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

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 Engineering Software Engineer 52

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

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

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

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

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

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 62

Banking Kafka Cloud Storage Government 62

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.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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