Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

Data Governance 98

Data Governance Government Metadata Medical 98

Knowledge Hut

APRIL 20, 2023

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

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. Effective data governance must extend beyond the IT organization.

Data Governance 84

Data Governance Government Metadata Data Security 84

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. . The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Government 89

Government Data Security Banking Metadata 89

Data Engineering Podcast

JUNE 5, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking all of that information into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. Go to dataengineeringpodcast.com/atlan today to learn more about how you can take advantage of active metadata and escape the chaos.

Data Security 100

Data Security Metadata MongoDB Scala 100

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 Programming Healthcare 52

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 95

Data Governance Government Metadata Datasets 95

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

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

François Nguyen

JANUARY 18, 2021

To finish the trilogy (Dataops, MLops), let’s talk about DataGovOps or how you can support your Data Governance initiative. 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.

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

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 ? Data As Code is a very strong choice : we do not want any UI because it is an heritage of the ETL period.

Technology 130

Technology Architecture Google Cloud Metadata 130

Precisely

MAY 13, 2024

Integrated data catalog for metadata support As you build out your IT ecosystem, it’s important to leverage tools that have the capabilities to support forward-looking use cases. A notable capability that achieves this is the data catalog. If so, how do you combine that metadata with other data across the enterprise? #4.

Data Integration 52

Data Integration Metadata Amazon Web Services 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. 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 101

Cloud Government Healthcare Metadata 101

Christophe Blefari

JUNE 16, 2023

The power of pre-commit and SQLFluff —SQL is a query programming language used to retrieve information from data storages, and like any other programming language, you need to enforce checks at all times. Privitar will bring "data security" stuff. This is where you should use pre-commit and SQLFluff.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

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

Precisely

JULY 31, 2023

In the context of improving their organizations’ data integrity , respondents cite data quality and data integration as priorities for 2023 and as challenges to data integrity. Let’s explore more of the report’s findings around data integrity maturity, challenges, and priorities.

Data Integration 52

Data Integration Telecommunication Data Governance Government 52

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. Organizations need to establish data governance policies, processes, and procedures, as well as assign roles and responsibilities for data governance.

Data Governance 40

Data Governance Data Cleanse Government Data Science 40

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 Entertainment Government 111

Databand.ai

AUGUST 30, 2023

Data silos: Legacy architectures often result in data being stored and processed in siloed environments, which can limit collaboration and hinder the ability to generate comprehensive insights. 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

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. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

NOVEMBER 23, 2021

Implementing data virtualization requires fewer resources and investments compared to building a separate consolidated store. Enhanced data security and governance. All enterprise data is available through a single virtual layer for different users and a variety of use cases. ETL in most cases is unnecessary.

Process 69

Process Data Lake Metadata Data Warehouse 69

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

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. Accordance: State-of-the-art data infrastructure technologies and tooling are not sufficient to fully realize our vision.

Building 75

Building Banking Datasets Media 75

Cloudera

JANUARY 21, 2022

Auditing has been setup for data in the metastore. System metadata is reviewed and updated regularly. Ideally, the cluster has been setup so that lineage for any data object can be traced (data governance). Apache Ranger is a framework to enable, monitor and manage comprehensive data security across the platform.

Architecture 109

Architecture Transportation Certification Government 109

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. Industry Transformation: Telkomsel — Ingesting 25TB of data daily to provide advanced customer analytics in real-time .

Food 69

Food Healthcare Government Medical 69

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

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.

Government 56

Government Data Governance Data Science Machine Learning 56

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 76

Hadoop SQL Database Kafka 76

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 62

Banking Kafka Cloud Storage Government 62

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 103

Cloud Data Warehouse Banking Data 103

ProjectPro

NOVEMBER 15, 2021

It offers a fault-tolerant storage engine that prioritizes data security. On top of existing data lakes like S3, ADLS, GCS, and HDFS, Delta Lake enables ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. To contribute to this project, hop onto: [link] 19.DataHub

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 31, 2022

Several organizations can quickly transform, integrate, and analyze their data with Snowflake's Data Cloud. They can also design and run data apps and securely share, gather, and commercialize real-time data. This layer stores the metadata needed to optimize a query or filter data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MAY 12, 2023

Unstructured data storage solutions must ensure data durability (protection against data loss) and availability (ensuring data is accessible when needed). That’s why there must be some sort of data replication, backup strategies, and failover mechanisms. Data security and privacy.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

Architecture 122

Architecture Metadata Kafka Government 122

Monte Carlo

MARCH 13, 2024

Let’s dig in and explore the landscape of the top so-called “data quality tools” — what they are, what they’re not, and whether they’re the right first step towards more reliable data. Governance helps companies set important standards and achieve higher levels of data security, data accessibility, and data quality.

Data Governance 52

Data Governance Government Metadata Data 52

phData: Data Engineering

JULY 18, 2023

Key Benefits and Features of Using Snowflake Data Sharing: Easily share data securely within your organization or externally with your customers and partners. Zero Copy Cloning: Create multiple ‘copies’ of tables, schemas, or databases without actually copying the data.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52