CIO Business Intelligence

MARCH 14, 2022

Thus, the storage architecture can be optimized for performance and scale. In addition, Aerospike’s “shared nothing” architecture supports algorithmic cluster management combined with global cross-data center replication to support complex filtering, dynamic routing, and self-healing capabilities. Just starting out with analytics?

Data Processing 109

Data Processing Optimization Deep Learning Software 109

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. Just starting out with analytics?

Unstructured Data 87

Unstructured Data Deep Learning Insurance Interactive 87

CIO Business Intelligence

APRIL 11, 2022

And it saves money for the City services as garbage collection rounds can be optimized. For example, smart waste is an essential part of the IoT-UK program, backed by a £40m investment from the British government to increase the adoption of high-quality IoT technologies across the private and the public sectors.

IoT 145

IoT Measurement Cost-Benefit Technology 145

CIO Business Intelligence

APRIL 6, 2022

For example, on the front end, healthcare organizations can optimize secure access to clinical data to improve the level of care provided and reduce patient wait times. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Data mining 67

Data mining Deep Learning Insurance Digital Transformation 67

CIO Business Intelligence

JUNE 2, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Machine Learning 134

Machine Learning Deep Learning Data Quality Strategy 134

CIO Business Intelligence

APRIL 25, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Machine Learning 125

Machine Learning Enterprise Deep Learning Cost-Benefit 125

CIO Business Intelligence

JUNE 13, 2022

Some conversational AI implementations rely heavily on ML tools that incorporate neural networks and deep learning techniques. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Just starting out with analytics?

Data Processing 86

Data Processing Deep Learning Insurance Cost-Benefit 86

IBM Big Data Hub

NOVEMBER 29, 2023

They are already identifying and exploring several real-life use cases for synthetic data, such as: Generating synthetic tabular data to increase sample size and edge cases. You can combine this data with real datasets to improve AI model training and predictive accuracy.

Metrics 86

Metrics Machine Learning Risk Statistics 86

CIO Business Intelligence

APRIL 26, 2022

Ever increasing advances in technology and continuous process optimization techniques have helped ensure that the global supply chain runs efficiently, turning raw materials into products that make their way to physical stores and ecommerce warehouses. Ready to evolve your analytics strategy or improve your data quality?

Manufacturing 91

Manufacturing Optimization Metrics Deep Learning 91

CIO Business Intelligence

JUNE 1, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Manufacturing 98

Manufacturing Digital Transformation Predictive Analytics Strategy 98

CIO Business Intelligence

JANUARY 20, 2023

Emerging from the pandemic, Montage Health leaders aimed to continue and optimize telehealth, telemedicine, virtual care, and virtual visits. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Technology 56

Technology Cost-Benefit Deep Learning Modeling 56

CIO Business Intelligence

APRIL 11, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Deep Learning 56

Deep Learning Strategy Risk Data Quality 56

CIO Business Intelligence

JUNE 2, 2022

For optimizing existing resources, Eni uses HPC5 to model, study, and ultimately improve refinement operations. . To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Just starting out with analytics?

Informatics 85

Informatics Modeling Testing Technology 85

CIO Business Intelligence

JANUARY 4, 2023

Of course, data center challenges are also driving demand for these alternatives. Workflow Optimization from Edge to Core/Cloud and Back : Integration with edge devices as well as integration with different HPC systems is currently designed in-house or otherwise customized. Just starting out with analytics?

Cost-Benefit 56

Cost-Benefit Machine Learning Modeling Uncertainty 56

CIO Business Intelligence

APRIL 4, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Technology 52

Technology Deep Learning Cost-Benefit Data Quality 52

CIO Business Intelligence

MAY 16, 2022

For example, concession stand and retail merchandise shop owners can use occupancy conditions to make more effective decisions on deploying their staff and optimizing inventory, especially for items with a limited shelf life. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Recreation/Entertainment 80

Recreation/Entertainment Broadcasting Cost-Benefit Advertising 80

Cloudera

NOVEMBER 15, 2021

Here we briefly describe some of the challenges that data poses to AI. Data annotation. Abundance of data has been one of the main facilitators of the AI boom of the last decade. Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful. Data curation.

Unstructured Data 86

Unstructured Data Recreation/Entertainment Structured Data Reporting 86

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Our Top Data Science Tools.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Domino Data Lab

MARCH 3, 2019

O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

O'Reilly on Data

MARCH 31, 2020

At measurement-obsessed companies, every part of their product experience is quantified and adjusted to optimize user experience. These companies eventually moved beyond using data to inform product design decisions. If you don’t understand your data intimately, you will have trouble knowing what’s feasible and what isn’t.

Management 332

Management Machine Learning Experimentation Metrics 332

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. Data breaks.

Testing 307

Testing Machine Learning Consulting Data Quality 307

CIO Business Intelligence

APRIL 1, 2022

Better decision-making isn’t always about deciding whether A or B is the optimal choice. BSI’s solutions make use of a wide range of Dell Technologies, including accelerated-optimized, high-density Dell PowerEdge servers. Ready to evolve your analytics strategy or improve your data quality? AI for Better Decision-Making.

Data-driven 83

Data-driven Deep Learning Risk Optimization 83

Domino Data Lab

JUNE 23, 2019

It used deep learning to build an automated question answering system and a knowledge base based on that information. It is like the Google knowledge graph with all those smart, intelligent cards and the ability to create your own cards out of your own data.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

IBM Big Data Hub

AUGUST 1, 2022

2000 Deep Learning: . Deep learning attempts to mimic the human brain and helps with enabling systems in clustering data and making predictions with incredible accuracy. It has raised the bar for image recognition and even learning patterns for unstructured data. .

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

Modeling 193

Modeling Machine Learning Testing Metrics 193

DataRobot Blog

DECEMBER 20, 2022

In this context, an augmented intelligence approach around the data will be increasingly more critical for asset managers, investors, and real estate developers to ensure a better understanding of the real estate assets and take better decisions aimed at optimizing both the Net Asset Value and the Net Operating Income.

Management 59

Management Machine Learning Optimization Modeling 59

CIO Business Intelligence

APRIL 12, 2022

Computer vision is helping to reshape the transportation industry at every level from streamlining the passenger experience to preemptive fleet maintenance to fuel optimization. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

IT 67

IT Cost-Benefit IoT Machine Learning 67

Domino Data Lab

JULY 22, 2019

We’ve got this complex landscape, tons of data sharing, an economy of data, external data, tons of mobile devices. and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. You can take TensorFlow.js You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

JANUARY 31, 2023

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Deep Learning 97

Deep Learning Cost-Benefit Manufacturing Data-driven 97

CIO Business Intelligence

MARCH 22, 2022

To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Analytics 94

Analytics Key Performance Indicator Data Warehouse Data-driven 94

CIO Business Intelligence

JANUARY 20, 2023

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. Though experts agree on the difficulty of deploying new platforms across an enterprise, there are options for optimizing the value of AI and analytics projects. [2]

Analytics 128

Analytics Key Performance Indicator Unstructured Data IoT 128

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 133

Visualization Cost-Benefit Big Data Prescriptive Analytics 133