Data Engineering Podcast

OCTOBER 15, 2021

Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. How is the governance of DataHub being managed?

Metadata 100

Metadata BI Data Warehouse Government 100

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Data lineage and metadata systems are a hot topic right now. What are the core problems that Manta aims to solve?

IT 100

IT Metadata MongoDB MySQL 100

Knowledge Hut

SEPTEMBER 25, 2023

You can learn deeply about the Azure learning journey that leads to the position of an Azure Data Engineer Associate on the Microsoft Azure platform. Who is an Azure Data Engineer? As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. 3. Expansion beyond core data management. It accomplishes this while avoiding issues around interoperability among the workloads.

Data Management 43

Data Management Management Metadata Government 43

Ascend.io

DECEMBER 19, 2023

You’re extracting and loading data first, then transforming it in Snowflake’s cloud data warehouse. The GUI often allows for easy visualization and monitoring of data pipelines, which can be particularly beneficial for complex workflows. that you can combine to create custom data workflows.

ETL Tools 52

ETL Tools IT Data Pipeline Data Warehouse 52

Knowledge Hut

DECEMBER 28, 2023

Today, organizations seek skilled professionals who can harness data’s power to drive informed decisions. As technology evolves, cloud platforms have emerged as the cornerstone of modern data management. Its comprehensive suite of services can handle data at scale. Who is an Azure Data Engineer?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JANUARY 1, 2022

In this episode Emily Riederer shares her work to create a controlled vocabulary for managing the semantic elements of the data managed by her team and encoding it in the schema definitions in her data warehouse. star/snowflake schema, data vault, etc.) Who should be involved in that design process?

Data Warehouse 100

Data Warehouse BI Data Workflow Coding 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). Data lakes are notoriously complex. To start, can you share your definition of what constitutes a "Data Lakehouse"?

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

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. 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.

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Monte Carlo

MAY 14, 2024

Let’s revisit how several of those key table formats have emerged and developed over time: Apache Avro : Developed as part of the Hadoop project and released in 2009, Apache Avro provides efficient data serialization with a schema-based structure.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. By improving data quality, organizations can generate more accurate and reliable insights from their data analytics processes.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Data Engineering Podcast

APRIL 3, 2022

Summary The flexibility of software oriented data workflows is useful for fulfilling complex requirements, but for simple and repetitious use cases it adds significant complexity. In this episode Satish Jayanthi explains how he is building a framework to allow enterprises to move quickly while maintaining guardrails for data workflows.

Data Warehouse 100

Data Warehouse Data Workflow Data Architecture SQL 100

Data Engineering Podcast

OCTOBER 29, 2021

In this episode Ahmed Elsamadisi shares his journey to find a more flexible and universal data model in the form of the "activity schema" that is powering the Narrator platform, and how it has allowed his customers to perform self-service exploration of their business domains without being blocked by schema evolution in the data warehouse.

Data Warehouse 100

Data Warehouse BI Data Workflow Data Pipeline 100

Data Engineering Podcast

DECEMBER 18, 2022

In this episode Abe Gong brings his experiences with the Great Expectations project and community to discuss the technical and organizational considerations involved in implementing these constraints to your data workflows. Can you describe what your conception of a data contract is?

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Data Engineering Podcast

NOVEMBER 14, 2021

In this episode Michael Harper advocates for proactive data quality and starting with the source, rather than being reactive and having to work backwards from when a problem is found. Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams.

Data Warehouse 100

Data Warehouse BI Data Workflow Data 100

Data Engineering Podcast

JUNE 1, 2021

In this episode he explains the utility of a low code solution that lets non engineers create their own self-serve pipelines, how the Shipyard platform is designed to make that possible, and how it allows engineers to create reusable tasks to satisfy the specific needs of the business. task-based, data assets, etc.)

Data Pipeline 100

Data Pipeline Data Warehouse Data Workflow Data 100

Meltano

OCTOBER 5, 2022

We’ll explain what a data engineer is, what the job entails, and how to become a data engineer. Plus, we’ll explain how data engineers use Meltano, our DataOps platform, for efficient data management. What Is Data Engineering? A data engineer’s focus is mainly on raw data, formats, security, and storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Data Engineering Weekly

JANUARY 15, 2023

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. Take control of your customer data today. Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. They are different tools with different capabilities, designed to handle different tasks. The tools are designed to simply close this gap, sometimes even in a simple 1-source to 1-target approach.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Meltano

OCTOBER 5, 2022

Think about data operations as a factory assembly line where a warehouse engineer optimizes and automates processes to increase productivity and product quality. In the same way, a DataOps engineer designs the data assembly line that enables data scientists to derive insights from data analytics faster and with fewer errors.

Engineering 52

Engineering Raw Data Data Pipeline ETL Tools 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Telm.ai — Telm.ai

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

Databand.ai

DECEMBER 29, 2022

He believes in making data do the work through proper data management based on strategic rationale and business alignment. On LinkedIn, he posts frequently about big data, master data, data science, data management, and data storytelling.

BI 52

BI Consulting Data Science Data Governance 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59