Data Engineering Podcast

MARCH 1, 2021

Summary The process of building and deploying machine learning projects requires a staggering number of systems and stakeholders to work in concert. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Machine Learning 100

Machine Learning Data Warehouse Scala Hadoop 100

Data Engineering Podcast

JUNE 14, 2021

Summary When you build a machine learning model, the first step is always to load your data. In this episode Paige Roberts explains the benefits of pushing the machine learning processing into the database layer and the approach that Vertica has taken for their implementation. when working within the database?

Machine Learning 100

Machine Learning Database Data Warehouse Hadoop 100

Picnic Engineering

DECEMBER 12, 2023

At Picnic, we track the latest machine learning developments to ensure the best possible demand forecasting. This blog post delves into the learnings and challenges on our journey towards implementing and scaling state-of-the-art deep learning approaches. For that use case a simple SQL query can be enough.

Machine Learning 52

Machine Learning Deep Learning Food High Quality Data 52

Data Engineering Podcast

JANUARY 15, 2022

Summary Data quality control is a requirement for being able to trust the various reports and machine learning models that are relying on the information that you curate.

Machine Learning 100

Machine Learning Management Data Warehouse Data 100

Data Engineering Podcast

FEBRUARY 8, 2021

In this episode Zeeshan Qureshi and Michelle Ark share their experiences using DBT to manage the data warehouse for Shopify. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. What kinds of data sources are you working with?

Data Warehouse 100

Data Warehouse Building BI SQL 100

Data Engineering Podcast

AUGUST 6, 2022

For analytical systems there are decades of investment in data warehouses and various modeling techniques. For machine learning applications relational models require additional processing to be directly useful, which is why there has been a growth in the use of vector databases.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. If you are evaluating your options for building or migrating a data platform, then this is definitely worth a listen.

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 83

Machine Learning Algorithm Government Metadata 83

Data Engineering Podcast

AUGUST 31, 2020

Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage.

Data Warehouse 100

Data Warehouse Cloud Building Data Lake 100

Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . Cloudera Data Warehouse vs HDInsight.

Data Warehouse 118

Data Warehouse Cloud Storage Metadata Cloud 118

Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Sometimes, however, one of those transformations is actually a full-fledged machine learning project in its own right.

Data Pipeline 100

Data Pipeline Machine Learning Data Warehouse Datasets 100

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 89

Data Warehouse Cloud Government Metadata 89

Monte Carlo

APRIL 16, 2022

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. Treating data like an API. Immutable data warehouses have challenges too.

Data Warehouse 52

Data Warehouse Architecture Data Government 52

Data Engineering Podcast

OCTOBER 14, 2019

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 94

Data Warehouse Cloud Consulting SQL 94

Data Engineering Podcast

JANUARY 18, 2021

Summary The data warehouse has become the central component of the modern data stack. This is an interesting conversation about the importance of the data warehouse and how it can be used beyond just internal analytics. How do you keep data up to date between the warehouse and downstream systems?

Data Warehouse 100

Data Warehouse BI Data Data Pipeline 100

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. Cloudera Data Warehouse added support for the most recent format version of Iceberg in its latest release.

Data Warehouse 81

Data Warehouse Metadata Java Data 81

Cloudera

DECEMBER 11, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 Cloudera Data Warehouse vs EMR. Learn more about Cloudera Data Warehouse on CDP.

Data Warehouse 108

Data Warehouse Metadata Datasets Data 108

Data Engineering Podcast

APRIL 24, 2022

Summary There are very few tools which are equally useful for data engineers, data scientists, and machine learning engineers. WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model.

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Knowledge Hut

JUNE 20, 2023

A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions. They develop self-running software.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 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

Data Engineering Podcast

AUGUST 14, 2021

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads?

Unstructured Data 100

Unstructured Data Machine Learning Data Lake SQL 100

Cloudera

APRIL 9, 2021

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. ETL jobs and staging of data often often require large amounts of resources.

Data Warehouse 58

Data Warehouse Cloud Data Architecture 58

Netflix Tech

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Data Engineering Podcast

JULY 8, 2019

Summary The market for data warehouse platforms is large and varied, with options for every use case. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform. that are unique to Clickhouse?

Data Warehouse 100

Data Warehouse MySQL Data Lake Hadoop 100

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). The Machine Learning Podcast helps you go from idea to production with machine learning.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Cloudera

JANUARY 11, 2021

How self-service data warehousing frees IT resources. Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Cloudera Machine Learning (CML).

Data Warehouse 62

Data Warehouse Pharmaceutical Data Lake BI 62

Hepta Analytics

FEBRUARY 24, 2022

Examples of such systems are: ATM Shopping cart MoMo ticket systems OLAP on the other hand is used for data analysis. Data is aggregated from multiple sources and used by the business team to make decisions. Data structure and schema is defined in advance. The main goal is to become the single source of truth in an organization.

Data Warehouse 52

Data Warehouse Data Engineering Data Engineer Engineering 52

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses. Support for Modern Analytics Workloads : With support for both SQL-based querying and advanced analytics frameworks (e.g.,

Data Lake 71

Data Lake Data Warehouse Programming Language Data Ingestion 71

dbt Developer Hub

MARCH 9, 2022

But there’s one baton pass that’s still relatively painful and undefined: the handoff between machine learning (ML) engineers and analytics engineers. Here’s what happened ​ After some initial planning, I knew we had this raw data living somewhere in our data warehouse. But how do these breakdowns happen?

Machine Learning 52

Machine Learning Raw Data SQL Python 52

Data Engineering Podcast

APRIL 23, 2023

The Machine Learning Podcast helps you go from idea to production with machine learning. If you've learned something or tried out a project from the show then tell us about it! You can collect, transform, and route data across your entire stack with its event streaming, ETL, and reverse ETL pipelines.

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Data Lake Kafka Machine Learning Data Warehouse 277

Data Engineering Podcast

JANUARY 21, 2024

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

APRIL 9, 2023

When it was difficult to wire together the event collection, data modeling, reporting, and activation it made sense to buy monolithic products that handled every stage of the customer data lifecycle. Now that the data warehouse has taken center stage a new approach of composable customer data platforms is emerging.

Data Lake 147

Data Lake Data Warehouse Machine Learning Data 147

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Modern data warehousing for the cloud. Using Cloudera Altus for your cloud data warehouse.

Data Warehouse 40

Data Warehouse Metadata Cloud Storage Cloud 40

AltexSoft

JULY 27, 2021

And what does machine learning have to do with it? In this article, we’re taking you down the road of machine learning-based personalization. You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. How recommender systems work: data processing phases.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76