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 86

Government Data Security Banking Metadata 86

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

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 94

Data Governance Government Metadata Datasets 94

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 87

Big Data Bytes Data Governance Raw Data 87

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.

Architecture 130

Architecture Technology Google Cloud Metadata 130

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

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 123

Architecture Metadata Government Kafka 123

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

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 99

Cloud Government Healthcare Metadata 99

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

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

Snowflake

JANUARY 22, 2024

Fidelity has two main enterprise data architecture guiding principles for its data scientists and data engineers: For data storage, Snowflake is the platform for storing all of the company’s structured and semi-structured analytical data in its Enterprise Data Lake and Data Labs.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

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 Pipeline 40

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

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 107

Manufacturing Retail Government Entertainment 107

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

Precisely

DECEMBER 8, 2023

As you strive to achieve higher levels of data integrity, data governance becomes imperative. What is Data Governance? Robert Seiner, author of Non-Invasive Data Governance and founder of KIK Consulting, defines data governance as “the execution and enforcement of authority over data.”

Data Governance 69

Data Governance Government Datasets Programming 69

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

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

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

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 107

Architecture Transportation Certification Government 107

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

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 66

Food Healthcare Government Medical 66

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 57

Government Data Governance Data Science Machine Learning 57

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 75

Hadoop SQL Database Kafka 75

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

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

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. Data lineage helps ensure you have clear lines of accountability that data team structure–centralized, center of excellence , data mesh– you use or however your data pipelines evolve.

Data Warehouse 52

Data Warehouse BI Government Data 52

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

AltexSoft

MARCH 30, 2023

Source: The Data Team’s Guide to the Databricks Lakehouse Platform Integrating with Apache Spark and other analytics engines, Delta Lake supports both batch and stream data processing. Besides that, it’s fully compatible with various data ingestion and ETL tools. Databricks two-plane infrastructure.

Scala 64

Scala Data Lake BI Google Cloud 64

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

ProjectPro

MAY 1, 2018

Hortonworks announced the launch of a data governance plug-in named Studio for its DataPlane platform at the recent Hadoop Summit.DataPlane platform that was announced last year provides data architecture as a service with data governance baked in Apache Atlas.Scott Gnau, chief technology officer at Hortonworks said that the supplier is at stage 3.0

Hadoop 40

Hadoop Banking Healthcare Food 40

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