AWS Big Data

MAY 4, 2023

Amazon’s Open Data Sponsorship Program allows organizations to host free of charge on AWS. Over the last decade, we’ve seen a surge in data science frameworks coming to fruition, along with mass adoption by the data science community. Data scientists have access to the Jupyter notebook hosted on SageMaker.

Data Processing 93

Data Processing Metadata Informatics Interactive 93

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

Insight

MARCH 12, 2020

There was only one problem: literary agents, the gatekeepers of the publishing industry, kept rejecting the book?—?often Galbraith eventually opted to publish Cuckoo’s Calling through an acquaintance of sorts. but the publishing industry failed to see it. Data Collection The AIgent leverages book synopses and book metadata.

Modeling 59

Modeling Metadata Publishing Sales 59

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

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

Ontotext

FEBRUARY 1, 2024

With RDF-Star we can add a date to the relationship between the person and the book, and state that ‘Stephen King’ published The Shining in 1977. This transparency and explainability is key to extending the user community beyond engineers, data scientists, or others with coding and scripting skills.

Enterprise 59

Enterprise Management Metadata Modeling 59

Andrew White

OCTOBER 22, 2021

Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5.

IT 52

IT Data Lake Strategy Data Science 52

Cloudera

FEBRUARY 11, 2019

The Magic Quadrant (MQ) is an established, widely-referenced series of research reports published by the analyst firm Gartner, Inc. The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market.

Management 42

Management Metadata Analytics Machine Learning 42

Cloudera

JUNE 7, 2022

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 108

IT Data Architecture Unstructured Data Big Data 108

AWS Big Data

JUNE 7, 2023

They chose AWS Glue as their preferred data integration tool due to its serverless nature, low maintenance, ability to control compute resources in advance, and scale when needed. To share the datasets, they needed a way to share access to the data and access to catalog metadata in the form of tables and views.

Metadata 56

Metadata Data Lake Machine Learning Big Data 56

CIO Business Intelligence

JUNE 23, 2022

Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. We deliver cloud-native data analytics across the full data lifecycle – data distribution, data engineering, data warehousing, transactional data, streaming data, data science, and machine learning – that’s portable across infrastructures.

IT 75

IT Data Architecture Unstructured Data Big Data 75

AWS Big Data

MAY 7, 2024

This post explains how you can extend the governance capabilities of Amazon DataZone to data assets hosted in relational databases based on MySQL, PostgreSQL, Oracle or SQL Server engines. Second, the data producer needs to consolidate the data asset’s metadata in the business catalog and enrich it with business metadata.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

Analytics Vidhya

SEPTEMBER 17, 2022

This article was published as a part of the Data Science Blogathon. Any type of contextual information, like device context, conversational context, and metadata, […]. Any type of contextual information, like device context, conversational context, and metadata, […].

Metadata 380

Metadata Statistics Data Science Publishing 380

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

FEBRUARY 11, 2020

Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Comparatively few organizations have created dedicated data quality teams. Adopting AI can help data quality.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. Additionally, the task of maintaining and managing files in the data lake can be tedious and sometimes complex. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? This is the focus of my latest research which published in Jan 2019. As you can tell, data governance is a hot topic but an area that many public cloud vendors are weak in. So, why did I decide to write on this topic? I am glad you asked.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Cloudera

FEBRUARY 9, 2021

The Cost-Effective Data Warehouse Architecture. From the data ingestion perspective, in the CDP datahub cluster, a NiFi collecting dataflow is designed to continuously collect and process source streaming data then publish it into a Kafka topic in real-time. Avro Schema without Kafka Metadata Example. {.

Data Warehouse 69

Data Warehouse Cost-Benefit Metadata Management 69

Analytics Vidhya

SEPTEMBER 13, 2022

This article was published as a part of the Data Science Blogathon. Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting. It consists of historical and commutative data from single or multiple sources.

Data Warehouse 326

Data Warehouse Forecasting Big Data Data Science 326

Rita Sallam

JULY 22, 2016

By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities. Research VP, Business Analytics and Data Science.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. LPG lacks schema and semantics, which makes it inappropriate for publishing and sharing of data. This makes LPGs inflexible.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 89

Management Metadata Data Architecture Data Lake 89

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

IBM Big Data Hub

FEBRUARY 22, 2024

IBM’s Scaled Data Science Method , an extension of CRISP-DM, offers governance across the AI model lifecycle informed by collaborative input from data scientists, industrial-organizational psychologists, designers, communication specialists and others. This should all be baked into the interpretable, findable metadata).

Metadata 103

Metadata Measurement Risk Modeling 103

Cloudera

DECEMBER 12, 2022

Gartner has also been providing very pointed guidance to clients on the urgency and inevitability of hybrid and multi-cloud for data management. In March 2022, Gartner published A Strategic Roadmap for Migrating Data Management to the Cloud. Some do multi-cloud, but not hybrid and not really data management.

Recreation/Entertainment 90

Recreation/Entertainment Insurance Digital Transformation Metadata 90

Insight

MAY 16, 2019

In this post, I describe how I built an object detection algorithm (FurniSure), during my time as an Insight Data Science Fellow, using a convolutional neural network-based algorithm called “You Only Look Once” to identify, classify, and localize different types of furniture in images and videos. Python-Labellmg interface.

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

Cloudera

SEPTEMBER 9, 2022

As a data analyst or data scientist, we would all love to be able to do all these things, and much more. This is the promise of the modern data lakehouse architecture. New innovations in the cloud have driven data explosions. We’re asking new and more complex questions of our data to gain even greater insights.

Metadata 97

Metadata Machine Learning Unstructured Data Data Lake 97

AWS Big Data

AUGUST 16, 2023

Change Data Capture (CDC) in the context of a data lake refers to the process of capturing and propagating changes made to source data. Source systems often lack the capability to publish data that is modified or changed. We fetch the metadata of the users_xxxxxx table from Athena.

Data Lake 69

Data Lake Metadata Testing Snapshot 69

Andrew White

JANUARY 9, 2022

I try to relate as much published research as I can in the time available to draft a response. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend.

Analytics 64

Analytics Measurement Modeling Data-driven 64

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Machine Learning 68

Machine Learning Data Warehouse Modeling Cost-Benefit 68

IBM Big Data Hub

MAY 9, 2023

Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1] 1] Users can access data through a single point of entry, with a shared metadata layer across clouds and on-premises environments.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Domino Data Lab

JULY 21, 2019

But you also need to have metadata around the data. And many of you who worked with open data will have observed that the open data can be a bit dodgy in terms of quality. And what you really need is you want the data users to be to be involved in the metadata documentation. That’s the basic idea.

Metadata 65

Metadata Statistics Risk Machine Learning 65

CIO Business Intelligence

JUNE 14, 2023

Additionally, it is vital to be able to execute computing operations on the 1000+ PB within a multi-parallel processing distributed system, considering that the data remains dynamic, constantly undergoing updates, deletions, movements, and growth.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

CIO Business Intelligence

SEPTEMBER 22, 2023

Others aim simply to manage the collection and integration of data, leaving the analysis and presentation work to other tools that specialize in data science and statistics. DMP vs. CDP Lately a cousin of DMP has evolved, called the customer data platform (CDP).

Management 101

Management Advertising Data Lake Sales 101

CIO Business Intelligence

JUNE 9, 2022

Others aim simply to manage the collection and integration of data, leaving the analysis and presentation work to other tools that specialize in data science and statistics. Lately a cousin of DMP has evolved, called the customer data platform (CDP). Some DMPs specialize in producing reports with elaborate infographics.

Management 139

Management Advertising Data Lake Sales 139

Domino Data Lab

OCTOBER 9, 2019

Data Science meets Climate Science. Environment Data Management (EDM) is an annual meeting for data management teams at the NOAA , this year chaired by Kim Valentine and Eugene Burger. Data veracity, data stewardship, and heros of data science. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

O'Reilly on Data

MARCH 20, 2019

Especially in today’s overheated and turnover-prone data “science” market.) Along with model documentation, all modeling artifacts, source code, and associated metadata need to be managed, versioned, and audited for security like the valuable commercial assets they are.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222