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. Atlan is the metadata hub for your data ecosystem. Data lineage and metadata systems are a hot topic right now.

IT 100

IT Metadata MongoDB MySQL 100

Monte Carlo

JANUARY 16, 2024

Factor in the advertising strategies, media production, partner programming, audience analytics…and you’re looking at an ocean of data that would fill even the deepest trench (we’d like a television show about that too, please!). So how does Fox’s data strategy support these complex data workflows? Build what you want.

Government 52

Government High Quality Data Data Governance Entertainment 52

Data Engineering Weekly

NOVEMBER 24, 2024

Canva writes about its custom solution using dbt and metadata capturing to attribute costs, monitor performance, and enable data-driven decision-making, significantly enhancing its Snowflake environment management. link] Grab: Metasense V2 - Enhancing, improving, and productionisation of LLM-powered data governance.

Data Engineering 59

Data Engineering Data Engineer Engineering Insurance 59

Ascend.io

DECEMBER 4, 2024

Deploy DataOps DataOps , or Data Operations, is an approach that applies the principles of DevOps to data management. It aims to streamline and automate data workflows, enhance collaboration and improve the agility of data teams. How effective are your current data workflows?

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

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

Ascend.io

DECEMBER 4, 2024

Deploy DataOps DataOps , or Data Operations, is an approach that applies the principles of DevOps to data management. It aims to streamline and automate data workflows, enhance collaboration and improve the agility of data teams. How effective are your current data workflows?

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

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

Cloudera

FEBRUARY 11, 2019

Only Cloudera provides multi-cloud choice and hybrid cloud flexibility – powered by cloud-native technologies – for a public cloud experience across public and private clouds, significantly simplifying IT operations and governance. 3. Expansion beyond core data management.

Data Management 44

Data Management Management Metadata Government 44

Cloudera

AUGUST 21, 2020

Beyond volume, velocity, and variety the two biggest challenges for businesses around streaming analytics are security and governance. Organizations need to handle them in a transparent way because data hacking can happen at any point in the data-in-motion journey.

Banking 63

Banking Kafka Cloud Storage Government 63

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

Monte Carlo

OCTOBER 1, 2024

AI-powered Monitor Recommendations that leverage the power of data profiling to suggest appropriate monitors based on rich metadata and historic patterns — greatly simplifying the process of discovering, defining, and deploying field-specific monitors.

Database 52

Database Metadata Software Engineer Software Engineering 52

Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. Technical Challenges Choosing appropriate tools and technologies is critical for streamlining data workflows across the organization.

Data Governance 40

Data Governance Data Cleanse Government Data Science 40

Databand.ai

DECEMBER 29, 2022

Follow Ravit on LinkedIn 5) Priya Krishnan Head of Product Management, Data and AI at IBM Priya is an innovative, customer-focused, data-driven product executive with over 16 years of experience in global product management, strategy, and GTM roles to commercialize and monetize in-demand enterprise solutions.

BI 52

BI Consulting Data Science Data Governance 52

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents. Scaling data governance.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Ascend.io

MAY 19, 2023

The holistic approach of the post-modern data stack translates into numerous benefits: First, it accelerates pinpointing and troubleshooting pipeline hotspots with a single console that observes the entire data pipeline and all its processes. Second, it enhances governance and security.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

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. Continuously review and optimize costs.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. Data in Elasticsearch is organized into documents, which are then categorized into indices for better search efficiency.

Engineering 52

Engineering NoSQL Programming Language Java 52

Ascend.io

MARCH 17, 2023

Today, RPA is heavily used in telecommunications, insurance, banking, finance, and healthcare companies to streamline their reconciliation, invoicing, and governance processes. For data pipeline automation, these previous approaches have foundered on one important barrier: the need to scale.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Today, RPA is heavily used in telecommunications, insurance, banking, finance, and healthcare companies to streamline their reconciliation, invoicing, and governance processes. For data pipeline automation, these previous approaches have foundered on one important barrier: the need to scale.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

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

Data Engineering Weekly

DECEMBER 16, 2024

Automated Data Classification and Governance LLMs are reshaping governance practices. Grab’s Metasense , Uber’s DataK9 , and Meta’s classification systems use AI to automatically categorize vast data sets, reducing manual efforts and improving accuracy.

Data Engineering 59

Data Engineering Data Engineer Engineering Unstructured Data 59

AltexSoft

MARCH 14, 2023

Also, Databricks are pioneering the lakehouse concept that makes it possible to use data management features inherent in data warehousing on the raw data stored in a low-cost data lake owing to its metadata layer. The data governance, orchestration, and monitoring component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Edureka

JULY 3, 2024

You can extract data efficiently and once gathered, you can transform this data using built-in or custom transformations, and then load it into your desired destination. For optimum data consistency and reliability, devs can incorporate Delta Lake within Databricks workflows, allowing for ACID transactions on data lakes.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Data Engineering Weekly

DECEMBER 18, 2024

DEW published The State of Data Engineering in 2024: Key Insights and Trends , highlighting the key advancements in the data space in 2024. We witnessed the explosive growth of Generative AI, the maturing of data governance practices, and a renewed focus on efficiency and real-time processing. But what does 2025 hold?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52