AWS Big Data

MAY 16, 2024

As an AWS Partner, CARTO offers a software solution on the curated digital catalog AWS Marketplace that seamlessly integrates distinctive capabilities for spatial visualization, analysis, and app development directly within the AWS data warehouse environment. To learn more, visit CARTO.

Data Warehouse 118

Data Warehouse Visualization Cost-Benefit Data-driven 118

AWS Big Data

OCTOBER 26, 2023

times better price-performance than other cloud data warehouses on real-world workloads using advanced techniques like concurrency scaling to support hundreds of concurrent users, enhanced string encoding for faster query performance, and Amazon Redshift Serverless performance enhancements. Amazon Redshift delivers up to 4.9

Data Warehouse 111

Data Warehouse Cost-Benefit Dashboards Optimization 111

CIO Business Intelligence

MARCH 22, 2022

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Ready to evolve your analytics strategy or improve your data quality?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Sanjeev Mohan

SEPTEMBER 14, 2020

The boundaries between data management and advanced analytics are blurring fast. Databases are enhancing capabilities to build, train and validate machine learning models right where the data sits – inside the databases and data warehouses. to sentiment analysis to graph and time series analysis.

Machine Learning 93

Machine Learning Data Warehouse Deep Learning Statistics 93

Smart Data Collective

OCTOBER 13, 2021

As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields).

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

CIO Business Intelligence

JANUARY 20, 2023

It provides rapid, direct access to trusted data for data scientists, business analysts, and others who need data to drive business value. Focus on Outcomes Analytics and AI hold the promise of driving better business insights from data warehouses, streams, and lakes. Just starting out with analytics?

Analytics 137

Analytics Key Performance Indicator Unstructured Data Deep Learning 137

CIO Business Intelligence

MARCH 9, 2022

Some examples include: Customer 360 analytics, retail inventory and sales analysis, manufacturing operational analysis, eCommerce fraud prevention, network security intelligence, data warehouse consolidation and discount pricing optimization. Ready to evolve your analytics strategy or improve your data quality?

Data-driven 110

Data-driven Analytics Machine Learning Deep Learning 110

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. After a few iterations, this results in a well-defined business question with identifiable supporting data.

Statistics 84

Statistics Machine Learning Deep Learning Sales 84

CIO Business Intelligence

JULY 10, 2024

Utilizamos Azure Data Factory para el proceso de extracción y ETL, el cual genera un data lake con toda la información consolidada almacenándose en un data warehouse basado en tecnología SQL. (Epsilon) y datos en Excel alojados en Sharepoint.

Data Lake 105

Data Lake Big Data Deep Learning Data Warehouse 105

Analytics Vidhya

FEBRUARY 17, 2023

Introduction Are you curious about the latest advancements in the data tech industry? Perhaps you’re hoping to advance your career or transition into this field. In that case, we invite you to check out DataHour, a series of webinars led by experts in the field.

Analytics 319

Analytics Data Warehouse Deep Learning Machine Learning 319

Laminar Security

DECEMBER 13, 2023

They offer a comprehensive solution to enhance your cloud security posture and effectively manage your data. The primary focus of discovery is to find all the places where data exists and identify the assets it resides in. One trend is the increasing use of deep learning algorithms for these processes.

Data-driven 119

Data-driven Machine Learning Deep Learning Risk 119

AWS Big Data

NOVEMBER 15, 2023

With new capabilities for self-service and straightforward builder experiences, you can democratize data access for line of business users, analysts, scientists, and engineers. Hear also from Adidas, GlobalFoundries, and University of California, Irvine.

Data Lake 72

Data Lake Data Warehouse B2B Deep Learning 72

O'Reilly on Data

SEPTEMBER 11, 2019

Deep learning,” for example, fell year over year to No. Increasingly, the term “data engineering” is synonymous with the practice of creating data pipelines, usually by hand. In quite another respect, however, modern data engineering has evolved to support a range of scenarios that simply were not imaginable 40 years ago.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

Domino Data Lab

OCTOBER 14, 2020

We needed an “evolvable architecture” which would work with the next deep learning framework or compute platform. Our scientists and teams are familiar with working in Spark on EMR and using data with our existing feature store and data warehouse. TFRecord and Parquet).

Experimentation 99

Experimentation Deep Learning Modeling Testing 99

CDW Research Hub

SEPTEMBER 15, 2020

Creating a modern data platform that is designed to support your current and future needs is critical in a data-driven organization. Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Easy Access with a Secure Foundation.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

Cloudera

JULY 15, 2019

At a time when machine learning, deep learning, and artificial intelligence capture an outsize share of media attention, jobs requiring SQL skills continue to vastly outnumber jobs requiring those more advanced skills.

Big Data 59

Big Data Deep Learning Data Warehouse Data-driven 59

Domino Data Lab

JULY 2, 2019

Scale the problem to handle complex data structures. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

Jen Stirrup

MAY 5, 2020

It has native integration with other data sources, such as SQL Data Warehouse, Azure Cosmos, database storage, and even Azure Blob Storage as well. When you’re using Big Data technologies, it’s often a concern about how well those are performing in terms of performance and robustness.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

IBM Big Data Hub

MAY 17, 2023

The data captured by the sensors and housed in the cloud flow into real-time monitoring for 24/7 visibility into your assets, enabling the Predictive Failure Model. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification.

Data Collection 76

Data Collection Visualization Data-driven Unstructured Data 76

CIO Business Intelligence

AUGUST 21, 2024

The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says. Adding smarter AI also adds risk, of course.

Risk 136

Risk Insurance Cost-Benefit Software 136

Cloudera

FEBRUARY 16, 2022

This allows data scientists, engineers and data management teams to have the right level of access to effectively perform their role. Given the complexity of some ML models, especially those based on Deep Learning (DL) Convolutional Neural Networks (CNNs), there are limits to interpretability.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Cloudera

MAY 22, 2018

It makes machine learning accessible and collaborative and easy to put into production. It enables a rich data warehouse experience, only with more fluidity and exploration of ad hoc questions. And can operate smoothly everywhere – in your data center or in your choice of cloud infrastructure.

Enterprise 40

Enterprise Recreation/Entertainment Data Warehouse Machine Learning 40

IBM Big Data Hub

FEBRUARY 19, 2024

A data monetization capability built on platform economics can reach its maximum potential when data is recognized as a product that is either built or powered by AI. At the enterprise level, business units identify the data they need from source systems and create data sets tailored exclusively to their specific solutions.

Cost-Benefit 63

Cost-Benefit Data-driven Optimization Marketing 63

KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

Data Science 159

Data Science Machine Learning Analytics Data Lake 159

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. Fortunately, data stores serve as secure data repositories and enable foundation models to scale in both terms of their size and their training data.

Modeling 55

Modeling Cost-Benefit Machine Learning Data Lake 55

Cloudera

SEPTEMBER 12, 2018

AbbVie, one of the world’s largest global research and development pharmaceutical companies, established a big data platform to provide end-to-end operations visibility, agility, and responsiveness. Modern Data Warehousing: Barclays (nominated together with BlueData ). IQVIA is re-envisioning healthcare using a data-driven approach.

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”). Automatic sampling to test transformation. Scheduling. Target Matching.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Domino Data Lab

JULY 22, 2019

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

OCTOBER 16, 2023

Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection. The platform has three powerful components: the watsonx.ai

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. We keep feeding the monster data.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

AWS Big Data

OCTOBER 25, 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. Amazon Redshift’s advanced Query Optimizer is a crucial part of that leading performance.

Statistics 90

Statistics Data Warehouse Metadata Data Lake 90

CIO Business Intelligence

MARCH 13, 2025

Introducing business intelligence required a great deal of change management work, because from a data use that wasnt very sophisticated and organized, and very do-it-yourself, we moved to a consistent and verified data warehouse, he says. The technical work of Sicca is typical of ICT in a distributed multinational.

Digital Transformation 117

Digital Transformation Insurance Management Deep Learning 117

CIO Business Intelligence

FEBRUARY 24, 2025

Lintroduzione della business intelligence (prima con Board e poi con Power BI) ha richiesto un grande lavoro di change management, perch da una fruizione del dato poco sofisticata e organizzata e molto fai-da-te, siamo passati a un data warehouse consistente e verificato, riferisce Sicca.

Management 96

Management Digital Transformation Deep Learning Data Warehouse 96