Data Engineering Podcast

MARCH 24, 2024

It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your first 30 days are free! The Machine Learning Podcast helps you go from idea to production with machine learning.

Data Lake 162

Data Lake High Quality Data Hadoop Data Pipeline 162

Data Engineering Podcast

FEBRUARY 4, 2024

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Data Engineering Podcast

MARCH 31, 2024

Identifying and accounting for those errors is a critical piece of building trust in the organization that your data is accurate and up to date. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Project 130

Project Data Lake High Quality Data Data Workflow 130

Data Engineering Podcast

MARCH 3, 2024

Colleen Tartow has worked across all stages of the data lifecycle, and in this episode she shares her hard-earned wisdom about how to conduct an AI program for your organization. Your first 30 days are free! In order to make those promises a reality there is a substantial amount of strategy and investment required.

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

Data Engineering Podcast

MARCH 10, 2024

In this episode Alex Merced explains how the branching and merging functionality in Nessie allows you to use the same versioning semantics for your data lakehouse that you are used to from Git. Your first 30 days are free! How have the design and goals of the project changed since it was first created?

Data Lake 147

Data Lake High Quality Data Data Pipeline Architecture 147

The Pragmatic Engineer

JUNE 1, 2023

We covered how Stack Overflow learned this the hard way, a few months back. ” stage Improve deploys. Change deploys to be a one-command process, instead of multiple steps See blog posts #1-11 for details on all the steps. This likely helped him to learn, and it also helps others wanting to understand, too.

Education 363

Education Project PostgreSQL Software Engineer 363

Data Engineering Podcast

FEBRUARY 11, 2024

For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Your first 30 days are free!

Data Lake 147

Data Lake High Quality Data Government Data Pipeline 147

Data Engineering Podcast

FEBRUARY 25, 2024

It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your first 30 days are free! This was the core of your recent re-write of the InfluxDB engine. Want to see Starburst in action?

Database 162

Database Technology Data Lake High Quality Data 162

Data Engineering Podcast

MARCH 17, 2024

In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Your first 30 days are free! What are the most interesting, unexpected, or challenging lessons that you have learned while working on Datafold?

Database 147

Database Data Lake High Quality Data Data Workflow 147

Data Engineering Podcast

NOVEMBER 12, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. Want to see Starburst in action? With Materialize, you can!

Software Engineer 147

Software Engineer Software Engineering Engineering Data Lake 147

Data Engineering Podcast

OCTOBER 29, 2023

In this episode Tanya Bragin shares her experiences as a product manager for two major vendors and the lessons that she has learned about how teams should approach the process of tool selection. Datafold integrates with dbt, the modern data stack, and seamlessly plugs in your data CI for team-wide and automated testing.

Database 189

Database BI SQL Machine Learning 189

Christophe Blefari

MARCH 15, 2024

I'd like to thank you for the excellent comments you sent me last week after the publication of the first version of the Recommendations. RAG is the new trend — RAG means retrieval-augmented generation, it has been coined in 2020 ( see more ) and let's you ground AI models with facts fetched from external sources.

Metadata 272

Metadata Datasets Data Data Warehouse 272

Data Engineering Podcast

OCTOBER 8, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. How can you get the best results for your use case?

Insurance 162

Insurance BI SQL Machine Learning 162

Data Engineering Podcast

JULY 2, 2023

Summary Feature engineering is a crucial aspect of the machine learning workflow. To make that possible, there are a number of technical and procedural capabilities that must be in place first. What are the most interesting, unexpected, or challenging lessons that you have learned while working on feature engineering?

Machine Learning 130

Machine Learning Data Engineering Data Engineer Engineering 130

Data Engineering Podcast

JULY 23, 2023

In Hex you can use SQL, Python, R, and no-code visualization together to explore, transform, and model data. Hex also has AI built directly into the workflow to help you generate, edit, explain and document your code. Make your data team unstoppable with Hex. What was your decision process for building Dozer as open source?

Building 130

Building SQL Machine Learning Data Ingestion 130

Edureka

MAY 6, 2024

In today’s data-driven world, machine learning models play a huge role in developing sectors like healthcare, finance, transport, e-commerce, and so on. However, building and deploying these models is just the beginning. This is where MLOps (Machine Learning Operations) comes into play.

Machine Learning 52

Machine Learning Metadata Programming Language Healthcare 52

Data Engineering Podcast

SEPTEMBER 3, 2023

The dlt project was created to eliminate overhead and bring data integration into your full control as a library component of your overall data system. This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production.

Data Integration 162

Data Integration BI SQL Python 162

Cloudera

MAY 9, 2024

First, we need to help customers get AI models based on trusted data into production faster than ever. Let’s take a deeper dive into how these capabilities accelerate your AI initiatives and support data democratization. SQL AI Assistant: Your New Best Friend Writing complex SQL queries can be a real challenge.

BI 71

BI SQL Business Analyst Machine Learning 71

Cloudera

NOVEMBER 29, 2023

In the dynamic world of machine learning operations (MLOps), staying ahead of the curve is essential. That’s why we’re excited to announce the Cloudera Model Registry as generally available, a game-changer that’s set to transform the way you manage your machine learning models in production environments.

Machine Learning 86

Machine Learning Metadata Cloud Project 86

Cloudera

MARCH 26, 2024

How do you adapt a foundational model to your specific needs? Cloudera: Your Trusted Partner in AI With over 25 Exabytes of Data Under Management and hundreds of customers leveraging our platform for Machine Learning, Cloudera has a long and successful history as an industry leader.

Machine Learning 82

Machine Learning Banking Professional Services Architecture 82

Data Engineering Podcast

NOVEMBER 5, 2023

You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! Want to see Starburst in action?

PostgreSQL 147

PostgreSQL Data Lake High Quality Data SQL 147

Data Engineering Podcast

DECEMBER 3, 2023

Summary The first step of data pipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Andrei Tserakhau has dedicated his careeer to this problem, and in this episode he shares the lessons that he has learned and the work he is doing on his most recent data transfer system at DoubleCloud.

Systems 130

Systems Designing Data Lake SQL 130

Data Engineering Podcast

AUGUST 13, 2023

Summary Data pipelines are the core of every data product, ML model, and business intelligence dashboard. If you're not careful you will end up spending all of your time on maintenance and fire-fighting. In this episode Ariel Pohoryles explains what they are and how they work together to increase your chances of success.

Data Pipeline 130

Data Pipeline BI SQL Business Intelligence 130

Christophe Blefari

JANUARY 26, 2024

Next week, I'll be wrapping up my DataOps lecture by incorporating how to deploy machine learning models. This is a fun part where students learn how to serve a simple classifier in production. Before jumping to AI projects you need first to start with words and to define metrics reflecting [your] values.

Google Cloud 130

Google Cloud Algorithm Data Java 130

Cloudera

MAY 30, 2024

One of the primary benefits of deploying AI and analytics within an open data lakehouse is the ability to centralize data from disparate sources into a single, cohesive repository. Learn more about the Cloudera Open Data Lakehouse here. The post Unify your data: AI and Analytics in an Open Lakehouse appeared first on Cloudera Blog.

Data Lake 63

Data Lake Data Warehouse Programming Language Data Ingestion 63

Cloudera

MAY 3, 2024

With a single click, AMPs build, deploy, and set up continuous monitoring of enterprise-ready machine learning (ML) applications. The workflow—from data ingestion and model training to model deployment—is meticulously defined within a YAML configuration file. Best of all, every AMP is fully open source.

Data Security 71

Data Security Machine Learning Data Ingestion Professional Services 71

Snowflake

JANUARY 23, 2024

Many developers and enterprises looking to use machine learning (ML) to generate insights from data get bogged down by operational complexity. 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.

Machine Learning 120

Machine Learning Metadata Python Telecommunication 120

Cloudera

APRIL 1, 2024

Cloudera’s open data lakehouse accelerates BI query performance by over 40% while also making it easy for data scientists to explore the latest datasets for their models. Cloudera customers deploy a very diverse data infrastructure that consists of hundreds of data sources, multiple clouds, and multiple processing engines.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

Cloudera

MAY 30, 2024

Christian Simonelli, of TAI Solutions : One of Italy’s major banks, working with TAI, reorganized their existing data lifecycle management processes to explore advanced machine learning scenarios, streaming analytics, and data lineage capabilities. What are some of the reasons that TAI Solutions’ customers choose Cloudera?

Data Analytics 71

Data Analytics Banking Insurance Finance 71

Knowledge Hut

DECEMBER 26, 2023

As technology is evolving rapidly today, both Predictive Analytics and Machine Learning are imbibed in most business operations and have proved to be quite integral. Deep learning is a machine learning type based on artificial neural networks (ANN). What is TensorFlow ?

Deep Learning 98

Deep Learning Python Machine Learning Programming Language 98

Data Engineering Podcast

AUGUST 20, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. With Materialize, you can! When is Illumidesk the wrong choice?

Education 130

Education BI SQL Database 130

Cloudera

NOVEMBER 1, 2023

Elevate your AI applications with our latest applied ML prototype At Cloudera, we continuously strive to empower organizations to unlock the full potential of their data, catalyzing innovation and driving actionable insights. High-level overview of real-time data ingest with Cloudera DataFlow to Pinecone vector database.

Machine Learning 108

Machine Learning Data Ingestion Database Architecture 108

Cloudera

MAY 14, 2024

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models. appeared first on Cloudera Blog. Data comes in many forms.

Cloud 96

Cloud Data Governance Unstructured Data Data Architecture 96

Knowledge Hut

APRIL 29, 2024

Machine Learning is no longer just the latest buzzword. Most of the applications across the world are built using Machine Learning and their applications extend further when they are combined with other cutting-edge technologies like Deep Learning and Artificial Intelligence. What is Model Deployment?

Machine Learning 52

Machine Learning Python Datasets Coding 52

Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Organizations need to usher their ML models out of the lab (i.e., COPML accounts for the fact that true production machine learning (i.e.,

Machine Learning 121

Machine Learning IT Data Engineering Data Engineer 121

Christophe Blefari

JUNE 9, 2023

I search and read articles first and then I write. Data contracts, dbt and modeling Back to the roots, it's been a long time since I did not share dedicated stuff about dbt. A few people already implemented things with the new model governance dbt introduced last month in v1.5. As of today I do the newsletter every Friday.

Data 130

Data Government SQL Coding 130

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. The best Website to learn Python: w3schools.com. Best Website for excel: excelexposure.com.

Data Science 98

Data Science Datasets Database Design Machine Learning 98