Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. AI drives the demand for data integrity.

Data Analytics 59

Data Analytics Data Governance Government Data Integration 59

Precisely

DECEMBER 9, 2024

Top reported benefits of data governance programs include improved quality of data analytics and insights (58%), improved data quality (58%), and increased collaboration (57%). Data governance is a top data integrity challenge, cited by 54% of organizations second only to data quality (56%).

Data Governance 64

Data Governance Government Data Integration Architecture 64

Ascend.io

DECEMBER 4, 2024

Further Exloration: What is data automation? 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.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Precisely

MAY 23, 2024

Key takeaways: Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business. Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.

Data Integration 64

Data Integration Metadata Telecommunication Data Governance 64

Data Engineering Podcast

FEBRUARY 26, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Are you tired of dealing with the headache that is the 'Modern Data Stack'? It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze. We feel your pain.

Building 147

Building Machine Learning Metadata Data Integration 147

Data Engineering Podcast

FEBRUARY 19, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze.

IT 147

IT Data Lake Metadata Data Warehouse 147

Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like.

Metadata 52

Metadata IT Government High Quality Data 52

Data Engineering Podcast

MARCH 5, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze.

Building 147

Building Machine Learning Database Design Metadata 147

phData: Data Engineering

NOVEMBER 1, 2024

Monitor and Adapt: Continuously assess the impact of GenAI on data governance practices and be prepared to adapt policies as technologies evolve. Data governance is the only way to ensure those requirements are met. Chief Technology Officer, Finance Industry For all the quotes, download the Trendbook today!

Government 52

Government Data Governance Finance Metadata 52

Ascend.io

DECEMBER 4, 2024

Further Exloration: What is data automation? 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.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

Data Management 52

Data Management Management Metadata Database-centric 52

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Data Engineering Podcast

NOVEMBER 20, 2022

He explains the constraints that he and his team are faced with and the various challenges that they have overcome to build useful data products on top of a legacy platform where they don’t control the end-to-end systems. Atlan is the metadata hub for your data ecosystem. Closing Announcements Thank you for listening!

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Precisely

MAY 31, 2023

To innovate, compete, and grow in the current macroeconomic environment, enterprises must approach data strategically. A sound data strategy doesn’t happen by accident; it’s built on a foundation of data integrity , including accuracy, consistency, and rich context. Many organizations still struggle with data integrity.

Data Integration 52

Data Integration Metadata Data Governance Data 52

Precisely

MAY 23, 2024

Key takeaways: Quickly adapt to market changes by easily adding new data sources and targets, ensuring your IT landscape evolves at the pace of your business. Gain a competitive edge with real-time data integration, crucial for time-sensitive decisions and actions in fraud detection and customer interactions.

Data Integration 52

Data Integration Metadata Telecommunication Data Governance 52

phData: Data Engineering

NOVEMBER 8, 2024

Track data files within the table along with their column statistics. Open table formats enable efficient data management and retrieval by storing these files chronologically, with a history of DDL and DML actions and an index of data file locations. It can also be integrated into major data platforms like Snowflake.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Data Engineering Podcast

MARCH 18, 2023

He also explains why data security is distinct from application security and some methods for reducing the challenge of working across different data systems. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Join in with the event for the global data community, Data Council Austin.

Data Security 130

Data Security Machine Learning Data Science Metadata 130

Data Engineering Podcast

MARCH 25, 2023

In this episode they explain why streaming architectures are so challenging, how they have designed Grainite to be robust and scalable, and how you can start using it today to build your streaming data applications without all of the operational headache. As your business adapts, so should your data.

MySQL 130

MySQL Python Architecture Machine Learning 130

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Architecture 124

Architecture Metadata Kafka Government 124

Snowflake

NOVEMBER 29, 2023

Also, the associated business metadata for omics, which make it findable for later use, are dynamic and complex and need to be captured separately. Additionally, the fact that they need to be standardized makes the data discovery effort challenging for downstream analysis. The principles emphasize machine-actionability (i.e.,

Metadata 111

Metadata Healthcare Medical Data Storage 111

Data Engineering Weekly

FEBRUARY 18, 2025

This capability, termed Union Read, allows both layers to work in tandem for highly efficient and accurate data access. Confluent Tableflow can bridge Kafka and Iceberg data, but that is just a data movement that data integration tools like Fivetran or Airbyte can also achieve.

Kafka 73

Kafka Lambda Architecture SQL Architecture 73

Data Engineering Podcast

FEBRUARY 27, 2022

In this episode Tobias Macey, the host of the show, reflects on his plans for building a data platform and what he has learned from running the podcast that is influencing his choices. Data integration (extract and load) What are your data sources? Data integration (extract and load) What are your data sources?

Designing 100

Designing Metadata Data Lake Relational Database 100

Precisely

JUNE 22, 2023

As the financial services landscape has become more complex and sophisticated, the concept of data quality has evolved to imply a holistic approach that encompasses the overall trustworthiness of data. They have found ways to curate and manage data to instill confidence among decision-makers.

Data Integration 52

Data Integration Banking Data Governance Government 52

Data Engineering Podcast

DECEMBER 25, 2022

In order to condense that acquired knowledge into a format that is useful to everyone Scott Hirleman turns the tables in this episode and asks Tobias about the tactical and strategic aspects of his experiences applying those lessons to the work of building a data platform from scratch. Atlan is the metadata hub for your data ecosystem.

Building 100

Building Metadata Business Intelligence Data Lake 100

Data Engineering Podcast

MARCH 22, 2021

In this episode Raghu Murthy, founder and CEO of Datacoral, does a deep dive on how he and his team manage change data capture pipelines in production. What are the factors that you need to consider when deciding whether to implement a CDC system for a given data integration? What are the alternatives to CDC?

Data Warehouse 100

Data Warehouse Metadata Hadoop Data Lake 100

AltexSoft

OCTOBER 8, 2021

The good news is, businesses can choose the path of data integration to make the most out of the available information. The bad news is, integrating data can become a tedious task, especially when done manually. Data integration in a nutshell. Data integration process. That’s a lot of work.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Precisely

JUNE 24, 2024

His key takeaways from the conversation were that “ data leaders are under tremendous pressure to collaborate within the C-Suite on projects that deliver true business value. Explore the key topics and insights from this event below, and get inspired to apply these takeaways for success in your own data-driven journey.

Food 94

Food Data Analytics Pharmaceutical Consulting 94

Maxime Beauchemin

AUGUST 28, 2017

It’s the task of the business intelligence (now data engineering) teams to solve these issues with methodologies that enforces consensus, like Master Data Management (MDM), data integration , and an ambitious data warehousing program.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineering 174

U-Next

SEPTEMBER 7, 2022

Maintaining communication with your staff, which necessitates correct employee data , is one approach to improve it. . What Is Employee Data Management? . Employee database management is a self-service system that allows employees to enter, update and assess their data. Improved Data Security and Sharing.

Data Management 52

Data Management Management Electronics Database 52

ProjectPro

FEBRUARY 16, 2023

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. Data integration with ETL has changed in the last three decades.

AWS 52

AWS Data Management ETL Tools Management 52

Netflix Tech

MARCH 25, 2019

Data Landscape Design Goals At the project inception stage, we defined a set of design goals to help guide the architecture and development work for data lineage to deliver a complete, accurate, reliable and scalable lineage system mapping Netflix’s diverse data landscape. push or pull.

Building 90

Building Metadata Transportation Data Ingestion 90

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 92

Metadata Data Architecture BI Machine Learning 92

Precisely

JULY 15, 2024

Key Takeaways Data Mesh is a modern data management architectural strategy that decentralizes development of trusted data products to support real-time business decisions and analytics. However, complex architectures and data silos make that difficult. One strategy being leveraged is a data mesh.

Data Governance 72

Data Governance Data Integration Government Data 72

Towards Data Science

FEBRUARY 6, 2024

Operational data management in Data Mesh A Data Mesh implementation improved my experience in these aspects: Knowledge : I could quickly identify the owners of the exposed data. The distance between the owner and the domain that generated the data is key to expedite further analytical development.

Systems 98

Systems Raw Data Metadata Data Cleanse 98

Data Engineering Podcast

FEBRUARY 13, 2022

In this episode CEO and founder Soumyadeb Mitra explains how Rudderstack compares to the various other tools and platforms that share some overlap, how to set it up for your own data needs, and how it is architected to scale to meet demand. You can observe your pipelines with built in metadata search and column level lineage.

Building 100

Building Hadoop Data Pipeline Metadata 100

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. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Data Management 43

Data Management Management Metadata Government 43