Data Engineering Podcast

FEBRUARY 4, 2024

RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage layer. In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Want to see Starburst in action?

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Data Engineering Podcast

APRIL 21, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action?

Data Lake 182

Data Lake High Quality Data Data Pipeline Machine Learning 182

Data Engineering Podcast

NOVEMBER 12, 2023

Generative AI has accelerated the ability of developer tools to provide useful suggestions that speed up the work of engineers. Tabnine is one of the main platforms offering an AI powered assistant for software engineers. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Data lakes are notoriously complex.

Software Engineer 147

Software Engineer Software Engineering Engineering Data Lake 147

Data Engineering Podcast

FEBRUARY 11, 2024

Summary Sharing data is a simple concept, but complicated to implement well. There are also numerous technical considerations to be made, particularly if the producer and consumer of the data aren't using the same platforms. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 147

Data Lake High Quality Data Government Data Pipeline 147

Data Engineering Podcast

MARCH 17, 2024

Summary A significant portion of data workflows involve storing and processing information in database engines. 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. Data lakes are notoriously complex.

Database 147

Database Data Lake High Quality Data Data Workflow 147

Data Engineering Podcast

MARCH 10, 2024

Summary Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. Data lakes are notoriously complex. Join us at the top event for the global data community, Data Council Austin.

Data Lake 147

Data Lake High Quality Data Data Pipeline Architecture 147

Data Engineering Podcast

MAY 5, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action?

Building 147

Building Data Lake High Quality Data Machine Learning 147

Data Engineering Podcast

APRIL 28, 2024

In this episode he explains the data collection and preparation process, the collection of model types and sizes that work together to power the experience, and how to incorporate it into your workflow to act as a second brain. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action?

Building 147

Building Data Lake High Quality Data Machine Learning 147

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. Want to see Starburst in action?

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

JANUARY 28, 2024

Summary Monitoring and auditing IT systems for security events requires the ability to quickly analyze massive volumes of unstructured log data. Cliff Crosland co-founded Scanner to provide fast querying of high scale log data for security auditing. SIEM) A query engine is useless without data to analyze.

Data Lake 147

Data Lake Building High Quality Data AWS 147

Data Engineering Weekly

MARCH 3, 2024

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

Data Engineering Podcast

JANUARY 7, 2024

Summary Data processing technologies have dramatically improved in their sophistication and raw throughput. Unfortunately, the volumes of data that are being generated continue to double, requiring further advancements in the platform capabilities to keep up. What are the open questions today in technical scalability of data engines?

Data Process 147

Data Process Process Data Lake High Quality Data 147

Data Engineering Podcast

FEBRUARY 25, 2024

Summary Building a database engine requires a substantial amount of engineering effort and time investment. When Paul Dix decided to re-write the InfluxDB engine he found the Apache Arrow ecosystem ready and waiting with useful building blocks to accelerate the process. Data lakes are notoriously complex.

Database 162

Database Technology Data Lake High Quality Data 162

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. Data lakes are notoriously complex. Join us at the top event for the global data community, Data Council Austin. Your first 30 days are free!

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

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

DECEMBER 24, 2023

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. Data lakes are notoriously complex.

Kafka 245

Kafka Data Lake High Quality Data SQL 245

Data Engineering Podcast

DECEMBER 31, 2023

Summary Working with financial data requires a high degree of rigor due to the numerous regulations and the risks involved in security breaches. In this episode Andrey Korchack, CTO of fintech startup Monite, discusses the complexities of designing and implementing a data platform in that sector. Want to see Starburst in action?

Designing 130

Designing Data Lake High Quality Data SQL 130

Data Engineering Podcast

MARCH 31, 2024

Summary Working with data is a complicated process, with numerous chances for something to go wrong. 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. 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

NOVEMBER 26, 2023

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. Data lakes are notoriously complex.

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Data Engineering Podcast

DECEMBER 17, 2023

Summary The "modern data stack" promised a scalable, composable data platform that gave everyone the flexibility to use the best tools for every job. In this episode founder Tarush Aggarwal explains how the realities of the modern data stack are impacting data teams and the work that they are doing to accelerate time to value.

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Ascend.io

APRIL 27, 2023

Going into the Data Pipeline Automation Summit 2023, we were thrilled to connect with our customers and partners and share the innovations we’ve been working on at Ascend. The summit explored the future of data pipeline automation and the endless possibilities it presents.

Data Pipeline 52

Data Pipeline Pipeline-centric Data Validation Data Engineering 52

Monte Carlo

FEBRUARY 27, 2024

If you’re a data engineer experiencing GenAI-induced whiplash, you’re not alone. On one hand, everyone’s talking about whether GenAI’s not-insignificant data engineering skills are going to automate away their jobs. They need robust data pipelines, high-quality data, well-guarded privacy, and cost-effective scalability.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Monte Carlo

APRIL 24, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. But it’s not just our data platform that impacts how we define the problem and its solution.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

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

NOVEMBER 19, 2023

Summary The dbt project has become overwhelmingly popular across analytics and data engineering teams. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data projects are notoriously complex. Data lakes are notoriously complex.

Project 147

Project Data Lake High Quality Data SQL 147

Data Engineering Podcast

NOVEMBER 5, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.

PostgreSQL 147

PostgreSQL Data Lake High Quality Data SQL 147

Knowledge Hut

MARCH 5, 2024

Data engineers are highly in demand and short in supply. Data engineering is one of the hottest jobs that is trending across the globe. Singapore has a thriving technical market that has been on the lookout for data engineers. Who is Data Engineer and What Do They Do?

Data Engineering 52

Data Engineering Data Engineer Engineering Education 52

Data Engineering Podcast

DECEMBER 10, 2023

Unfortunately, it can often be complex or expensive to incorporate anomaly detection into your data platform. 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.

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Monte Carlo

JULY 27, 2023

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

DareData

JULY 29, 2020

The Challenges of Medical Data In recent times, there have been several developments in applications of machine learning to the medical industry. Odds are that your local hospital, pharmacy or medical institution's definition of being data-driven is keeping files in labelled file cabinets, as opposed to one single drawer.

Healthcare 52

Healthcare Data Pipeline Medical Pipeline-centric 52

Monte Carlo

MAY 3, 2024

It’s 2024, and the data estate has changed. Data systems are more diverse. But even though the data landscape is evolving, many enterprise data organizations are still managing data quality the “old” way: with simple data quality monitoring. Architectures are more complex.

High Quality Data 52

High Quality Data Data Architecture Media 52

Data Engineering Weekly

NOVEMBER 13, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. I'm a software engineer; how can I transition to a Machine Learning engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Monte Carlo

MAY 29, 2024

We’re surrounded by tons of data people, data conversation, and data keynotes to kick us all off. Join to learn his approach to building a robust data platform, and how his approach to monitoring for data quality can help you identify problems before they wreak havoc on your pipelines. Register here.

Cloud 69

Cloud Food Manufacturing Data Architect 69

Monte Carlo

JANUARY 10, 2024

What happens when you strip away all the noise of queries and pipelines and focus on the data itself? You get down to the intrinsic data quality. What’s the difference between intrinsic and extrinsic data quality? Intrinsic data quality is the quality of data assessed independently of its use case.

Data Cleanse 52

Data Cleanse Data Engineering Data Engineer Engineering 52

Monte Carlo

APRIL 1, 2024

But, for data engineers, there’s something else that comes pretty close to the top of that list: clean data. Data cleaning is an essential step to ensure your data is safe from the adage “garbage in, garbage out.” Define Clear Data Quality Standards 2. Implement Routine Data Audits 3.

High Quality Data 52

High Quality Data Datasets Data Data Pipeline 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52