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.

Metadata 105

Metadata Government Data Governance Data 105

Precisely

APRIL 11, 2023

What existing data does the organization have to support my initiative? Where does that data live? Do I have access to the data? What do I need to do to access the data now and make it easy to find and access in the future? How can I ensure the data is up-to-date and issue-free moving forward?

Accessible 52

Accessible Accessibility Metadata Data Integration 52

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? How do we govern all these data products and domains ? In this stage, you will never think about the configuration.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Cloudera

AUGUST 10, 2021

With the release of CDP Private Cloud (PvC) Base 7.1.7, We understand that migrating your data platform to the latest version can be an intricate task, and at Cloudera we’ve worked hard to simplify this process for all our customers. . Impala Row Filtering to set access policies for rows when reading from a table.

Cloud 96

Cloud Kafka Metadata SQL 96

Cloudera

AUGUST 26, 2021

The object store is readily available alongside HDFS in CDP (Cloudera Data Platform) Private Cloud Base 7.1.3+. In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. Data ingestion through ‘s3’.

Data Science 109

Data Science Cloud Hadoop Metadata 109

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. How can Snowflake Help?

Transportation 83

Transportation Data Governance Government Consulting 83

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. A solution.

Cloud 102

Cloud Data Warehouse Banking Data 102

Precisely

MAY 31, 2023

When attempting to build a data strategy, the primary obstacle organizations face is a lack of resources. Teams are building complex, hybrid, multi-cloud environments, moving critical data workloads to the cloud, and addressing data quality challenges.

Data Integration 52

Data Integration Metadata Data Governance 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

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

Cloudera

JUNE 7, 2023

By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). The data is protected but it is also accessible by the people who need it.

Government 79

Government Metadata Data Lake Data 79

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 108

Manufacturing Retail Entertainment Government 108

dbt Developer Hub

JULY 2, 2023

Due to its complexity, Data Vault is not a go-to choice for: Simple and constant systems; Quick one-off solutions for experiments or short-term data warehouse projects; Data warehouse layers needed for direct reporting. Auditable data ​ One of the main selling points of Data Vault is its auditability.

Cloud 52

Cloud Data Warehouse Data BI 52

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 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

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

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. It works in both directions.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Data Engineering Podcast

NOVEMBER 9, 2020

In this episode Grant Seward explains how he built Tree Schema to be an easy to use and cost effective option for organizations to build their data catalogs. 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.

Building 100

Building PostgreSQL BI Metadata 100

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

Monte Carlo

SEPTEMBER 12, 2022

Now, according to Maxime, a new trend is emerging that could have a similar effect on data engineering workloads: reverse ETL. Reverse ETL tooling enables companies to easily move transformed data from their cloud warehouse out into operational business tools, like a CRM.

BI 52

BI Data Governance ETL Tools Data Warehouse 52

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Figure 03: lineage.yaml.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Cloudera

SEPTEMBER 15, 2022

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.” Ramsey International Modern Data Platform Architecture.

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Cloudera

MAY 12, 2021

HYBRID & MULTI-CLOUD INNOVATION. If you are working in an organization that is driving business innovation by unlocking value from data in multiple environments — in the private cloud or across hybrid and multiple public clouds — we encourage you to consider entering this category. SECURITY AND GOVERNANCE LEADERSHIP.

Food 66

Food Healthcare Government Medical 66

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

Monte Carlo

MARCH 16, 2023

The early days of the data mesh journey Long before Best Egg established their data mesh, data was siloed and owned by disparate teams managing their own data stores across tools like Excel and SQL servers. We as the central data team said, ‘Hey, we want to inherit all of these siloed data marts’,” Randy said.

Software Engineer 52

Software Engineer Software Engineering Data Governance Government 52

Monte Carlo

SEPTEMBER 20, 2022

“The way that our data flows across our stack is pretty integral to the way the company runs,” said Dylan. “We We take the data from our warehouse, and we actually push it back into our operational tooling for use by the individual teams. Scaling data governance. This left Dylan’s team with a gap to fill.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Precisely

DECEMBER 8, 2023

Together, these forces have pushed companies to accelerate the shift to technologies like Cloud, AI, and workflow automation. In the context of this change, business leaders recognize the pressing need for data-driven decision-making. As you strive to achieve higher levels of data integrity, data governance becomes imperative.

Data Governance 69

Data Governance Government Datasets Programming 69

Cloudera

AUGUST 21, 2020

One is data at rest, for example in a data lake, warehouse, or cloud storage and from there they can do analytics on this data and that is predominantly around what has already happened or around how to prevent something from happening in the future.

Banking 60

Banking Kafka Cloud Storage Government 60

Monte Carlo

MARCH 16, 2023

The early days of the data mesh journey Long before Best Egg established their data mesh, data was siloed and owned by disparate teams managing their own data stores across tools like Excel and SQL servers. We as the central data team said, ‘Hey, we want to inherit all of these siloed data marts’,” Randy said.

Software Engineer 40

Software Engineer Software Engineering Data Governance Government 40

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy. But it’s still not easy.

Data Governance 83

Data Governance Government Metadata Data Security 83

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. Projections show that the data governance market will expand from $1.81

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

Cloudera

MAY 2, 2022

from China to the UK , new data governance and protection rules are coming in on an almost daily basis. There are many reasons to deploy a hybrid cloud architecture — not least cost, performance, reliability, security, and control of infrastructure.

Cloud 99

Cloud Government Healthcare Metadata 99

Precisely

JANUARY 25, 2024

But today’s cloud platforms offer similar capabilities, with the added benefits of flexibility, elasticity, and virtually unlimited scalability. The cloud helps companies lower their capital expenditures, enhance operational efficiency, and innovate faster. They’re also valued for their rock-solid reliability, boasting 99.999% uptime.

Metadata 69

Metadata Data Governance Relational Database Government 69

Snowflake

NOVEMBER 29, 2023

Data cloud technology can accelerate FAIRification of the world’s biomedical patient data. To summarize the importance of multiomics data analytics, the need of the hour is data governance around integrated data analysis that assures appropriate access, lineage tracking and auditability of analysis results.

Metadata 83

Metadata Healthcare Medical Data Storage 83