Octopai

JANUARY 21, 2020

How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. It’s a snapshot of data at a specific point in time, at the end of a day, week, month or year. – Business changes. Cube to the rescue.

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

Cloudera

OCTOBER 11, 2022

Risk increases. As Julian and Bret say above, a scaled AI solution needs to be fed new data as a pipeline, not just a snapshot of data and we have to figure out a way to get the right data collected and implemented in a way that is not so onerous. Let this sink in a while – AI at scale isn’t magic, it’s data. Innovation stalls.

Snapshot 92

Snapshot Data Science Digital Transformation Metadata 92

AWS Big Data

MAY 10, 2023

However, it’s also possible for multiple shard copies across both active zones to be unavailable in cases of two node failures or one zone plus one node failure (often referred to as double faults ), which poses a risk to availability. No one size fits all workloads, therefore we use Auto-Tune to control them more granularly.

Snapshot 96

Snapshot Testing Metadata Management 96

Alation

AUGUST 26, 2021

It includes intelligence about data, or metadata. The earliest DI use cases leveraged metadata — EG, popularity rankings reflecting the most used data — to surface assets most useful to others. Privacy, Risk and Compliance. Again, metadata is key. Data Intelligence and Metadata. Cloud Transformation.

Metadata 64

Metadata Data Governance Dashboards Software 64

AWS Big Data

APRIL 3, 2024

As data is refreshed and updated, changes can happen through upstream processes that put it at risk of not maintaining the intended quality. By selecting the corresponding asset, you can understand its content through the readme, glossary terms , and technical and business metadata.

Data Quality 91

Data Quality Visualization Metadata Metrics 91

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There are tools to replicate and snapshot data, plus tools to scale and improve performance.” I am not interested in owning that risk internally.” What Are the Biggest Business Risks to Cloud Data Migration? Yet the cloud, according to Sacolick, doesn’t come cheap. “A

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. This leads to wasted time and effort during research and collaboration or, worse, compliance risk.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Cloudera

MAY 24, 2021

Each mechanism has common aspects of work, risk mitigation, and successful outcomes expected across all paths from legacy distributions into CDP. Second, configure a replication process to provide periodic and consistent snapshots of data, metadata, and accompanying governance policies.

Metadata 81

Metadata Testing Snapshot Strategy 81

AWS Big Data

JUNE 12, 2023

With the ability to monitor and respond to real-time events, organizations are better equipped to capitalize on opportunities and mitigate risks as they arise. After the processed data is stored in Amazon S3, we create an AWS Glue crawler to create a Data Catalog table that acts as a metadata layer for the data.

Management 82

Management Metadata Testing Internet of Things 82

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. An attacker could use an adversarial example attack to grant themselves a large loan or a low insurance premium or to avoid denial of parole based on a high criminal risk score. Newer types of fair and private models (e.g.,

Modeling 219

Modeling Machine Learning Predictive Modeling Consulting 219