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

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

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. Semi-structured data falls between the two.

Unstructured Data 134

Unstructured Data Data Analytics Analytics Structured Data 134

Smart Data Collective

AUGUST 28, 2021

In other words, data warehouses store historical data that has been pre-processed to fit a relational schema. Data lakes are much more flexible as they can store raw data, including metadata, and schemas need to be applied only when extracting data. Target User Group.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Unstructured Data 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent.

Unstructured Data 117

Unstructured Data Metadata Management Analytics 117

Smart Data Collective

APRIL 5, 2022

This feature helps automate many parts of the data preparation and data model development process. This significantly reduces the amount of time needed to engage in data science tasks. A text analytics interface that helps derive actionable insights from unstructured data sets. Neptune.ai. Neptune.AI

Cost-Benefit 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

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

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

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

Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 108

IT Data Architecture Unstructured Data Big Data 108

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Ontotext

DECEMBER 16, 2021

A critical component of knowledge graphs’ effectiveness in this field is their ability to introduce structure to unstructured data. Many rich sources of information in the medical world are written documents with poor quality metadata. That information enhances the graph, which improves the NLP model. Clinical study.

Metadata 98

Metadata Reporting Unstructured Data Risk 98

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

CIO Business Intelligence

JUNE 23, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 81

IT Data Architecture Unstructured Data Big Data 81

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. Crafting a Knowledge Graph: The Semantic Data Modeling Way. We also continued to improve our knowledge graph platform. Check out Ontotext Platform 3.1 , 3.2 , and 3.3.

Metadata 52

Metadata Unstructured Data Visualization Enterprise 52

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. With this, the recommendation was the formation of a large enterprise data governance board with CEO sponsorship.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

IBM Big Data Hub

JANUARY 5, 2023

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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

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.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Query large-sized data without loading data back and forth and incurring twice the cost.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 100

Data Lake Sales Data Warehouse Snapshot 100

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Pre-Check: Data Lake Cluster.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Coordinates distribution of data and metadata, also known as shards.

Snapshot 66

Snapshot Unstructured Data Dashboards Interactive 66

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. . • You have data but don’t use it.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Sisense

MAY 28, 2020

“Not only do they have to deal with data that is distributed across on-premises, hybrid, and multi-cloud environments, but they have to contend with structured, semi-structured, and unstructured data types. That’s without mentioning outdated metadata—the data about data that provides data intelligence,” said Gopal.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Cloudera

AUGUST 30, 2018

Digital technologies are changing business models, reshaping how companies go-to-market, win new customers and drive new revenue-producing opportunities. Below are a few C6 highlights to get you started: A new release of Cloudera’s Altus Director – the tool that helps you spin up multiple data and compute clusters in the cloud.

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

O'Reilly on Data

FEBRUARY 11, 2020

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. An additional 7% are data engineers.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

CIO Business Intelligence

MARCH 6, 2024

SAP unveiled Datasphere a year ago as a comprehensive data service, built on SAP Business Technology Platform (BTP), to provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

Unstructured Data 112

Unstructured Data Dashboards Business Intelligence Data Governance 112

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

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

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Modeling 95

Modeling Metadata Data Processing Unstructured Data 95

erwin

JUNE 27, 2019

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Evaluating a Data Modeling Tool – Key Features.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

IBM Big Data Hub

AUGUST 17, 2023

Bringing together traditional machine learning and generative AI with a family of enterprise-grade, IBM-trained foundation models, watsonx allows the USTA to deliver fan-pleasing, AI-driven features much more quickly. million data points are captured, drawn from every shot of every match. As play progresses, a further 2.7

Unstructured Data 93

Unstructured Data Statistics Consulting Enterprise 93

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. It’s a good idea to record metadata.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Alation

APRIL 6, 2023

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52