Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success. For more on the data-driven journey, I would encourage you to view our Cloudera Now presentation.

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

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

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. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 119

Unstructured Data Metadata Management Analytics 119

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 112

IT Data Architecture Unstructured Data Big Data 112

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. From Data Silos to Data Fabric with Knowledge Graphs. Ontotext Knowledge Graph Platform: The Modern Way of Building Smart Enterprise Applications.

Metadata 52

Metadata Unstructured Data Visualization Enterprise 52

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. To help eliminate tool sprawl, an enterprise-grade AIOps platform can provide a holistic view of IT operations on a central pane of glass for monitoring and management.

Cost-Benefit 82

Cost-Benefit Insurance Unstructured Data Machine Learning 82

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 97

IT Data Architecture Unstructured Data Big Data 97

Alation

JUNE 2, 2022

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. A data catalog is a central hub for XAI and understanding data and related models. Machine Learning Technology. Other Technologies. Conclusion.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

MARCH 29, 2022

Organizations may acquire a lot of data, but they aren’t getting much value from it. It is estimated that nearly 75% of the data that enterprises collect remains unused, and thus, the value is not realized. It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. In the future of healthcare, data lake is a prominent component, growing across the enterprise.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Ontotext

NOVEMBER 22, 2020

Ontotext’s extensive experience of bringing enterprise-level to national and global brands understands this and has for over a decade strived to make the power of semantic technology accessible. From packaging and deployment to monitoring tools and report generations, the Platform has everything an enterprise needs.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

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. Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. versions).

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

AWS Big Data

MARCH 7, 2024

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can also store other data in purpose-built data stores to analyze and get fast insights from both structured and unstructured data.

Data Lake 113

Data Lake Analytics Dashboards Metrics 113

Sisense

MAY 28, 2020

They want data in the moment, on the go, and personalized. As enterprises demand data infrastructures that can meet this growth in real-time data — and ultimately assist with their product differentiation strategy — the pressure put on product teams is huge. “Not Pressure on infrastructure builds.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

AWS Big Data

MARCH 10, 2023

Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes.

Data Lake 103

Data Lake Sales Data Warehouse Snapshot 103

Ontotext

DECEMBER 15, 2022

Today’s enterprises are increasingly daunted by the realization that more data doesn’t automatically equal deeper knowledge and better business decisions. Obviously, not all of that data is accessible to businesses, but what they can access is still overwhelming. Enter metadata.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

O'Reilly on Data

FEBRUARY 11, 2020

Just 20% of organizations publish data provenance and data lineage. Adopting AI can help data quality. Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues. Can AI be a catalyst for improved data quality?

Data Quality 311

Data Quality Metadata Data Governance Publishing 311

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. What Happened to Tradition BI?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Ontotext

MAY 22, 2023

At the same time, most data management (DM) applications require 100% correct retrieval, 0% hallucination! Many enterprise data and knowledge management tasks require strict agreement, with a firm deterministic contract, about the meaning of the data. LLM will not replace knowledge graphs either.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

IBM Big Data Hub

AUGUST 17, 2023

Year after year, IBM Consulting works with the United States Tennis Association (USTA) to transform massive amounts of data into meaningful insight for tennis fans. This year, the USTA is using watsonx , IBM’s new AI and data platform for business. million data points are captured, drawn from every shot of every match.

Unstructured Data 90

Unstructured Data Statistics Consulting Enterprise 90

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. FILE_SYSTEM_OPTIMIZED Bucket (“FSO”).

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

Sisense

AUGUST 21, 2020

AI and machine learning are the future of every industry, especially data and analytics. Reading through the Gartner Top 10 Trends in Data and Analytics for 2020 , I was struck by how different terms mean different things to different audiences under different contexts. Trend 5: Augmented data management.

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

Cloudera

SEPTEMBER 6, 2018

Handle increases in data volume gracefully. Support machine learning (ML) algorithms and data science activities, to help with name matching, risk scoring, link analysis, anomaly detection, and transaction monitoring. Provide audit and data lineage information to facilitate regulatory reviews. Cloudera Enterprise.

Machine Learning 40

Machine Learning Big Data Risk Unstructured Data 40

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Streaming data analytics. .

Cost-Benefit 76

Cost-Benefit Big Data ROI Risk 76

Ontotext

SEPTEMBER 2, 2020

Instead, it creates a unified way, sometimes called a data fabric, of accessing an organization’s data as well as 3rd party or global data in a seamless manner. Data is represented in a holistic, human-friendly and meaningful way. With knowledge graphs, automated reasoning becomes even more of a possibility.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

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. Choose a Metadata Storage Option.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. AI can help business users extract and produce (i.e.,

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 88

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 88

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.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94