DataRobot Blog

MARCH 16, 2023

Traditionally, developing appropriate data science code and interpreting the results to solve a use-case is manually done by data scientists. The integration allows you to generate intelligent data science code that reflects your use case. Data scientists still need to review and evaluate these results.

Data Science 98

Data Science Technology Data-driven Modeling 98

Cloudera

AUGUST 26, 2021

Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange. Before we jump into the data ingestion step, here is a quick overview of how Ozone manages its metadata namespace through volumes, buckets and keys. . Data ingestion through ‘s3’. Ozone Namespace Overview.

Data Science 108

Data Science Forecasting Metadata Machine Learning 108

AWS Big Data

APRIL 16, 2024

Running Apache Airflow at scale puts proportionally greater load on the Airflow metadata database, sometimes leading to CPU and memory issues on the underlying Amazon Relational Database Service (Amazon RDS) cluster. A resource-starved metadata database may lead to dropped connections from your workers, failing tasks prematurely.

Metadata 90

Metadata Metrics Testing Management 90

TDAN

SEPTEMBER 3, 2019

As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.” Sorry, I’m going to have to disagree with you there. You are on a fool’s errand that will just provide […].

Metadata 65

Metadata Data Governance Big Data Modeling 65

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

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Data Architecture Data Warehouse Statistics Visualization 132

O'Reilly on Data

JANUARY 29, 2019

In other words, could we see a roadmap for transitioning from legacy cases (perhaps some business intelligence) toward data science practices, and from there into the tooling required for more substantial AI adoption? Data scientists and data engineers are in demand.

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

Rocket-Powered Data Science

JULY 19, 2023

That is not a totally clear separation and distinction, but it might help to clarify their different applications of data science. Data scientists work with business users to define and learn the rules by which precursor analytics models produce high-accuracy early warnings.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

Analytics 67

Analytics Data Quality Visualization Metadata 67

Rocket-Powered Data Science

FEBRUARY 15, 2023

These rules are not necessarily “Rocket Science” (despite the name of this blog site), but they are common business sense for most business-disruptive technology implementations in enterprises. Love thy data: data are never perfect, but all the data may produce value, though not immediately.

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Strategy Experimentation Uncertainty Machine Learning 289

Cloudera

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. save the built model container, along with metadata like who built or deployed it. Cloudera Data Science Workbench 1.4.x

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

Smart Data Collective

APRIL 5, 2022

The data science profession has become highly complex in recent years. Data science companies are taking new initiatives to streamline many of their core functions and minimize some of the more common issues that they face. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

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CIO Business Intelligence

MAY 24, 2022

The company said that IDMC for Financial Services has built-in metadata scanners that can help extract lineage, technical, business, operational, and usage metadata from over 50,000 systems (including data warehouses and data lakes) and applications including business intelligence, data science, CRM, and ERP software.

Finance 140

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IBM Big Data Hub

OCTOBER 4, 2022

This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. It drives a complete governance solution without the excessive costs of switching from your current data science platform. Lifecycle Governance: Monitor, catalog and govern AI models from anywhere and throughout the AI lifecycle.

Metadata 102

Metadata Risk Risk Management Experimentation 102

Timo Elliott

JANUARY 6, 2022

The data you’ve collected and saved over the years isn’t free. If storage costs are escalating in a particular area, you may have found a good source of dark data. Analyze your metadata. If you’ve yet to implement data governance, this is another great reason to get moving quickly.

IT 133

IT Metadata Data-driven Data Governance 133

DataKitchen

JANUARY 5, 2021

Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance. Each of the roles mentioned above views the world through a preferred set of tools: Data Center/IT – Servers, storage, software.

Testing 147

Testing Data Governance Metadata Visualization 147

O'Reilly on Data

JANUARY 8, 2019

Beyond investments in narrowing the skills gap, companies are beginning to put processes in place for their data science projects, for example creating analytics centers of excellence that centralize capabilities and share best practices. Automation in data science and data. Burgeoning IoT technologies.

IoT 202

IoT Machine Learning Internet of Things Data Science 202

Rocket-Powered Data Science

MARCH 10, 2020

The training data and feature sets that feed machine learning algorithms can now be immensely enriched with tags, labels, annotations, and metadata that were inferred and/or provided naturally through the transformation of your repository of data into a graph of data.

Metadata 250

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IBM Big Data Hub

MAY 9, 2023

It drives an AI governance solution without the excessive costs of switching from your current data science platform. The resulting automation drives scalability and accountability by capturing model development time and metadata, offering post-deployment model monitoring, and allowing for customized workflows.

Metadata 77

Metadata Risk Experimentation Dashboards 77

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

CIO Business Intelligence

MARCH 24, 2023

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

MARCH 21, 2022

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Data scientist salary. Semi-structured data falls between the two.

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Unstructured Data Data Analytics Analytics Structured Data 137

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

Cloudera

OCTOBER 11, 2022

This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. And that data is likely in clouds, in data centers and at the edge.

Snapshot 90

Snapshot Data Science Digital Transformation Metadata 90

Rita Sallam

APRIL 2, 2023

We explored these questions and more at our Bake-Offs and Show Floor Showdowns at our Data and Analytics Summit in Orlando with 4,000 of our closest D&A friends and family. The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms.

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Optimization Machine Learning Insurance Risk 52

Alation

DECEMBER 15, 2022

June 2017: Dresner Advisory Services names Alation the #1 data catalog in its inaugural Data Catalog End-User Market Study. August 2017: Alation debuts as a leader in the Gartner MQ for Metadata Management Solutions. August 2018: Gartner names Alation a 2X Leader in the MQ for Metadata Management Solutions.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

CIO Business Intelligence

NOVEMBER 22, 2022

Data fabric is an architecture that enables the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. The fabric, especially at the active metadata level, is important, Saibene notes.

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Data Strategy Strategy Enterprise Consulting 145

Alation

FEBRUARY 20, 2020

Prior to the Big Data revolution, companies were inward-looking in terms of data. During this time, data-centric environments like data warehouses dealt only with data created within the enterprise. THE NEED FOR METADATA TOOLS. Given the characteristics of data acquisition, how should it be handled?

IT 52

IT Metadata Data Governance Data Warehouse 52

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance toolkit lets you direct, manage and monitor AI activities without the expense of switching your data science platform, even for models developed using third-party tools.

Risk 76

Risk Modeling Management Metadata 76

DataRobot Blog

SEPTEMBER 1, 2022

These and many other questions are now on top of the agenda of every data science team. To quantify how well your models are doing, DataRobot provides you with a comprehensive set of data science metrics — from the standards (Log Loss, RMSE) to the more specific (SMAPE, Tweedie Deviance). Learn More About DataRobot MLOps.

Metrics 145

Metrics Statistics Modeling Data Science 145

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

IBM Big Data Hub

SEPTEMBER 20, 2022

Automated, integrated data science tools help build, deploy, and monitor AI models. Often data scientists aren’t thrilled with the prospect of generating all the documentation necessary to meet ethical and regulatory standards. It’s not just about granting proper access to data science teams.

Metadata 57

Metadata Machine Learning Data-driven Modeling 57

Alation

FEBRUARY 13, 2020

Making datasets easy to find, understand, and access is the purpose of data curation—a purpose that demands well-described datasets. Data curation is a metadata management activity and data catalogs are essential data curation technology. Who Are the Data Curators? What about Data Stewards?

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., ….

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Testing Data Lake Metadata Publishing 246

Analytics Vidhya

JANUARY 27, 2022

This article was published as a part of the Data Science Blogathon. A centralized location for research and production teams to govern models and experiments by storing metadata throughout the ML model lifecycle. A Metadata Store for MLOps appeared first on Analytics Vidhya. Keeping track of […].

Metadata 143

Metadata Machine Learning Data Science Publishing 143

Alation

FEBRUARY 20, 2020

These recommendations organize the data about your data — what the industry for many years has called metadata. And yet instead of storing this metadata in a vault accessible only by IT experts, Alation makes metadata come alive as a living data recommendation engine for the business.

Metadata 52

Metadata Analytics Dashboards Sales 52