Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies. Unlike software, ML models need continuous tuning.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

CIO Business Intelligence

JANUARY 22, 2024

Since the introduction of ChatGPT, the healthcare industry has been fascinated by the potential of AI models to generate new content. While the average person might be awed by how AI can create new images or re-imagine voices, healthcare is focused on how large language models can be used in their organizations.

Unstructured Data 79

Unstructured Data Digital Transformation Data Strategy Modeling 79

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 comes in many forms.

Data Architecture 96

Data Architecture Data Governance Unstructured Data Structured Data 96

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities.

Digital Transformation 137

Digital Transformation Unstructured Data Machine Learning Risk Management 137

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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

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 95

Data Lake Unstructured Data Data Warehouse Data Quality 95

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere accesses and integrates both SAP and non-SAP data sources into end-users’ data flows, including on-prem data warehouses, cloud data warehouses and lakehouses, relational databases, virtual data products, in-memory data, and applications that generate data (such as external API data loads).

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

CIO Business Intelligence

APRIL 24, 2024

Finally, the flow of AMA reports and activities generates a lot of data for the SAP system, and to be more effective, we’ll start managing it with data and business intelligence.” The goal is to correlate all types of data that affect assets and bring it all into the digital twin to take timely action,” says D’Accolti.

Digital Transformation 89

Digital Transformation Business Intelligence Unstructured Data Data Lake 89

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

Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

JUNE 7, 2022

The move to remote work and the surge in online everything during the COVID-19 pandemic have led many companies that provide financial services to rethink their business models to accommodate the changing needs of employees and customers. NLP solutions can be used to analyze the mountains of structured and unstructured data within companies.

Unstructured Data 80

Unstructured Data Deep Learning Insurance Interactive 80

Alation

AUGUST 4, 2022

Aligning business goals to data usage is a key foundation. There is no digital transformation without business-aligned data control,” Capgemini Executive Steve Jones adds. “The architectural model of big data is fundamental to this.”. Everything comes down to what organizations do with data.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Ontotext

JANUARY 29, 2024

These will include developing a better understanding of AI, recognizing the role semantic metadata plays in data fabrics, and the rapid acceleration and adoption of knowledge graphs — which will be driven by large language models (LLMs) and the convergence of labeled property graphs (LPGs) and resource description frameworks (RDFs).

Strategy 52

Strategy Management Metadata Data-driven 52

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

CDW Research Hub

SEPTEMBER 15, 2020

Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Traditional data warehouses are often too slow and can’t handle large volumes of data or different types of semi-structured or unstructured data.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement. How does Data Virtualization manage data quality requirements?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. Speaking of which.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

CIO Business Intelligence

AUGUST 9, 2022

Data engineers and data scientists often work closely together but serve very different functions. Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data engineer vs. data architect.

Analytics 116

Analytics Data Science Statistics Unstructured Data 116

datapine

DECEMBER 4, 2019

The accuracy of the predictions depends on the data used to create the model. For instance, if a model is created based on the factors inherent at one company, it doesn’t necessarily apply at a second company. The same may be true about a model for one year compared to the next year within the same company.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

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

datapine

AUGUST 14, 2019

Geet our bite-sized free summary and start building your data skills! What Is A Data Science Tool? In the past, data scientists had to rely on powerful computers to manage large volumes of data. Our Top Data Science Tools. Here, we list the most prominent ones used in the industry. Source: mathworks.com.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Alation

DECEMBER 15, 2021

A data governance strategy helps prevent your organization from having “bad data” — and the poor decisions that may result! Here’s why organizations need a governance strategy: Makes data available: So people can easily find and use both structured and unstructured data. Build a Governance Model.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Ontotext

DECEMBER 1, 2023

Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

Metadata 78

Metadata Sales Consulting Enterprise 78

Octopai

MARCH 22, 2023

This makes it an ideal platform for organizations that handle sensitive data. 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.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

IBM Big Data Hub

AUGUST 4, 2023

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

Ontotext

JANUARY 6, 2021

Having a formal definition that is both machine and human readable of enterprise-level models describing important and shared concepts across all business departments and reach agreement on common meta-data, reference and master data entities has an enormous value.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Cloudera

OCTOBER 8, 2020

Businesses are now faced with more data, and from more sources, than ever before. But knowing what to do with that data, and how to do it, is another thing entirely. . Poor data quality costs upwards of $3.1 Ninety-five percent of businesses cite the need to manage unstructured data as a real problem.

Digital Transformation 104

Digital Transformation Experimentation Unstructured Data Uncertainty 104

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection. Business analyst.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection. Business analyst.

Finance 98

Finance IT Software Reporting 98

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

CIO Business Intelligence

MARCH 29, 2022

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. You’ve lost that opportunity if the data has been thrown away. . •

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. E-commerce giants like Alibaba and Amazon extensively use big data to understand the market. Unlike traditional databases, processing large data volumes can be quite challenging. Easy implementation.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52