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

Cloudera

APRIL 18, 2024

In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular. Learn more about how Cloudera is accelerating enterprise AI.

Metadata 111

Metadata Government Data Governance Data 111

Cloudera

AUGUST 10, 2021

SDX enhancements for improved platform and data governance, including the following notable features: . We expand on this feature later in this blog. x, as well as documented rollback procedures to help customers with their move to CDP PvC Base, as mentioned in the blog introduction. . x, and 6.3.x, x, and 6.3.x,

Cloud 97

Cloud Kafka Metadata SQL 97

Cloudera

AUGUST 3, 2021

Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Improve Visibility within Supply Chains.

Manufacturing 111

Manufacturing Retail Government Entertainment 111

Cloudera

MAY 2, 2022

from China to the UK , new data governance and protection rules are coming in on an almost daily basis. This is not just to implement specific governance rules — such as tagging, metadata management, access controls, or anonymization — but to prepare for the potential for rules to change in the future. .

Cloud 105

Cloud Government Healthcare Metadata 105

Cloudera

DECEMBER 20, 2021

Understanding that the future of banking is data-driven and cloud-based, Bank of the West embraced cloud computing and its benefits, like remote capabilities, integrated processes, and flexible systems. The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Government 92

Government Data Security Banking Metadata 92

Cloudera

OCTOBER 10, 2024

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

IT 85

IT Data Lake Metadata Data Warehouse 85

Precisely

AUGUST 22, 2024

Both architectures tackle significant data management challenges such as integrating disparate data sources, improving data accessibility, automating management processes, and ensuring data governance and security. Problems it solves Data fabric addresses key data management and use challenges.

Data Governance 69

Data Governance Government High Quality Data Metadata 69

Snowflake

JUNE 5, 2024

To help organizations better govern AI, Snowflake Horizon is also advancing security, lineage and sharing capabilities for models. Additional built-in UI’s and privacy enhancements make it even easier to understand and manage sensitive data. Learn more in the blog.

Government 102

Government Accessibility Accessible Cloud 102

Cloudera

MARCH 22, 2023

Luke Roquet recently drilled into the topic of data observability with Mark Ramsey of Ramsey International (RI) to also cover the five pillars (freshness, distribution, volume, schema, and lineage) that describe the quality and reliability of data. And, crucial for a hybrid data platform, it does so across hybrid cloud.

Data Governance 89

Data Governance Government Business Analyst Metadata 89

Data Engineering Weekly

NOVEMBER 24, 2024

The blog highlights how moving from 6-character base-64 to 20-digit base-2 file distribution brings more distribution in S3 and reduces request failures. link] Jon Osborn: Best Practices for Using QUERY_TAG in Snowflake The modern data warehouses are good at running at scale, given the cost is not a constraint.

Data Engineering 57

Data Engineering Data Engineer Engineering Insurance 57

phData: Data Engineering

NOVEMBER 1, 2024

In an effort to better understand where data governance is heading, we spoke with top executives from IT, healthcare, and finance to hear their thoughts on the biggest trends, key challenges, and what insights they would recommend. Get the Trendbook What is the Impact of Data Governance on GenAI?

Government 52

Government Data Governance Finance Metadata 52

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

BI 85

BI Metadata Data Lake Business Intelligence 85

Cloudera

JUNE 7, 2023

Agencies should inventory, categorize, and label data; protect data at rest and in transit; and deploy mechanisms to detect and stop data exfiltration. Agencies should carefully craft and review data governance policies to ensure all data lifecycle security aspects are appropriately enforced across the enterprise.”

Government 84

Government Metadata Data Lake Data 84

Cloudera

MARCH 23, 2022

The table information (such as schema, partition) is stored as part of the metadata (manifest) file separately, making it easier for applications to quickly integrate with the tables and the storage formats of their choice. Enterprise grade security and data governance – centralized data authorization to lineage and auditing.

Metadata 92

Metadata Data Architecture BI Machine Learning 92

Snowflake

APRIL 29, 2024

Additionally, data can be classified and tagged based on its level of sensitivity, confidentiality or importance to the organization. This prioritizes security measures and simplifies data discovery. Data Governance: Snowflake also offers a comprehensive list of data governance features.

Transportation 87

Transportation Data Governance Government Consulting 87

Databand.ai

JULY 19, 2023

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? It provides context for data, making it easier to understand and manage.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Confluent

AUGUST 27, 2019

Confluent Schema Registry provides a serving layer for your metadata and a RESTful interface for storing and retrieving Avro schemas. Confluent Cloud Schema Registry in GA comes with production-level support and SLA to ensure that enterprises run mission-critical applications with proper data governance.

Cloud 18

Cloud Kafka Electronics Metadata 18

Cloudera

JANUARY 21, 2022

This blog will summarise the security architecture of a CDP Private Cloud Base cluster. The architecture reflects the four pillars of security engineering best practice, Perimeter, Data, Access and Visibility. Auditing has been setup for data in the metastore. System metadata is reviewed and updated regularly.

Architecture 113

Architecture Transportation Certification Government 113

Towards Data Science

MAY 19, 2023

Tech Target , defines a data silo as a repository of data controlled by one department or business unit and, therefore, not wholly or easily accessible by other departments within the same organisation. Absence or poor adoption of company-wide guidelines surrounding the creation and deployment of data products.

Pipeline-centric 104

Pipeline-centric Data Software Engineer Software Engineering 104

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 86

Data Architecture Architecture Management Banking 86

Data Engineering Weekly

AUGUST 25, 2024

[link] FourSquare: Modern Data Platform: An Unbundling of a Traditional Data Warehouse When building their data platform, companies face a critical decision: adopt an all-in-one solution from vendors like Databricks, Snowflake, or AWS or compose a custom platform using tools from different providers.

Data Engineering 70

Data Engineering Data Engineer Engineering Database-centric 70

AltexSoft

FEBRUARY 11, 2023

If you are not familiar with the above-mentioned concepts, we suggest you to follow the links above to learn more about each of them in our blog posts. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Databand.ai

AUGUST 30, 2023

Finally, you should analyze the results of your data performance tests and implement any necessary improvements to your data processing systems and infrastructure. Metadata is data about data, such as data definitions, data lineage, and data quality rules, that helps organizations understand and manage their data more effectively.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 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

phData: Data Engineering

DECEMBER 16, 2021

Welcome to part two of our trilogy on data catalogs. If you missed our first blog on what a data catalog is , be sure to check it out! In this blog, we’ll explore what the ideal team to support your data catalog looks like. Who Are the Users of a Data Catalog?

Metadata 52

Metadata Datasets Data Education 52

Snowflake

JUNE 4, 2024

New AI governance advancements help organizations better understand, share and secure models. Governed internal collaboration with better discoverability and AI-powered object metadata Snowflake is introducing an entirely new way for data teams to easily discover, curate and share data, apps and now also models (private preview soon).

Government 85

Government Data Ingestion Data PostgreSQL 85

Data Engineering Weekly

OCTOBER 6, 2024

link] Medium: Learnings from optimising 22 of our most expensive Snowflake pipelines A blog about real-world learning is always a delight to read. Though the blog talks about Superset, every team should strive to adopt a similar framework to manage the lifecycle of their dashboards. “text-to-SQL” and “text-to-insight.”

Data Engineering 62

Data Engineering Data Engineer Engineering Data Warehouse 62

Data Science Blog: Data Engineering

MAY 20, 2024

Modelling Approaches : It supports top-down modelling, bottom-up modelling, import from external modelling tool, Dimensional/Kimball, Data Vault 2.0, and Kimball, Inmon, 3NF, or any custom data model. Versioning: AnalyticsCreator maintains a version of history of metadata changes. Mixed approach of DV 2.0

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Cloudera

FEBRUARY 16, 2022

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Figure 03: lineage.yaml.

Machine Learning 86

Machine Learning Algorithm Government Metadata 86

Databand.ai

AUGUST 30, 2023

Poor data quality: The lack of automation and data governance in legacy architectures can lead to data quality issues, such as incomplete, inaccurate, or duplicate data. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Lyft Engineering

OCTOBER 3, 2023

We can also evaluate timeliness of partitions and table landing times in data orchestration. Finally, as the subject of this blog post, we can assess data quality via batch compute analytics on our data warehouse, providing a comprehensive albeit slower evaluation compared to the previously mentioned methods.

Big Data 86

Big Data Metadata Data Warehouse Data 86

Ascend.io

DECEMBER 4, 2024

Automation, AI, DataOps, and strategic alignment are no longer optional —they are essential components of a successful data strategy. As we look towards 2025, it’s clear that data teams must evolve to meet the demands of evolving technology and opportunities.

Data Pipeline 52

Data Pipeline Metadata Data Workflow Data 52

phData: Data Engineering

SEPTEMBER 19, 2023

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Cloudera

NOVEMBER 12, 2020

Inability to maintain context – This is the worst of them all because every time a data set or workload is re-used, you must recreate its context including security, metadata, and governance. Alternatively, you can also spin up a different compute cluster and access the data by using CDP’s Shared Data Experience.

Cloud 104

Cloud Data Warehouse Banking Data 104

Snowflake

MARCH 30, 2023

Data Vault as a practice does not stipulate how you transform your data, only that you follow the same standards to populate business vault link and satellite tables as you would to populate raw vault link and satellite tables. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 86

Engineering Raw Data Data Science Machine Learning 86

Cloudera

FEBRUARY 11, 2019

The root cause is firmly entrenched in legacy systems and traditional data governance challenges that not only result in data silos but also the misguided belief that data privacy is diametrically opposed to effective exploration of information. Get in touch now to learn how we can help you achieve yours.

Government 58

Government Data Governance Data Science Machine Learning 58