Cloudera

JUNE 6, 2019

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants.

Metadata 85

Metadata Data Lake Optimization Strategy 85

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. You might have millions of short videos , with user ratings and limited metadata about the creators or content. If you can’t walk, you’re unlikely to run.

Management 339

Management Machine Learning Experimentation Metrics 339

AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run. You’re now ready to query the tables using Athena.

Analytics 102

Analytics IoT Metadata Internet of Things 102

Ontotext

MAY 18, 2020

Moreover, text is also used in scientific papers and blog posts that describe specific images, thus making healthcare-related data potentially the biggest annotated data collection worldwide. There are four types of data sources that the team will work with. The first type is metadata from images. Certainly not!

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance.

Data Warehouse 92

Data Warehouse Data Lake IT Analytics 92

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. There are two types of data warehouses: on-premises and cloud-based.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. Where these efforts break down is in the data that goes into the connection at one end and comes out the other. So, I hear you say, let’s share metadata and make the data self-describing.

Analytics 64

Analytics Measurement Data-driven Modeling 64

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Cloudera

NOVEMBER 22, 2021

Explosion of data availability from a variety of sources, including on-premises data stores used by enterprise data warehousing / data lake platforms, data on cloud object stores typically produced by heterogenous, cloud-only processing technologies, or data produced by SaaS applications that have now evolved into distinct platform ecosystems (e.g.,

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. So, establishing a framework to store data by its source is a great place to start. Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Andrew White

MARCH 31, 2023

A workshop that helps diagnostically map specific data to specific business outcomes. I hosted 25 1-1s in between the meetings and presentations. Data mesh versus data fabric I am not the expert here but in lay terms, I believe both fabric and mesh include a semantic inference engine that consumes active metadata.

Analytics 40

Analytics Marketing Visualization Data-driven 40

Jet Global

MAY 1, 2023

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.” addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52