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Gartner Magic Quadrant for Metadata Management Includes Alation

Alation

Gartner predicts that “By 2020, 50% of information governance initiatives will be enacted with policies based on metadata alone.”. Magic Quadrant for Metadata Management Solutions , Guido de Simoni and Roxane Edjlali, August 10, 2017. Metadata management no longer refers to a static technical repository.

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10 Years Later: Who’s the GOAT of Data Catalogs?

Alation

January 2017: MercadoLibre signs on as the first LATAM customer. June 2017: Dresner Advisory Services names Alation the #1 data catalog in its inaugural Data Catalog End-User Market Study. June 2017: Yahoo Japan Corp. August 2017: Alation debuts as a leader in the Gartner MQ for Metadata Management Solutions.

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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

In 2017, we published “ How Companies Are Putting AI to Work Through Deep Learning ,” a report based on a survey we ran aiming to help leaders better understand how organizations are applying AI through deep learning. Data scientists and data engineers are in demand.

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Why Data Governance Is Crucial for All Enterprise-Level Businesses

Cloudera

In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. Data analytics and machine learning can become a business and a compliance risk if data security, governance, lineage, metadata management, and automation are not holistically applied across the entire data lifecycle and all environments.

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Bringing the National Museum of African American History and Culture to the world

CIO Business Intelligence

The startup focused on federal contracts and earned its first contract with the Secret Service in 2017. Fearless chose Gatsby, a JavaScript framework for fast web page creation, and Craft CMS, which provides a speedy yet robust reach into the museum’s sizable catalog of metadata stored in AWS S3. Today, it employs more than 200.

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AI in Analytics: The NLQ Use Case

Sisense

Once both issues are addressed, the user can ask “how many customers are responsible for 80% of my Q1 2018 income compared to 2017?” and the system will know to look after ‘ clients ’ and aggregate the ‘ revenue ’ (the actual variable names in the system) to compare between Q1 2018 and Q1 2017. Machine Intent vs. User Intent.

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5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. It allows data scientists to log, store, share, compare and search important metadata that is used to build models for data science applications. Neptune.ai. Neptune.AI