The Modern Data Company

MARCH 1, 2024

Each Data Product is designed for a specific purpose, equipped with the necessary data, transformations, and metadata. Data Products simplify access and processing, empowering faster decision-making. Beyond the Analogy: A Closer Look at Data Products Think of a Data Product as a Lego brick.

Database-centric 40

Database-centric Data Lake Government Retail 40

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

Monte Carlo

MAY 25, 2023

That’s why we’re excited to announce that uniting diverse data team personas to collectively ensure data quality just got easier, thanks to a new integration between Monte Carlo’s data observability platform and Atlan’s active metadata platform.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

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

The Modern Data Company

JANUARY 17, 2023

Companies Can Finally End Marketing Silos CDPs tend to be siloed in marketing departments — data comes through marketing channels, and there is very little connection with the company’s larger data ecosystem. CDP data remains cut off from data in other departments that could enrich the customer picture.

Metadata 59

Metadata Government Data Lake Data 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. 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

Data Engineering Weekly

JULY 23, 2023

Find the right, trusted data by simply asking a question. Atlan AI leverages metadata that Atlan captures across the data stack to make AI part of your data stack. And you won’t have to ask 3 different people in your team just to find the right, trusted data — you just need your AI copilot.

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 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

Silectis

DECEMBER 15, 2020

Integrated Security & Governance Features Ensuring that your data is protected and secure is one of our top priorities. The time to identify more insights out of huge sets of data. Request your demo below and we’ll be in touch to get you set up. Learn more about the technology behind Magpie here.

Data Engineering 52

Data Engineering Data Engineer Engineering ETL Tools 52

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

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. Overwhelmed data engineers need to have the proper context of the blast radius to understand which incidents need to be addressed right away, and which incidents are a secondary priority.

Data Warehouse 52

Data Warehouse BI Data Government 52

Monte Carlo

JULY 10, 2023

Accuracy reflects the degree to which the data correctly describes the “real-world” objects being described. For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. According to the CRM’s data set, the streaming provider has 13 million subscribers.

Data Collection 40

Data Collection Data Governance Government Data 40

AltexSoft

MARCH 30, 2023

Besides that, it’s fully compatible with various data ingestion and ETL tools. Unity catalog serves as a centralized metadata management and data governance layer for all Databricks data assets, including tables, files, dashboards, and machine learning models.

Scala 64

Scala Data Lake BI Google Cloud 64

AltexSoft

OCTOBER 8, 2021

At the same time, you get rid of the “data silos” problem: When no team or department has a unified view of all data due to fragments being locked in separate databases with limited access. Instead, companies can opt for automated data integration tools and platforms that often present no-code or low-code environments.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52