AWS Big Data

JULY 14, 2023

Defining and capturing a business capability model If an enterprise doesn’t have a system to capture the business capability model, consider defining and finding a way to capture the model for better insight and visibility, and then map it with digital assets like APIs. It keeps evolving with business requirements and usage.

Modeling 71

Modeling Visualization Reporting Measurement 71

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. The AIgent was built with BERT, Google’s state-of-the-art language model.

Modeling 59

Modeling Metadata Publishing Sales 59

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications.

Cost-Benefit 95

Cost-Benefit Visualization Modeling Machine Learning 95

Ontotext

FEBRUARY 1, 2024

We as a taxonomy community are facing rapid technological change and grappling with where our discipline fits into a world captivated by ChatGPT and other generative models. The challenge of complexity Knowledge models for taxonomy have responded to an increasing need for sophistication and expressiveness.

Enterprise 59

Enterprise Management Metadata Modeling 59

AWS Big Data

MAY 4, 2023

After deployment, the user will have access to a Jupyter notebook, where they can interact with two datasets from ASDI on AWS: Coupled Model Intercomparison Project 6 (CMIP6) and ECMWF ERA5 Reanalysis. Solution overview Each day, the UK Met Office produces up to 300 TB of weather and climate data, a portion of which is published to ASDI.

Data Processing 97

Data Processing Metadata Informatics Interactive 97

AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Also, datasets are accessed for ML, data exporting, and publishing needs. Let’s look at the components of the architecture in more detail.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference.

Data Lake 83

Data Lake Data Governance Data Architecture Data Warehouse 83

Ontotext

DECEMBER 16, 2020

In its third generation, Ontotext Platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content. The article also explains how enterprise knowledge graphs enable organizations to incorporate machine learning algorithms for the smart interpretation of their data.

Metadata 52

Metadata Unstructured Data Visualization Enterprise 52

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

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. A brief pictorial history.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Ontotext

NOVEMBER 22, 2020

Semantic Objects and the Semantic Objects Modeling Language (SOML) is a simple way to describe business objects or domain objects. The Platform is able to generate the initial Semantic Objects model, which can be modified and extended by the business user without having to work directly with the underlying knowledge graphs.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

CIO Business Intelligence

MARCH 29, 2022

For example, AI and machine learning projects offer great potential value, but they are speculative. Fortunately, learning-based projects typically use data collected for other purposes. . It’s also important to go back to raw data to ask new questions and train new models, particularly as the world is constantly changing.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Cloudera

JUNE 7, 2022

And, as Deloitte put it: “Hybrid cloud is the de facto model”. . 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 110

IT Data Architecture Unstructured Data Big Data 110

CIO Business Intelligence

JUNE 23, 2022

And, as Deloitte put it: “Hybrid cloud is the de facto model”. . 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 97

IT Data Architecture Unstructured Data Big Data 97

AWS Big Data

MARCH 10, 2023

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data. Dimension-based models have been used extensively to build data warehouses.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

AWS Big Data

MARCH 30, 2023

An event-driven architecture is a software design pattern in which decoupled applications can asynchronously publish and subscribe to events via an event broker. Amazon Elastic Kubernetes Service (Amazon EKS) is becoming a popular choice among AWS customers to host long-running analytics and AI or machine learning (ML) workloads.

Data-driven 73

Data-driven Metadata Testing Management 73

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. But for most enterprise, using machine learning…not really.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

JANUARY 15, 2021

McKnight Consulting Group recently published their own third party benchmark study comparing the price-performance of Cloudera Data Warehouse to 4 other prominent cloud data warehouse vendors. Some examples of recent optimizations in Impala include: New multithreading model (see dedicated blog post ). Benchmark Description.

Data Warehouse 94

Data Warehouse Cost-Benefit Consulting Interactive 94

O'Reilly on Data

FEBRUARY 11, 2020

Just 20% of organizations publish data provenance and data lineage. Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. What’s covered in this post is already implemented and available in the Guidance for Connecting Data Products with Amazon DataZone solution, published in the AWS Solutions Library.

Metadata 77

Metadata Data Lake Data Processing Data-driven 77

AWS Big Data

OCTOBER 4, 2023

Use business terms to search, share, and access cataloged data, making data accessible to all the configured users to learn more about data they want to use with the business glossary. Automate data discovery and cataloging with machine learning (ML).

Metadata 103

Metadata Data Lake Publishing Data Governance 103

Ontotext

JANUARY 10, 2024

In Computer Science, we are trained to use the Okham razor – the simplest model of reality that can get the job done is the best one. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Analytics Vidhya

SEPTEMBER 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context. However, we can improve the system’s accuracy by leveraging contextual information.

Metadata 391

Metadata Statistics Data Science Publishing 391

IBM Big Data Hub

JULY 28, 2022

Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively.

Metadata 57

Metadata Data Quality Machine Learning Statistics 57

AWS Big Data

APRIL 25, 2023

AWS Step Functions is a visual workflow service that helps developers use AWS services to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning (ML) pipelines. Upon a successful file transfer, Step Functions publishes an event in the consumer account’s EventBridge.

Sales 72

Sales Visualization Software Marketing 72

DataRobot Blog

MARCH 9, 2022

This article was originally published at Algorithimia’s website. With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task. The company was acquired by DataRobot in 2021. Find out more about DataRobot MLOps here.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

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. Answer: Better than every other vendor?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Cloudera

FEBRUARY 22, 2022

Companies such as Adobe , Expedia , LinkedIn , Tencent , and Netflix have published blogs about their Apache Iceberg adoption for processing their large scale analytics datasets. . In CDP we enable Iceberg tables side-by-side with the Hive table types, both of which are part of our SDX metadata and security framework.

Snapshot 107

Snapshot Metadata Cost-Benefit Data Architecture 107

Ontotext

MAY 22, 2023

What is the future of knowledge graphs in the era of ChatGPT and Large Language Models? To start with, Large Language Models (LLM) will not replace databases. They are good for compressing information, but one cannot retrieve from such a model the same information that it got trained on. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

IBM Big Data Hub

APRIL 27, 2022

A data fabric utilizes continuous analytics over existing, discoverable and inferenced metadata to support the design, deployment and utilization of integrated and reusable datasets across all environments, including hybrid and multicloud platforms.” [1]. This improves data engineering productivity and time-to-value for data consumers.

Management 90

Management Metadata Data Architecture Data Lake 90

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. The answer is that generative AI leverages recent advances in foundation models. Watsonx.ai

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Ontotext

FEBRUARY 12, 2024

This quickly becomes difficult to scale with data discovery and data version issues, schema evolution, tight coupling, and a lack of semantic metadata. Data products are nodes on the mesh that encapsulate structural components such as code, data, metadata, and infrastructure.

IT 64

IT Metadata Data Quality Data Lake 64

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

Machine Learning 69

Machine Learning Data Warehouse Modeling Cost-Benefit 69

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. Rather than publish an agenda as most technology conferences do, why not let people mingle, discuss, and propose topics and possible sessions? Latest in quantum physics?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 104

Metadata Measurement Risk Modeling 104