Ontotext

MAY 26, 2021

In the same way as with data linking, we have to adjust our ML algorithms by giving them plenty of documents to learn from. Once developed and trained, these algorithms become the building blocks of systems that can automatically interpret data. Evaluation is for AI systems what quality assurance (QA) is for software systems.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

CIO Business Intelligence

SEPTEMBER 12, 2024

The main reason is that it is difficult and time-consuming to consolidate, process, label, clean, and protect the information at scale to train AI models. The examples above demonstrate how expanding AI applications and unstructured data help create transformational outcomes.

Unstructured Data 119

Unstructured Data Data Quality Structured Data Machine Learning 119

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. That work takes a lot of machine learning and AI to accomplish.

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Without this, LLMs cannot reliably interpret or generate meaningful outputs.

Data Quality 117

Data Quality Unstructured Data Testing Data-driven 117

CIO Business Intelligence

OCTOBER 2, 2024

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. During the blending process, duplicate information can also be eliminated.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

CIO Business Intelligence

MARCH 9, 2022

Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio. They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. The challenges of data. Data curation.

Unstructured Data 90

Unstructured Data Recreation/Entertainment Structured Data Reporting 90

CIO Business Intelligence

JANUARY 24, 2024

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

Cloudera

MAY 14, 2024

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models.

Data Architecture 99

Data Architecture Data Governance Unstructured Data Structured Data 99

erwin

OCTOBER 24, 2019

. • Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards. Analyzing metadata – Understand how data relates to the business and what attributes it has. Addressing the Complexities of Metadata Management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. And until recently, such governance processes have been fragmented.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Ontotext

FEBRUARY 14, 2024

Ivory tower modeling We’ve seen too many models developed by isolated ontologists that don’t survive the first battle with the data. There’s a famous saying by a statistician, George Box, “All models are wrong, but some are useful.” ” So, how do you know whether your model is useful?

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

CIO Business Intelligence

APRIL 4, 2024

Some prospective projects require custom development using large language models (LLMs), but others simply require flipping a switch to turn on new AI capabilities in enterprise software. “AI A human reviews it to make sure it makes sense, and if it does, the AI incorporates that into the learning model,” she says.

Enterprise 134

Enterprise Cost-Benefit Forecasting Sales 134

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. Unlike software, ML models need continuous tuning.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Define data quality check task to test a package, generate docs and copy the docs to required S3 location data_quality_check = BashOperator( task_id='data_quality_check', dag=dag, bash_command=''' /usr/local/airflow/.local/bin/dbt

Data Warehouse 119

Data Warehouse Testing Data Quality Reporting 119

Ontotext

JULY 29, 2021

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Octopai

MARCH 22, 2023

Cost: Snowflake’s pricing model is based on usage, which means you only pay for what you use. This can be more cost-effective than traditional data warehousing solutions that require a significant upfront investment. Support for multiple data structures.

Data Warehouse 103

Data Warehouse Cost-Benefit Unstructured Data Optimization 103

Ontotext

SEPTEMBER 15, 2020

There must be a representation of the low-level technical and operational metadata as well as the ‘real world’ metadata of the business model or ontologies. Connecting the data in a graph allows concepts and entities to complement each other’s description. Consider using data catalogs for this purpose.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web.

Cost-Benefit 87

Cost-Benefit Big Data Technology Metadata 87

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Wayne Yaddow

FEBRUARY 26, 2025

This is particularly helpful in environments where upstream data sources are subject to frequent revisions. If a dataset that normally has 10 columns suddenly shows 12 columns, for example, or if a date field starts appearing as a string, the AI model raises alerts immediately.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

AWS Big Data

MARCH 7, 2023

ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. Unlike ingestion processes, data can be transformed as per business rules before loading. You can apply technical or business data quality rules and load raw data as well.

Analytics 79

Analytics Data Warehouse Data Lake Metadata 79

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web.

Cost-Benefit 75

Cost-Benefit Big Data Technology Metadata 75

AWS Big Data

AUGUST 15, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. This model enables the units to focus on insights, with costs aligned to actual consumption.

Data Lake 109

Data Lake Data Warehouse Data Governance Publishing 109

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

Ontotext

JANUARY 6, 2021

A knowledge graph can be used as a database because it structures data that can be queried such as through a query language like SPARQL. Reuse of knowledge from third party data providers and establishing data quality principles to populate it. The connections made through these descriptions create context.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

AWS Big Data

JULY 12, 2023

With a wide array of data sources, including transactional databases, log files, and event streams, you need a simple-to-use solution capable of efficiently ingesting and transforming large volumes of data in real time, ensuring data cleanliness, structural integrity, and data team collaboration.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production? There are essentially four types encountered: image/video, audio, text, and structured data.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40