Ontotext

FEBRUARY 14, 2024

CEEL is now immediately available as part of our text analysis offerings, coming preconfigured as part of the new version of the Ontotext Metadata Studio (OMDS). This makes it an effective and cost-efficient system for extracting entities from large-scale data collections.

Cost-Benefit 52

Cost-Benefit Modeling Metadata Optimization 52

O'Reilly on Data

MARCH 31, 2020

The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 98

Dashboards Analytics Metadata Data Warehouse 98

AWS Big Data

JULY 3, 2023

It provides features such as ACID transactions on top of Amazon S3-based data lakes, schema evolution, partition evolution, and data versioning. 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 86

Snapshot Data Lake Testing Strategy 86

AWS Big Data

FEBRUARY 1, 2024

The Common Crawl corpus contains petabytes of data, regularly collected since 2008, and contains raw webpage data, metadata extracts, and text extracts. In addition to determining which dataset should be used, cleansing and processing the data to the fine-tuning’s specific need is required.

Metadata 99

Metadata Modeling Data Processing Unstructured Data 99

Alation

OCTOBER 12, 2022

This method differs from traditional business analysis in that it normally will include hypothesis testing around a single research question; by contrast,the traditional business approach focuses on reviewing outcomes and prescribing actions or new questions. What Is the Role of Statistics in Quantitative Data Analysis?

Statistics 52

Statistics Sales Testing Marketing 52

O'Reilly on Data

JANUARY 28, 2019

The problems with consent to data collection are much deeper. It comes from medicine and the social sciences, in which consenting to data collection and to being a research subject has a substantial history. We really don't know how that data is used, or might be used, or could be used in the future.

Insurance 170

Insurance Metadata Data Collection Marketing 170

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 85

Metadata Data Lake Optimization Strategy 85

CIO Business Intelligence

SEPTEMBER 22, 2023

How to choose which DMP is right for your organization While each organization will have its own unique needs, a number of common factors are important to keep in mind when selecting a data management platform. The platform’s data collection, storage, scalability, and processing capabilities will also weigh heavily in making your choice.

Management 103

Management Advertising Data Lake Sales 103

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

CIO Business Intelligence

JUNE 9, 2022

Advertisers use OnAudience to build an understanding of their audience from data collected from multiple sources. The Data Management tool from SAS is designed to be heavily integrated with many data sources, be they data lakes, data pipes such as Hadoop, data fabrics, or mere databases. OnAudience.

Management 142

Management Advertising Data Lake Sales 142

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. An example of a data science tool is Dataiku.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

While use of Sawzall at Google is in decline today, we believe the lessons discussed here have survived the test of time and are employed by descendant systems used throughout Google. Record-level program scope As a data scientist, you write a Sawzall script to operate at the level of a single record.

Data Science 56

Data Science Statistics Testing Metadata 56

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataKitchen

JUNE 24, 2021

Bergh added, “ DataOps is part of the data fabric. You should use DataOps principles to build and iterate and continuously improve your Data Fabric. Automate the data collection and cleansing process. Education is the Biggest Challenge.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

Alation

FEBRUARY 17, 2023

This is because you will know what data you can trust, and you will have processes to create and upkeep data, as well as curated metadata to exploit data’s full capabilities. So, establishing a framework to store data by its source is a great place to start. Do testing companies use data governance tools?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

O'Reilly on Data

DECEMBER 19, 2018

have a large body of tools to choose from: IDEs, CI/CD tools, automated testing tools, and so on. are only starting to exist; one big task over the next two years is developing the IDEs for machine learning, plus other tools for data management, pipeline management, data cleaning, data provenance, and data lineage.

Machine Learning 261

Machine Learning Software Metadata Testing 261

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Andrew White

MARCH 31, 2023

See Product Management Practices Crucial for Data and Analytics Asset Monetization. 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. Both build semantic maps that span silos of data.

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