve felt it ourselves.

Data Engineering 52

Data Engineering Data Engineer Process Engineering 52

Monte Carlo

MAY 14, 2024

It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

RandomTrees

APRIL 30, 2024

In this ever-changing world of healthcare, technological innovations are continuously changing the definition of what is possible. These systems can find out any anomalies and help radiologists in making more precise diagnoses. It keeps on making impossible things possible.

Medical 52

Medical Healthcare Algorithm Electronics 52

AltexSoft

NOVEMBER 23, 2021

But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. The traditional way of data integration involves consolidating disparate data within a single repository — commonly a data warehouse — via the extract, transform, load (ETL) process.

Process 69

Process Data Lake Metadata Data Warehouse 69

Netflix Tech

DECEMBER 3, 2022

mock Generate or validate mock datasets. Thanks to the Netflix internal lineage system (built by Girish Lingappa ) Dataflow migration can then help you identify downstream usage of the table in question. " ) COMMENT "Example dataset brought to you by Dataflow. -v, --verbose Enables verbose mode. backfill.sch.yaml ???

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

Cloudera

MARCH 9, 2021

While Cloudera Data Platform (CDP) already supports the entire data lifecycle from ‘Edge to AI’, we at Cloudera are fully aware that enterprises have more systems outside of CDP. Atlas provides a basic set of pre-defined type definitions (called typedefs ) for various Hadoop and non-Hadoop metadata to cover all the needs of CDP.

Data Governance 95

Data Governance Government Metadata Datasets 95

Knowledge Hut

DECEMBER 26, 2023

This has been applied to Computer Vision (CV), audio and speech recognition and Natural Language Processing (NLP) use cases. From the definition as per the official website , PyTorch is an open-source machine learning framework that accelerates the path from research prototyping to production deployment. What is PyTorch ? TensorFlow 2.0

Deep Learning 98

Deep Learning Python Machine Learning Programming Language 98

ProjectPro

NOVEMBER 30, 2021

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. It was a manual process and very challenging as well. The invention of the pipeline system automated the water supply delivery to homes via pipes from various water sources.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Scott Logic

MAY 31, 2023

For a while now I’ve been keeping a notebook where I record brief definitions of these new terms as I encounter them. This is a broad field, with AI models tackling various tasks including visual perception, language processing and speech recognition. This process is called tokenisation.

Datasets 59

Datasets Media Architecture Finance 59

Picnic Engineering

JANUARY 9, 2024

To do this we couldn’t do without recommender systems. Recommender systems are used in many places within Picnic. The long tail of the data is a large challenge in many recommendation systems. The input sequence is processed to produce a single “next-item” prediction, which is evaluated against the ground-truth test item.

Machine Learning 91

Machine Learning Datasets Algorithm Systems 91

Precisely

SEPTEMBER 5, 2023

Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises. Many businesses have multiple systems that house customer data, for example. Here’s what data governance adds to the bigger picture: Definition: What does a particular term mean?

Data Governance 52

Data Governance Government Data Management Management 52

U-Next

MARCH 13, 2023

Even though they deal with visual data, image processing, and computer vision are different. Image processing entails altering or editing photos to create a fresh outcome. An automated Machine Learning system may learn how to interpret visual input with the use of pre-programmed computational frameworks.

Deep Learning 73

Deep Learning Machine Learning Datasets Healthcare 73

Knowledge Hut

DECEMBER 22, 2023

A dataset is frequently represented as a matrix. Hadoop Gigabytes to petabytes of data may be stored and processed effectively using the open-source framework known as Apache Hadoop. You can utilize knowledge management systems to organize your knowledge base for your users or customers and amongst businesses or teams.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Ascend.io

MARCH 17, 2023

Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. The processes to consume and transform data are ad-hoc and manual, and the costs are unjustified. Robotic Process Automation (RPA) software was born. What if they could automate some of the process?

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. The processes to consume and transform data are ad-hoc and manual, and the costs are unjustified. Robotic Process Automation (RPA) software was born. What if they could automate some of the process?

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention.

Project 96

Project Healthcare Deep Learning Transportation 96

Towards Data Science

JANUARY 5, 2024

This is because optimization processes tend to search for better optimums in the vicinity of the current optimum — not only with gradient descent but also with human invention. Our main tool will be the abstraction of the process applied with OOP principles, and the normalization of work of individuals into a unified language.

Data Science 76

Data Science Datasets Data Machine Learning 76