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. Data As Code is a very strong choice : we do not want any UI because it is an heritage of the ETL period. It gives an anwser to what do we have , where is the data (its address) how many objects do we have ?

Architecture 130

Architecture Technology Google Cloud Metadata 130

François Nguyen

JANUARY 18, 2021

In every step,we do not just read, transform and write data, we are also doing that with the metadata. Last part, it was added the data security and privacy part. Every data governance policy about this topic must be read by a code to act in your data platform (access management, masking, etc.)

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

Data Engineering Podcast

MARCH 27, 2022

How would you characterize your position in the market for data governance/data security tools? What are the unique constraints and challenges that come into play when managing data in cloud platforms? Acryl]([link] The modern data stack needs a reimagined metadata management platform.

Data Governance 130

Data Governance Government Cloud Building 130

Ascend.io

FEBRUARY 28, 2024

Metadata Management for Enhanced Machine Interpretation Data engineering extends its importance to the realm of metadata management, providing AI models with essential context about data definitions, classifications, and governance policies.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Cloudera

MARCH 3, 2022

Data users in these enterprises don’t know how data is derived and lack confidence in whether it’s the right source to use. . If data access policies and lineage aren’t consistent across an organization’s private cloud and public clouds, gaps will exist in audit logs. From Bad to Worse.

Data Governance 95

Data Governance Government Metadata Medical 95

Cloudyard

OCTOBER 10, 2023

As we know data sharing allows organizations to securely share data with other Snowflake accounts without the need to copy the data. Data provider shares specific data securely, and data consumer queries this shared data in real-time, empowering data-driven decision-making.

Metadata 52

Metadata Database Data Security Systems 52

Christophe Blefari

JUNE 16, 2023

Masthead does not run SQL on your data—which generate costs uplift—but reading logs and metadata to identify anomalies. Privitar will bring "data security" stuff. Informatica acquires Privitar. This consolidation will bring new features to Informatica. See you next week ❤️

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Cloudyard

DECEMBER 7, 2023

The Listings feature enhances the capabilities of Secure Data Sharing with the following functionalities: Share Snowflake Native App Publish listings on the Snowflake Marketplace Automatically replicate your data to other regions Provide metadata about the share, including a title, description, and sample SQL queries While sharing data securely within (..)

Metadata 52

Metadata SQL Data Cloud 52

AltexSoft

FEBRUARY 11, 2023

If KPI goals are not met, a data architect recommends solutions (including new technologies) to improve the existing framework. Besides, it’s up to this specialist to guarantee compliance with laws, regulations, and standards related to data.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Data Engineering Podcast

FEBRUARY 13, 2022

You can observe your pipelines with built in metadata search and column level lineage. What are some of the data privacy primitives that you include to assist with data security/regulatory concerns? What is the process of getting started with Rudderstack as a software or data platform engineer?

Building 100

Building Hadoop Data Pipeline Metadata 100

Data Engineering Podcast

FEBRUARY 6, 2022

You can observe your pipelines with built in metadata search and column level lineage. What are some of the best practices in the definition, protection, and enforcement of data privacy policies? Is there a data security/privacy equivalent to the OWASP top 10? Which categor(y|ies) are you focused on addressing?

Data Pipeline 100

Data Pipeline Data Metadata Software Engineer 100

Knowledge Hut

APRIL 20, 2023

The following are some of the key reasons why data governance is important: Ensuring data accuracy and consistency: Data governance helps to ensure that data is accurate, consistent, and trustworthy. This helps organisations make informed decisions based on reliable data.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.

Data Governance 93

Data Governance Government Metadata Datasets 93

Cloudera

AUGUST 3, 2021

An organization, its partner, and customers, all benefit from enterprise-wide multi-function analytics only if data is protected, secured, and governed throughout. If data access policies and lineage aren’t consistent across an organization’s private cloud and public clouds, gaps will exist in audit logs.

Manufacturing 107

Manufacturing Retail Entertainment Government 107

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

Monte Carlo

MARCH 3, 2021

When it comes to managing your company’s data, security is high on your list of priorities. Today, I’m thrilled to share that Monte Carlo has achieved SOC 2 Type I certification , an industry-leading standard for the security, availability, and confidentiality that our organization adopted. What does this mean for you?

Metadata 52

Metadata Data Lake Business Intelligence Certification 52

Precisely

JULY 31, 2023

Echoing the pervasive theme of low data quality that emerged across the survey results, we see data quality playing a leading role in all three areas of inquiry Zeroing in on data quality and data integration The top-ranking priority for improving data integrity in 2023 is data quality at 53%, followed closely by data integration at 50%.

Data Integration 52

Data Integration Telecommunication Data Governance Government 52

LinkedIn Engineering

JUNE 2, 2023

LinkedIn’s members rely on the platform to keep their data secure, and it is essential that the EGRI team takes appropriate measures to ensure that member privacy is protected at all times. DataHub also provides us with a user-friendly interface to monitor metadata and the overall health of our dataset.

Building 75

Building Banking Datasets Media 75

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

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

JULY 24, 2023

In addition to data entered by users, database systems typically store large amounts of data. The system stores metadata about data which makes it easier to find and retrieve data. In a DBMS, once a set of metadata is stored in the database, it is difficult to change or update the metadata.

Database Design 52

Database Design Relational Database Metadata Database 52

Databand.ai

AUGUST 30, 2023

In a DataOps architecture, it’s crucial to have an efficient and scalable data ingestion process that can handle data from diverse sources and formats. 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

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., ….

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

Knowledge Hut

SEPTEMBER 29, 2023

Design and develop data processing (25–30%): This component is concerned with ingesting and developing reliable data processing solutions. Design and implementation of data security (10–15%): In this phase, a data security protocol is designed and put into action.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

APRIL 26, 2021

CDP is using Apache Ranger for data security management. If you wish to utilize Ranger to have a centralized security administration, HBase ACLs need to be migrated to policies. Table – Permissions granted at table scope apply to data or metadata within a given table. HBase Authorization.

Finance 94

Finance Metadata Accessible Accessibility 94

Cloudera

NOVEMBER 10, 2021

Sentry depended on Hue for visual policy management, and Cloudera Navigator for auditing data access in the CDH platform. . On the other hand, Apache Ranger provides a comprehensive security framework to enable, manage and monitor data security across the Hadoop platform.

Hadoop 74

Hadoop SQL Database Kafka 74

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. SECURITY AND GOVERNANCE LEADERSHIP. Data for Enterprise AI: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning.

Food 65

Food Healthcare Government Medical 65

Cloudera

DECEMBER 20, 2021

Judges were looking at how organizations tackled modeling & reduced business risk, prevented fraud, met regulatory compliance, established fully governed data marketplaces, and more. . This year, after careful consideration, two organizations stood out as leaders in data security and governance policies: Bank of the West and Telkomsel. .

Government 85

Government Data Security Banking Metadata 85

Netflix Tech

MARCH 5, 2019

Asset Inventory How can we develop a dimensional data model representing relationships between apps, clusters, regions and other metadata including AMI / software stack to help with availability, resiliency and fleet management? Can we develop learning models to enrich metadata with application vulnerabilities and risk scores?

Cloud 73

Cloud Building Amazon Web Services Metadata 73

Cloudera

NOVEMBER 12, 2020

Typically, when we talk about data warehousing at an enterprise level on the cloud, one of the biggest concerns is that moving workloads from on-premises to the cloud is not seamless and opens up new risks for data safety and security. How Burst to Cloud can solve your data center pressure. Key areas of concern are: .

Cloud 101

Cloud Data Warehouse Banking Data 101

Knowledge Hut

DECEMBER 21, 2023

Blockchain data-based cloud data integrity protection mechanism The "Blockchain data-based cloud data integrity protection mechanism" paper suggests a method for safeguarding the integrity of cloud data and which is one of the Cloud computing research topics.

Cloud Computing 52

Cloud Computing Cloud Algorithm Healthcare 52

Cloudera

AUGUST 21, 2020

Security needs to be treated at a mission-critical level and data security also needs to be a core part of a business’s strategic approach. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Banking 59

Banking Kafka Cloud Storage Government 59

Cloudera

APRIL 23, 2021

However, any user with HDFS admin or root access on cluster nodes would be able to impersonate the “hdfs” user and access sensitive data in clear text. HDFS Encryption prevents access to clear text data. Data in the file is encrypted with DEK. DEK is encrypted using EZK to give rise to encrypted data encryption key (EDEK).

MySQL 68

MySQL Java Bytes Data 68

Rockset

MARCH 18, 2024

There are several challenges that emerge when building real-time RAG pipelines: Real-time delivery of embeddings & updates Real-time metadata filtering Scale and efficiency for real-time data In the following sections, we’ll discuss these challenges broadly and delve into how they apply more specifically to vector search and vector databases.

Cloud 64

Cloud Building Metadata Kafka 64

Cloudera

MAY 2, 2022

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. . Designing an enterprise data architecture in anticipation of such regulatory changes is challenging.

Cloud 97

Cloud Government Healthcare Metadata 97

Cloudera

AUGUST 4, 2021

With hackers now working overtime to expose business data or implant ransomware processes, data security is largely IT managers’ top priority. And if data security tops IT concerns, data governance should be their second priority. Availability: Make the right data available only to the right users.

Data Governance 82

Data Governance Government Metadata Data Security 82