Ontotext

MAY 25, 2023

The event attracts individuals interested in graph technology, machine learning and natural language processes in numerous verticals, including publishing, government, financial services, manufacturing and retail. An entire conference track was dedicated to topics like graph embeddings, vector representations and matrix operations.

Machine Learning 52

Machine Learning Structured Data Unstructured Data Predictive Modeling 52

IBM Big Data Hub

APRIL 18, 2023

At this year’s National Association of Broadcasters (NAB) convention, the IBM sports and entertainment team accepted an Emmy® Award for its advancements in curating sports highlights through artificial intelligence (AI) and machine learning (ML). And that leads to innovations that can change an industry.”

Recreation/Entertainment 75

Recreation/Entertainment Broadcasting Unstructured Data Consulting 75

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. Numbers are only good if the data quality is good.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Cloudera

JUNE 7, 2022

We live in a hybrid data world. 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 107

IT Data Architecture Unstructured Data Big Data 107

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

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. This is quantitative data. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 85

Big Data Software Consulting Unstructured Data 85

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3.

Data Lake 87

Data Lake Big Data Consulting Data Warehouse 87

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. One solution with immense potential is ”edge computing.”

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

IBM Big Data Hub

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. This blog post will clarify some of the ambiguity. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 59

Deep Learning Machine Learning Unstructured Data Modeling 59

Cloudera

MAY 14, 2024

This form of hybrid also goes a level deeper than one may find in a standard hybrid cloud, accounting for the entirety of the data lifecycle, whether that’s the point of ingestion, warehousing, or machine learning—even when that end-to-end data lifecycle is split between entirely different environments.

Data Architecture 92

Data Architecture Data Governance Unstructured Data Structured Data 92

Domino Data Lab

AUGUST 9, 2021

Before selecting a tool, you should first know your end goal – machine learning or deep learning. Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

IBM Big Data Hub

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models.

Unstructured Data 79

Unstructured Data Deep Learning Cost-Benefit Modeling 79

Ontotext

DECEMBER 15, 2022

Connecting the dots of data of all types. To begin with, Fantastic Finserv has to handle a wide variety of data. This includes traditional structured data such as: Reference data – the data used to relate data to information outside of the organization.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

Ontotext

FEBRUARY 26, 2024

RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. Using machine learning, RED indicates the impact of events on stock prices. It compares actual price changes to expected changes based on historical data.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 86

Metadata Big Data Optimization Unstructured Data 86

bridgei2i

FEBRUARY 28, 2020

The rise of new kinds of data and analysis techniques from AI to machine learning that is actually driving the decisions behind the systems that can enable the so-called transformations. With AI, apart from the quantitative data, unstructured data systems can be assessed for risk management.

Risk Management 78

Risk Management Unstructured Data Machine Learning Digital Transformation 78

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. Using visualizations to make smarter decisions.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Cloudera

OCTOBER 30, 2018

In this blog post, Sheryl outlines how next-gen CIP applications are delivering a better customer experience, and why businesses are relying on CIPs as their preferred path to customer insights. Structured data from operational data stores now provides a small slice of the overall data needed to improve customer experience.

Unstructured Data 42

Unstructured Data Data Lake Machine Learning Interactive 42

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. But this was only the tip of the analytics iceberg. displaying BI insights for human users).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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. Sign up for a trial to see for yourself.

Unstructured Data 100

Unstructured Data Cost-Benefit Metadata Machine Learning 100