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 57

Big Data Deep Learning Data Warehouse Data-driven 57

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 Optimization 84

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 53

Machine Learning Marketing Forecasting Modeling 53

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

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 84

Machine Learning Modeling Metadata Recreation/Entertainment 84

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 82

Data Warehouse Visualization Cost-Benefit Optimization 82

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 299

Analytics Data Warehouse Deep Learning Machine Learning 299

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 98

Data Warehouse Cost-Benefit Dashboards Optimization 98

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

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 158

Data Science Machine Learning Analytics Data Lake 158

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

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

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 111

Data Warehouse Cost-Benefit Machine Learning Modeling 111

O'Reilly on Data

OCTOBER 19, 2021

This introduces further requirements: The scale of operations is often two orders of magnitude larger than in the earlier data-centric environments. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 346

IT Testing Experimentation Software 346

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

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 74

Cost-Benefit Data-driven Optimization Marketing 74

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

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.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 62

Modeling Cost-Benefit Data Lake Machine Learning 62

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Production Monitoring Only.

Testing 307

Testing Machine Learning Consulting Data Quality 307

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 86

Data Collection Visualization Data-driven Unstructured Data 86

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

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 Machine Learning Data Science Data-driven 105

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 Modeling Data-driven 59

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 20

IoT Big Data Data Warehouse Uncertainty 20

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 67

Data Lake Data Warehouse B2B Deep Learning 67

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 IoT 137

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

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 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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 Modeling Deep Learning Testing 99