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

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 104

Metadata Government Data Governance Data 104

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. What data do we have ?

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

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.

Transportation 82

Transportation Data Governance Government Consulting 82

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

Monte Carlo

MAY 18, 2023

Whether you’re a data scientist, data engineer, or business analyst, keeping track of your data’s origin, transformation, and movement is crucial for maintaining transparency, enforcing data governance, and ensuring data quality. You may even already have access to one of them.

Metadata 64

Metadata Data Lake Government Data Governance 64

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 78

Government Metadata Data Lake Data 78

Precisely

MAY 31, 2023

With the right enterprise-grade technology, organizations can find simple solutions to complex data integrity challenges at scale. The act of bringing data into hybrid cloud and VPC environments doesn’t solve data integrity challenges by itself. The end result is that users can’t trust their data because it lacks integrity.

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

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

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

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Cloudera

AUGUST 10, 2021

SDX enhancements for improved platform and data governance, including the following notable features: . Impala Row Filtering to set access policies for rows when reading from a table. Figure 1: sales group SELECT access. This helps simplify Impala queries and provides row-level security for each table. x, and 6.3.x,

Cloud 96

Cloud Kafka Metadata SQL 96

The Modern Data Company

APRIL 15, 2024

Understands how different pieces of data (books) relate to each other, helping users find related information. Keeps the library orderly, adjusting as new data arrives. Tracks key performance indicators to understand the use and value of the data. Manages information about data access and monitors data quality.

Government 52

Government Metadata Data Data Lake 52

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

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. . Keep data lineage secure and governed.

Manufacturing 107

Manufacturing Retail Entertainment Government 107

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 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

Cloudera

AUGUST 26, 2021

This means that there is out of the box support for Ozone storage in services like Apache Hive , Apache Impala, Apache Spark, and Apache Nifi, as well as in Private Cloud experiences like Cloudera Machine Learning (CML) and Data Warehousing Experience (DWX). Data ingestion through ‘s3’. Spark SQL to access Hive table.

Data Science 107

Data Science Cloud Hadoop Metadata 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

Silectis

FEBRUARY 3, 2021

By understanding the producer/consumer relationship of all the data within a data lake, data quality issues that arise can quickly be identified and traced back to their source. Let’s consider a common scenario: a given dataset is consumed by several downstream pipelines and a data quality issue is discovered.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 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

Monte Carlo

SEPTEMBER 12, 2022

Reverse ETL tooling enables companies to easily move transformed data from their cloud warehouse out into operational business tools, like a CRM. This new approach empowers business users to access and act on their data, while reinforcing the data warehouse as the source of truth.

BI 52

BI Data Governance ETL Tools Data Warehouse 52

LinkedIn Engineering

JUNE 2, 2023

Availability: Data must be readily available to the broader team in order to support their research and analysis. This data must be accessible and available in near real-time in order to accurately reflect current trends and conditions. The team operates with the following guiding principles as our collective north star: 1.

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

DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. For example: Complete toolchain.

Data Governance 59

Data Governance Government Metadata Data Science 59

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.

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

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

Cloudera

FEBRUARY 16, 2022

Within the CML data service, model lineage is managed and tracked at a project level by the SDX. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets. Figure 03: lineage.yaml.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Silectis

DECEMBER 15, 2020

Integrated Security & Governance Features Ensuring that your data is protected and secure is one of our top priorities. Learn more about the technology behind Magpie here.

Data Engineering 52

Data Engineering Data Engineer Engineering ETL Tools 52

Monte Carlo

JULY 11, 2023

Even if the data is accurate, if it does not address the specific questions or requirements of the task, it may be of limited value or even irrelevant. Contextual understanding: Data quality is also influenced by the availability of relevant contextual information. is the gas station actually where the map says it is?).

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Monte Carlo

MARCH 16, 2023

Today, Best Egg’s data stack is built primarily on AWS and leverages tools like Kafka, Sagemaker, dbt, and Terraform. Randy’s team also uses custom code to ingest specific types of third-party data, like their bank processor’s EBCDICfiles. The analytics users across the company access most data through Snowflake and PowerBI.

Software Engineer 52

Software Engineer Software Engineering Data Governance Government 52

Monte Carlo

SEPTEMBER 20, 2022

Plus Monte Carlo’s API and Python SDK allow for simple extensibility by enabling programmatic access or embedding data observability functions into existing processes and workflows. These data monitors combine to track data accuracy, data completeness and general adherence to internal business rules.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

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 82

Data Governance Government Metadata Data Security 82