Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. You're choosing only one metric because you want to optimize it. There is a lot of deliberation in step two on ensuring that we have an optimal hypothesis to work from. But it is not routine.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

IBM Big Data Hub

OCTOBER 4, 2022

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Platforms and practices not optimized for AI. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. This is due to: An inability to access the right data.

Metadata 97

Metadata Risk Management Risk Experimentation 97

AWS Big Data

JANUARY 24, 2023

The utility for cloning and experimentation is available in the open-sourced GitHub repository. This solution only replicates metadata in the Data Catalog, not the actual underlying data. Lake Formation permissions In Lake Formation, there are two types of permissions: metadata access and data access.

Data Architecture 93

Data Architecture Metadata Data Lake Snapshot 93

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 119

Metadata Data Lake Publishing Data Governance 119

O'Reilly on Data

MARCH 23, 2023

Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. It was not optimized to provide correct responses. It has helped to write a book.

IT 348

IT Modeling Testing Risk 348

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 86

Metadata Data Lake Optimization Strategy 86

Sisense

JULY 24, 2019

When the app is first opened, the user may be searching for a specific song that was heard while passing by the neighborhood cafe, or the user may want to be surprised with, let’s say, a song from the new experimental album by a Yemen Reggae folk artist. There are many activities going on with AI today, from experimental to actual use cases.

Analytics 89

Analytics Experimentation Metadata Big Data 89

CIO Business Intelligence

DECEMBER 10, 2024

For example, our employees can use this platform to: Chat with AI models Generate texts Create images Train their own AI agents with specific skills To fully exploit the potential of AI, InnoGames also relies on an open and experimental approach. In addition to the vectors, contextual headings are added to each chunk. The KAWAII frontend.

Data-driven 98

Data-driven Metadata Interactive KPI 98

AWS Big Data

JULY 20, 2023

Determining optimal table partitioning Determining optimal partitioning for each table is very important in order to optimize query performance and minimize the impact on teams querying the tables when partitioning changes. The following diagram illustrates the solution architecture. Orca addressed this in several ways.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

CIO Business Intelligence

MARCH 21, 2022

As such, a data scientist must have enough business domain expertise to translate company or departmental goals into data-based deliverables such as prediction engines, pattern detection analysis, optimization algorithms, and the like. It doesn’t conform to a data model but does have associated metadata that can be used to group it.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

CIO Business Intelligence

MARCH 6, 2023

“Previous tasks such as changing a watermark on an image or changing metadata tagging would take months of preparation for the storage and compute we’d need. Optimizing for innovation Analytics in cloud is also proving key to Shutterstock operations. That is invaluable when optimizing your site.”

Data Lake 88

Data Lake Cost-Benefit Recreation/Entertainment Unstructured Data 88

IBM Big Data Hub

MAY 9, 2023

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. While the promise of AI isn’t guaranteed and may not come easy, adoption is no longer a choice.

Metadata 71

Metadata Risk Experimentation Dashboards 71

AWS Big Data

JUNE 12, 2024

These topics include federation with the Swisscom identity provider (IdP), JDBC connections, detective controls using AWS Config rules and remediation actions, cost optimization using the Redshift scheduler, and audit logging. This module is experimental and under active development and may have changes that aren’t backward compatible.

Data Architecture 115

Data Architecture Cost-Benefit Data-driven Experimentation 115

Ontotext

MARCH 29, 2021

Vassil Momtchev: RDF-star (formerly known as RDF*) helps in every case, where the user needs to express a complex relationship with metadata associated for a triple like: 1. << Technically speaking, RDF-star is the syntactic sugar, which makes it easier to attach metadata to edges in the graph. source :TheNationalEnquirer ; 3.

Metadata 59

Metadata IT Modeling Experimentation 59

Cloudera

FEBRUARY 16, 2022

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. Further auditing can be enabled at a session level so administrators can request key metadata about each CML process. Figure 03: lineage.yaml.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. internal metadata, industry ontologies, etc.) names, locations, brands, industry codes, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Cloudera

APRIL 9, 2019

For example, if you want to optimize for agility and experimentation, you probably will be better off doing so with an ephemeral public cloud infrastructure. An integrated suite of data management and analytics tools in a single platform enables cost-effective delivery of complex, multiple use cases and thus reduces overall TCO.

Strategy 54

Strategy Experimentation Business Objectives Metadata 54

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Just-in-Time” manufacturing increases production while optimizing resources. Comprehensive metadata that supports data product and process organization. Let’s take a look.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Cloudera

JANUARY 11, 2021

Experimental and production workloads access the same data without users impacting each others’ SLAs. Offers a hybrid model that enables you to optimize for cost and investment. You predict your needs and optimize “on-the-fly” so you can further control costs, no matter what the environment. High performance.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Machine Learning 63

IBM Big Data Hub

JANUARY 17, 2023

The automated metadata generation is essential to turn a manual process into one that is better controlled. AI is no longer experimental. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. Start a trial. Data science and MLOps.

Data-driven 56

Data-driven Enterprise Data Governance Data Science 56

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. With scalable metadata indexing, Apache Iceberg is able to deliver performant queries to a variety of engines such as Spark and Athena by reducing planning time.

Snapshot 105

Snapshot Data Lake Testing Strategy 105

AWS Big Data

JULY 26, 2023

This enables you to process a user’s query to find the closest vectors and combine them with additional metadata without relying on external data sources or additional application code to integrate the results. We recognize that many of you are in the experimentation phase and would like a more economical option for dev-test.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Ontotext

DECEMBER 30, 2022

9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. Metadata Studio – our new product for streamlining the development and operation of solutions involving text analysis. The first 18 years: Develop vision and products and deliver to innovation leaders.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 364

Marketing Experimentation Metrics Testing 364

CIO Business Intelligence

FEBRUARY 14, 2024

Introduce gen AI capabilities without thinking about data hygiene, he warns, and people will be disillusioned when they haven’t done the pre work to get it to perform optimally. At the beginning of 2023, Gartner reported only 15% of organizations already have data storage management solutions that classify and optimize data.

IT 143

IT Metadata Data-driven Management 143

O'Reilly on Data

JULY 25, 2023

I also installed the latest VS Code (Visual Studio Code) with GitHub Copilot and the experimental Copilot Chat plugins, but I ended up not using them much. This theme of sub-optimal defaults will come up repeatedly—that is, ChatGPT ‘knows’ what the optimal choice is but won’t generate it for me without me asking for it.

Consulting 246

Consulting Interactive Software Metadata 246

Cloudera

SEPTEMBER 17, 2020

A large oil and gas company was suffering over not being able to offer users an easy and fast way to access the data needed to fuel their experimentation. To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle.

Data Warehouse 81

Data Warehouse Experimentation Dashboards Visualization 81

AWS Big Data

MAY 1, 2025

The Clinical Insights Data Science team runs critical end-of-day batch processes that need guaranteed resources, whereas the Digital Analytics team can use cost-optimized spot instances for their variable workloads. Additionally, data scientists from both teams require environments for experimentation and prototyping as needed.

Cost-Benefit 61

Cost-Benefit Interactive Management Data Processing 61

O'Reilly on Data

APRIL 15, 2025

Its like optimizing your websites load time while your checkout process is brokenyoure getting better at the wrong thing. Instead of focusing on the few metrics that matter for your specific use case, youre trying to optimize multiple dimensions simultaneously. Second, too many metrics fragment your attention.

Experimentation 328

Experimentation Testing Metrics Measurement 328