Data Engineering Podcast

NOVEMBER 20, 2022

He explains the constraints that he and his team are faced with and the various challenges that they have overcome to build useful data products on top of a legacy platform where they don’t control the end-to-end systems. Atlan is the metadata hub for your data ecosystem.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

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. How to Build a Movie Recommendation System in Python?

Systems 98

Systems Entertainment Algorithm Datasets 98

Snowflake

JANUARY 23, 2024

We have been making it easier and faster to build and manage ML models with Snowpark ML , the Python library and underlying infrastructure for end-to-end ML workflows in Snowflake. Many developers and enterprises looking to use machine learning (ML) to generate insights from data get bogged down by operational complexity.

Machine Learning 120

Machine Learning Metadata Python Telecommunication 120

Precisely

MAY 13, 2024

If you need to build stronger, faster, and flexible data integration, use this checklist of ten key attributes to streamline your search and find the right technology for your organization, faster. #1. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

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

Cloudera

APRIL 1, 2024

Our cutting-edge Shared data experience (SDX) service provides a unified control plane for common security, governance and metadata management on all structured and unstructured data. We are also continuously building tools and services to help organizations build AI applications with Cloudera.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

LinkedIn Engineering

JUNE 2, 2023

These requests require interaction with one or more of our datasets, and the timelines can range from a few days to a couple of weeks. LHR is featured in our monthly Workforce Reports Once the publishing process is complete, our metric and the associated datasets are all discoverable via DataHub , our metadata management platform.

Building 75

Building Banking Datasets Media 75

Netflix Tech

OCTOBER 19, 2020

Distributed Tracing: the missing context in troubleshooting services at scale Prior to Edgar, our engineers had to sift through a mountain of metadata and logs pulled from various Netflix microservices in order to understand a specific streaming failure experienced by any of our members. Trace Instrumentation: how will it impact our service?

Building 93

Building Transportation Metadata Java 93

Cloudera

FEBRUARY 8, 2021

Curated, quality datasets are the backbone of any advanced analytics initiative. To achieve this, a data engineering framework must be used to allow the building of all of the piping and plumbing needed to move, manipulate, and manage data of the different vehicle parts in the data lifecycle. Conclusion.

Data Pipeline 116

Data Pipeline Building Manufacturing Data Warehouse 116

Data Engineering Weekly

MARCH 10, 2024

Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects. Thanks to Ideas2IT Technologies for hosting us in their fantastic space.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Towards Data Science

FEBRUARY 6, 2024

Discoverability : A shared data platform provides a catalog of operational datasets in the form of source-aligned data products that helped me to understand the status and nature of the data exposed. Metadata update Data products need to be understandable. Accessibility : I could easily request access to these data products.

Systems 79

Systems Raw Data Metadata Data Cleanse 79

Netflix Tech

NOVEMBER 13, 2023

The detailed temporal metadata SMAD provides about speech and music regions in a polyphonic audio mixture are a first step for structural audio segmentation, indexing and pre-processing audio for the following downstream tasks. TVSM is significantly larger than other SMAD datasets and contains both speech and music labels at the frame level.

Datasets 89

Datasets Metadata Algorithm Architecture 89

Monte Carlo

JUNE 20, 2023

So, just to be safe you take the extra time to recreate the dataset. In the focus on building data trust with business stakeholders, it’s easy to lose sight of the importance of also building trust with data teams across different domains. Will it be reliable and safe even after you turn your focus elsewhere?

Building 52

Building Data Datasets High Quality Data 52

Cloudera

FEBRUARY 8, 2024

Apache Iceberg is a high-performance open table format for petabyte-scale analytic datasets. Create Iceberg materialized view For the examples in this blog, we will use three tables from the TPC-DS dataset as our base tables: store_sales, customer and date_dim. Both full and incremental rebuild of the materialized view are supported.

Metadata 90

Metadata Data Warehouse BI AWS 90

François Nguyen

MARCH 22, 2021

How do we build data products ? How to build Data Products or never call me Data Pipeline any more You have this interesting schema in her second article on Data Mesh by Zhamak Dehghani : “Data mesh introduces the concept of data product as its architectural quantum. .” What you have to code is this workflow !

Technology 130

Technology Architecture Google Cloud Metadata 130

Cloudera

FEBRUARY 22, 2022

The data architecture layer is one such area where growing datasets have pushed the limits of scalability and performance. The data explosion has to be met with new solutions, that’s why we are excited to introduce the next generation table format for large scale analytic datasets within Cloudera Data Platform (CDP) – Apache Iceberg.

Metadata 107

Metadata Datasets BI SQL 107

ProjectPro

FEBRUARY 25, 2022

Efficient Scheduling and Runtime Increased Adaptability and Scope Faster Analysis and Real-Time Prediction Introduction to the Machine Learning Pipeline Architecture How to Build an End-to-End a Machine Learning Pipeline? This makes it easier for machine learning pipelines to fit into any model-building application.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Netflix Tech

DECEMBER 3, 2022

mock Generate or validate mock datasets. This is one way to build trust with our internal user base. Obviously not all tools are made with the same use case in mind, so we are planning to add more code samples for other (than classical batch ETL) data processing purposes, e.g. Machine Learning model building and scoring.

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

LinkedIn Engineering

MARCH 21, 2023

One of the most exciting parts of our work is that we get to play a part in helping progress a skills-first labor market through our team’s ongoing engineering work in building our Skills Graph. Engineering vs PyTorch Figure 6: Sample Seed Skills Graph KGBert helps build a more accurate and complex taxonomy in less time.

Building 85

Building Recruitment Machine Learning Deep Learning 85

Lyft Engineering

MARCH 6, 2024

Build central infrastructure and automation first; only ask teams to jump in once we have exhausted what we can do for them. There are many ways a single repo can leverage Python — running locally, in builds, for linting, during tests, as a dependency, at runtime, or even via a sidecar — and we weren’t aware of all of them!

Python 72

Python Metadata Datasets Coding 72

Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Towards Data Science

NOVEMBER 4, 2023

Indeed, datalakes can store all types of data including unstructured ones and we still need to be able to analyse these datasets. Indeed, why would we build a data connector from scratch if it already exists and is being managed in the cloud? Datalake example. Image by author. The downside of this approach is it’s pricing model though.

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Data Engineering Podcast

DECEMBER 16, 2019

Summary Building clean datasets with reliable and reproducible ingestion pipelines is completely useless if it’s not possible to find them and understand their provenance. The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Ascend.io

APRIL 7, 2023

Data mesh’s distributed nature helps data engineering teams become more agile , connecting data product building blocks that already exist to form other data products. In other words, the product one person builds might have inputs from another product. They can build on each other’s work. Increasing speed.

Metadata 52

Metadata Datasets Data Governance Government 52

Cloudera

JULY 19, 2023

Introduction Ozone is an Apache Software Foundation project to build a distributed storage platform that caters to the demanding performance needs of analytical workloads, content distribution, and object storage use cases. OM’s rate of serving operations becomes critical at scale, supporting the workloads spanning the entire dataset stored.

Management 70

Management Metadata Datasets Architecture 70

Data Engineering Weekly

MARCH 24, 2024

al6z: 16 Changes to the Way Enterprises Are Building and Buying Generative AI This report has a lot of interesting insight into the enterprise adoption of Gen AI. Moirai utilizes a large, diverse dataset and innovative techniques like any-variate attention and multiple patch-size projection layers to model complex, variable patterns.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Monte Carlo

MAY 30, 2024

Fine tuning is an alternate approach to GenAI development that involves training an LLM on a smaller, specialized, labeled dataset and adjusting the model’s parameters and embeddings based on new data. RAG excels in this area by consistently pulling from the latest curated datasets to inform its outputs. What is Fine Tuning?

Pipeline-centric 52

Pipeline-centric Database-centric Datasets Data Pipeline 52

The Modern Data Company

MARCH 7, 2023

A data taxonomy uses a system of unambiguous metadata terms (such as a filename or tags attached to a file) that allow an enterprise to classify a file or dataset into important business categories. For various reasons, the data sometimes can’t be re-tagged to provide consistent metadata.

Data Governance 52

Data Governance Government Metadata Datasets 52

dbt Developer Hub

OCTOBER 30, 2023

Well, the warehouse “cheats” by only copying metadata from the source schema to the target schema; the underlying data remains at rest during this operation. This metadata includes materialized objects like tables and views, which is why you see a clone of these objects in the target schema. dbt clone is a new command in dbt 1.6

BI 52

BI Datasets Metadata Data Warehouse 52

Data Engineering Weekly

DECEMBER 10, 2023

Capital One: Insights on building a data strategy to drive business value One of the hotly debated and many companies struggling with is to build an agile data strategy to drive business value. I can’t wait for someone to build a bot around it!!! Tuning hyperparameters like rank and dataset diversity is key.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Rockset

NOVEMBER 7, 2023

As a result, indexing of newly ingested vectors and metadata does not negatively impact search performance. There are several methods to indexing vectors including building a graph, tree data structure and inverted file structure. Rockset supports streaming updates to metadata and vectors in an efficient way.

Cloud 64

Cloud Metadata Database SQL 64

Netflix Tech

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can push or pull.

Building 87

Building Metadata Transportation Data Ingestion 87

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. This means that data scientists and engineers will be able to spend less time on painstakingly preparing datasets for analytics or writing complex code. Those who don’t embrace it will be left behind. RAG workflow.

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

ProjectPro

FEBRUARY 8, 2023

Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. AWS Glue then creates data profiles in the catalog, a repository for all data assets' metadata, including table definitions, locations, and other features. For analyzing huge datasets, they want to employ familiar Python primitive types.

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 95

Data Governance Government Metadata Datasets 95

Cloudera

AUGUST 26, 2021

In this blog post, we will ingest a real world dataset into Ozone, create a Hive table on top of it and analyze the data to study the correlation between new vaccinations and new cases per country using a Spark ML Jupyter notebook in CML. On creation of the bucket, we also upload a COVID dataset [1] that is a CSV with about 100K rows.

Data Science 111

Data Science Cloud Hadoop Metadata 111