Data Engineering Podcast

APRIL 7, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents data quality issues from entering every part of your data workflow, from migration to dbt deployment.

Data Lake 162

Data Lake High Quality Data BI Data Workflow 162

Data Engineering Podcast

DECEMBER 24, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. With Materialize, you can!

Kafka 245

Kafka Data Lake High Quality Data SQL 245

Data Engineering Podcast

MARCH 31, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Dagster offers a new approach to building and running data platforms and data pipelines.

Project 130

Project Data Lake High Quality Data Data Workflow 130

Data Engineering Podcast

JANUARY 21, 2024

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

JANUARY 7, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Process 147

Data Process Process Data Lake High Quality Data 147

Data Engineering Podcast

NOVEMBER 26, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. With Materialize, you can!

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Monte Carlo

NOVEMBER 8, 2023

Kafka and Vector Database support According to Databricks’ State of Data and AI report , the number of companies using SaaS LLM APIs has grown more than 1300% since November 2022 with a nearly 411% increase in the number of AI models put into production during that same period. Both integrations will be available early 2024.

Kafka 64

Kafka Database High Quality Data Datasets 64

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. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. With Materialize, you can!

Systems 130

Systems Designing Data Lake SQL 130

Data Engineering Podcast

NOVEMBER 5, 2023

Summary Databases are the core of most applications, but they are often treated as inscrutable black boxes. When an application is slow, there is a good probability that the database needs some attention. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products.

PostgreSQL 147

PostgreSQL Data Lake High Quality Data SQL 147

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Data Engineering Podcast

DECEMBER 31, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data.

Designing 130

Designing Data Lake High Quality Data SQL 130

Data Engineering Podcast

NOVEMBER 12, 2023

If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Data lakes are notoriously complex. You shouldn't have to throw away the database to build with fast-changing data.

Software Engineer 147

Software Engineer Software Engineering Engineering Data Lake 147

Data Engineering Podcast

DECEMBER 17, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. With Materialize, you can!

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Data Engineering Podcast

NOVEMBER 19, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products. With Materialize, you can!

Project 147

Project Data Lake High Quality Data SQL 147

Data Engineering Podcast

DECEMBER 10, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management You shouldn't have to throw away the database to build with fast-changing data. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products.

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Monte Carlo

APRIL 24, 2023

At Uber, for example, data ingestion scale quickly surpassed what out-of-the-box solutions could support. In the early days, Kafka was used to capture events data while a combination of Sqoop and MapReduce were used to ingest transactional data from upstream databases. Missed Nishith’s 5 considerations?

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

DareData

JULY 29, 2020

With these points in mind, I argue that the biggest hurdle to the widespread adoption of these advanced techniques in the healthcare industry is not intrinsic to the industry itself, or in any way related to its practitioners or patients, but simply the current lack of high-quality data pipelines.

Healthcare 52

Healthcare Data Pipeline Medical Pipeline-centric 52

Monte Carlo

FEBRUARY 27, 2024

Organizations need to connect LLMs with their proprietary data and business context to actually create value for their customers and employees. They need robust data pipelines, high-quality data, well-guarded privacy, and cost-effective scalability. Data engineers. Who can deliver?

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Monte Carlo

APRIL 1, 2024

Implement Routine Data Audits Build a data cleaning cadence into your data teams’ schedule. Routine data quality checks will not only help to reduce the risk of discrepancies in your data, but it will also help to fortify a culture of high-quality data throughout your organization.

High Quality Data 52

High Quality Data Datasets Data Data Pipeline 52

Monte Carlo

JANUARY 3, 2024

But RAG development comes with a learning curve, even for your most talented data engineers. They need to know prompt engineering , vector databases and embedding vectors , data modeling, data orchestration , data pipelines and all for RAG. away from your data infrastructure being GenAI ready.

Technology 113

Technology Database Data Governance Data Engineering 113

Ripple Engineering

JANUARY 29, 2024

For Ripple's product capabilities, the Payments team of Ripple, for example, ingests millions of transactional records into databases and performs analytics to generate invoices, reports, and other related payment operations.    A lack of a centralized system makes building a single source of high-quality data difficult.

Database-centric 52

Database-centric Pipeline-centric NoSQL High Quality Data 52

Databand.ai

AUGUST 30, 2023

Data Consistency vs Data Integrity: Similarities and Differences Joseph Arnold August 30, 2023 What Is Data Consistency? Data consistency refers to the state of data in which all copies or instances are the same across all systems and databases.

Data Integration 52

Data Integration Data Cleanse Data Validation High Quality Data 52

Data Engineering Weekly

MARCH 3, 2024

Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

Ascend.io

JANUARY 10, 2024

AI models are only as good as the data they consume, making continuous data readiness crucial. Here are the key processes that need to be in place to guarantee consistently high-quality data for AI models: Data Availability: Establish a process to regularly check on data availability. Actionable tip?

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

Databand.ai

JULY 5, 2023

What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. Data observability tools allow teams to detect issues such as missing values, duplicate records, or inconsistent formats early on before they affect downstream processes.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Monte Carlo

JANUARY 10, 2024

Extrinsic data, meanwhile, is more about the context — it’s how your data interacts with the world outside and how it fits into the larger picture of your project or organization. Consider a database that holds customer details. usability) would be about extrinsic data quality.

Data Cleanse 52

Data Cleanse Data Engineering Data Engineer Engineering 52

Ascend.io

FEBRUARY 28, 2024

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Precisely

MARCH 14, 2023

Read Quality data you can depend on – today, tomorrow, and beyond For many years Precisely customers have ensured the accuracy of data across their organizations by leveraging our leading data solutions including Trillium Quality, Spectrum Quality, and Data360 DQ+. What does all this mean for your business?

Data Integration 52

Data Integration High Quality Data BI Data 52

Databand.ai

JULY 10, 2023

An observability platform is a comprehensive solution that allows data engineers to monitor, analyze, and optimize their data pipelines. By providing a holistic view of the data pipeline, observability platforms help teams rapidly identify and address issues or bottlenecks.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

Monte Carlo

MARCH 24, 2023

The key differences are that data integrity refers to having complete and consistent data, while data validity refers to correctness and real-world meaning – validity requires integrity but integrity alone does not guarantee validity. What is Data Integrity? How Do You Maintain Data Integrity?

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Knowledge Hut

MARCH 5, 2024

A Data Engineer's core responsibility is to process large amounts of data and optimize its storage. Data engineers also analyze the kind of data that should be retrieved and stored. Healthcare is regulated, so your data infrastructure must meet extensive compliance and audit requirements.

Data Engineering 52

Data Engineering Data Engineer Engineering Education 52

Monte Carlo

AUGUST 9, 2023

Bad data in—bad data products out. And that puts data quality at the top of every CTO’s priority list. In this post, we’ll look at 8 of the most common data quality issues affecting data pipelines, how they happen, and what you can do to find and resolve them. As in all things, it depends.

Finance 52

Finance High Quality Data SQL Data 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Monte Carlo

DECEMBER 19, 2022

When it comes to data engineering, quality issues are a fact of life. Like all software and data applications, ETL/ELT systems are prone to failure from time-to-time. Among other factors, data pipelines are reliable if: The data is current, accurate, and complete. The data is unique and free from duplicates.

High Quality Data 52

High Quality Data Data Bytes SQL 52

Monte Carlo

OCTOBER 5, 2023

Ensure data quality Even if there are no errors during the ETL process, you still have to make sure the data meets quality standards. High-quality data is crucial for accurate analysis and informed decision-making. Your data pipelines will thank you.

Data Cleanse 52

Data Cleanse ETL Tools Datasets High Quality Data 52

Ascend.io

JUNE 8, 2023

The Essential Six Capabilities To set the stage for impactful and trustworthy data products in your organization, you need to invest in six foundational capabilities. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Monte Carlo

JUNE 16, 2023

Data quality has broad applications across industries, but its importance and degree of quality required is also contextual to the use case. For example, in marketing, high-quality data can help businesses better understand their customers, allowing them to create more targeted and effective campaigns.

Data Integration 52

Data Integration Hospitality Banking Healthcare 52