Knowledge Hut

MARCH 7, 2024

Two, it creates a commonality of data definitions, concepts, metadata and the like. The traditional data management and data warehouses, and the sequence of data transformation, extraction and migration- all arise a situation in which there are risks for data to become unsynchronized.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Snowflake

APRIL 29, 2024

ICT Risk Management Framework and Governance FEs’ leadership teams must define a risk management strategy, inclusive of both their internally managed critical systems and the risks associated with their ICT providers. This prioritizes security measures and simplifies data discovery.

Transportation 84

Transportation Data Governance Government Consulting 84

Databand.ai

JULY 19, 2023

Data lineage tools are not a new concept. However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important?

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

The Modern Data Company

APRIL 15, 2024

Understands how different pieces of data (books) relate to each other, helping users find related information. Keeps the library orderly, adjusting as new data arrives. Tracks key performance indicators to understand the use and value of the data. Manages information about data access and monitors data quality.

Government 52

Government Metadata Data Data Lake 52

Databand.ai

AUGUST 30, 2023

This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management. Data profiling: Regularly analyze dataset content to identify inconsistencies or errors. This may include tasks such as data profiling, data cleansing, and metadata management.

Building 52

Building Data Cleanse Data Governance Datasets 52

Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Precisely

JUNE 6, 2023

Tendü Yogurtçu offered that organizations today are viewing data as a product, and they are working to streamline access to both data and metadata for faster insights that help business users deliver tangible value. Data observability also helps users identify the root cause of problem in the data.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Precisely

MAY 31, 2023

With the right enterprise-grade technology, organizations can find simple solutions to complex data integrity challenges at scale. The act of bringing data into hybrid cloud and VPC environments doesn’t solve data integrity challenges by itself. The end result is that users can’t trust their data because it lacks integrity.

Data Integration 52

Data Integration Metadata Data Governance Data 52

phData: Data Engineering

SEPTEMBER 19, 2023

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Data Engineering Podcast

NOVEMBER 9, 2020

He also shares the internal architecture, how he approached the design to make it accessible and easy to use, and how it autodiscovers the schemas and metadata for your source systems. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask.

Building 100

Building PostgreSQL BI Metadata 100

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Summary As your data needs scale across an organization the need for a carefully considered approach to collection, storage, organization, and access becomes increasingly critical. How do you define data curation? What are some of the high level concerns that are encapsulated in that effort?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. Integration with workflow management .

Data Governance 59

Data Governance Government Metadata Data Science 59

Cloudera

FEBRUARY 16, 2022

Within the CML data service, model lineage is managed and tracked at a project level by the SDX. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Cloudera

NOVEMBER 10, 2021

One such major change for CDH users is the replacement of Sentry with Ranger for authorization and access control. . For big data platforms like Cloudera’s stack that are used by multiple business units with many users, upgrading even minor versions must be a well-planned activity to reduce the impact to users and business.

Hadoop 74

Hadoop SQL Database Kafka 74

AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. What is data governance? billion in 2020 to $5.28

Data Governance 52

Data Governance Government Healthcare Programming 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

The Modern Data Company

MARCH 7, 2023

Data governance can be a powerful agent in scaling the use and distribution of trusted data throughout the company. However, more often than not, it conjures up the idea of a central authority strictly guarding against such access. If you missed it, make sure to catch up on Part 1 – Data Timeliness.

Data Governance 52

Data Governance Government Metadata Datasets 52

dbt Developer Hub

JULY 2, 2023

Agile development ​ dbt Cloud includes built-in Git with accessible features directly from its IDE, which simplifies development immensely. Once a developer is happy with their additions or changes to the Data Vault codebase, they can commit the code within the IDE and open a Pull Request, triggering a code review process.

Cloud 52

Cloud Data Warehouse Data BI 52

Snowflake

NOVEMBER 29, 2023

In medicine, lower sequencing costs and improved clinical access to NGS technology has been shown to increase diagnostic yield for a range of diseases, from relatively well-understood Mendelian disorders, including muscular dystrophy and epilepsy , to rare diseases such as Alagille syndrome.

Metadata 84

Metadata Healthcare Medical Data Storage 84

Data Engineering Podcast

NOVEMBER 26, 2023

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. One of the core complexities that needs to be addressed is the fractal set of integrations that need to be managed across the individual components. Closing Announcements Thank you for listening!

Architecture 147

Architecture Data Lake High Quality Data SQL 147

François Nguyen

MARCH 7, 2021

In this article, Juan Sequada gives maybe one of the best definition of Data Mesh ” It is paradigm shift towards a distributed architecture that attempts to find an ideal balance between centralization and decentralization of metadata and data management.”

Government 130

Government Data Governance Data Metadata 130

Monte Carlo

MAY 20, 2024

On the other hand, a data catalog aims to provide a macro view of an organization’s data landscape. It emphasizes discoverability, accessibility, and governance of data assets, promoting an integrated approach to data management across multiple platforms and stakeholders.

Datasets 52

Datasets Government Data Business Analyst 52

Cloudera

MARCH 23, 2022

Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. By being a truly open table format, Apache Iceberg fits well within the vision of the Cloudera Data Platform (CDP). What is Apache Iceberg? 2: Open formats.

Metadata 88

Metadata Data Architecture BI Machine Learning 88

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. This demands the implementation of advanced data integration techniques, such as real-time streaming ingestion, batch processing, and API-based access.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Monte Carlo

MAY 25, 2023

That’s why we’re excited to announce that uniting diverse data team personas to collectively ensure data quality just got easier, thanks to a new integration between Monte Carlo’s data observability platform and Atlan’s active metadata platform.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

Towards Data Science

MAY 19, 2023

Business users are unable to find and access data assets critical to their workflows. Data engineers spend countless hours troubleshooting broken pipelines. Absence or poor adoption of company-wide guidelines surrounding the creation and deployment of data products. Is it the responsibility of the data product managers?

Pipeline-centric 105

Pipeline-centric Data Software Engineer Software Engineering 105

Monte Carlo

NOVEMBER 14, 2023

Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. How Apache Iceberg tables structure metadata. Without a central query log, your team can run the risk of data loss and lack of data governance.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Cloudera

DECEMBER 20, 2021

But balancing a strong layer of security and governance with easy access to data for all users is no easy task. Another option — a more rewarding one — is to include centralized data management, security, and governance into data projects from the start. You can become a data hero too.

Government 86

Government Data Security Banking Metadata 86

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. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk.

Data Architecture 82

Data Architecture Architecture Management Banking 82

Ascend.io

JULY 19, 2023

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing.

Data Governance 40

Data Governance Government Metadata Data 40

Precisely

JUNE 22, 2023

To deliver maximum benefits, these initiatives require an integrated, clean, accurate, contextualized, and enriched view of the data. Historically, data problems were addressed using point solutions that solve specific data challenges. That calls for a deeper understanding of data integrity and collaboration across silos.

Data Integration 52

Data Integration Banking Data Governance Government 52