Data Engineering Podcast

JULY 31, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The only thing worse than having bad data is not knowing that you have it. What are the core problems that Manta aims to solve?

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

SEPTEMBER 18, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. What are the contributing factors that lead to fragmentation of visibility for data workflows at different stages?

Building 100

Building Metadata MongoDB MySQL 100

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. You can observe your pipelines with built in metadata search and column level lineage.

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Databand.ai

AUGUST 30, 2023

DataOps tools should provide a comprehensive data cataloging solution that allows organizations to create a centralized repository of their data assets, complete with metadata, data lineage information, and data samples.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Data Engineering Podcast

JANUARY 30, 2022

You can observe your pipelines with built in metadata search and column level lineage. Finally, if you have existing workflows in AbInitio, Informatica or other ETL formats that you want to move to the cloud, you can import them automatically into Prophecy making them run productively on Spark.

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

Data Engineering Podcast

MAY 3, 2021

Summary The Data industry is changing rapidly, and one of the most active areas of growth is automation of data workflows. Taking cues from the DevOps movement of the past decade data professionals are orienting around the concept of DataOps. Closing Announcements Thank you for listening!

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Workfall

JUNE 12, 2023

It facilitates data synchronisation, replication, real-time analytics, and event-driven processing, empowering data-driven decision-making and operational efficiency. These additional columns store metadata like timestamps, user IDs, and change types, ensuring granular change tracking and auditability.

Telecommunication 80

Telecommunication Metadata Healthcare Finance 80

Data Engineering Podcast

APRIL 5, 2021

What portions of the data workflow is Atlan responsible for? What components of the data stack might Atlan replace? How would you characterize Atlan’s position in the current data ecosystem? What makes Atlan stand out from other systems for data cataloguing, metadata management, or data governance?

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Weekly

OCTOBER 30, 2022

Editor’s Note: The current state of the Data Catalog The results are out for our poll on the current state of the Data Catalogs. The highlights are that 59% of folks think data catalogs are sometimes helpful. We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Data Engineering Weekly

MARCH 11, 2023

We also touch on the idea that data creation will be a decentralized process and the role of tools like data contracts in enabling successful decentralized data modeling. We emphasize the importance of creating high-quality data and the need for technological and organizational solutions to achieve this goal.

Data Engineering 52

Data Engineering Data Engineer Engineering High Quality Data 52

Data Engineering Podcast

AUGUST 5, 2019

Finding the data that you need is tricky, and Amundsen will help you solve that problem. And as your data grows in volume and complexity, there are foundational principles that you can follow to keep data workflows streamlined. Links Amundsen Data Council Presentation Strata Presentation Blog Post Lyft Airflow Podcast.__init__

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

Databand.ai

AUGUST 30, 2023

Unified DataOps represents a fresh approach to managing and synchronizing data operations across several domains, including data engineering, data science, DevOps, and analytics. The goal of this strategy is to streamline the entire process of extracting insights from raw data by removing silos between teams and technologies.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Cloudera

FEBRUARY 11, 2019

“Disruption slows as cloud and nonrelational technology take their place beside traditional approaches , the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA.” Established, mature technologies represent an integral part of DMSA.

Data Management 43

Data Management Management Metadata Government 43

Knowledge Hut

SEPTEMBER 29, 2023

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

JUNE 7, 2021

A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Cassandra excels at streaming data analysis. Data access options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Ascend.io

MAY 19, 2023

Whenever a new technology frontier appears (Stage 1 of the innovation cycle), the “Innovators” (coined by Geoffrey A. In the data world, this disruption manifested in the form of cloud computing with technologies such as Redshift, Snowflake, and Spark. Let’s review it briefly. Second, it enhances governance and security.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. Metadata database.

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

AltexSoft

SEPTEMBER 21, 2023

This endeavor would unwittingly plant the seeds for Elasticsearch, a technology that today drives data search and analytics for businesses around the globe. But like any technology, it has its share of pros and cons. Fields Fields are the smallest data unit in Elasticsearch, serving as key-value pairs within documents.

Engineering 52

Engineering NoSQL Programming Language Java 52

Cloudera

AUGUST 21, 2020

The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from. Data lineage, personally identifiable information or PPI and metadata all fall under a broad data governance banner which is critically important in terms of what needs to be protected and mapped out.

Banking 61

Banking Kafka Cloud Storage Government 61

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. to build products and services for various purposes.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Databand.ai

DECEMBER 29, 2022

Colleen is also experienced in building and leading diverse teams through business reorganization and transforming existing data ecosystems by maturing them into modern and robust technology stacks. On LinkedIn, Huy posts frequently about data strategy, data analytics, startups, and career advice.

BI 52

BI Consulting Data Science Data Governance 52

Netflix Tech

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Monte Carlo

JUNE 14, 2023

Apache Spark – Labeled as a unified analytics engine for large scale data processing, many leverage this open source solution for streaming use cases, often in conjunction with Databricks. Data orchestration Airflow : Airflow is the most common data orchestrator used by data teams. Now Go Build Some Data Pipelines!

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Technology needs to be accessible to a much broader user base.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Technology needs to be accessible to a much broader user base.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52