CIO Business Intelligence

MARCH 13, 2024

Altrettanto importante (e forse più trascurata) è la questione dei big data che servono per addestrare i modelli e il costo connesso. L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%).

Machine Learning 98

Machine Learning Deep Learning Big Data Testing 98

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It culminates with a capstone project that requires creating a machine learning model.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

JUNE 7, 2022

In business analytics, this is the purview of business intelligence (BI). Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance. In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 125

Data Analytics Diagnostic Analytics Management Analytics 125

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

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. And most importantly, what can this do for your business? So, what do these terms really mean?

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

CIO Business Intelligence

FEBRUARY 22, 2024

Since its creation over five years ago, the Digital Hub has included a team of experts in innovation, technologies, and trends — such as IoT, big data, AI, drones, 3D printing, or advances in customer experience — who work in concert with other business units to identify and execute new opportunities.

IT 92

IT Digital Transformation IoT Cost-Benefit 92

CIO Business Intelligence

JUNE 21, 2022

Real-time big data analytics, deep learning, and modeling and simulation are newer uses of HPC that governments are embracing for a variety of applications. Big data analytics is being used to uncover crimes. Ready to evolve your analytics strategy or improve your data quality?

Deep Learning 92

Deep Learning Big Data ROI Software 92

CIO Business Intelligence

JANUARY 13, 2023

Software-based advanced analytics — including big data, machine learning, behavior analytics, deep learning and, eventually, artificial intelligence. In my view, there are two key interrelated developments that can shift the cybersecurity paradigm. They are: Innovations in automation.

Software 128

Software Machine Learning Behavioral Analytics Risk 128

CIO Business Intelligence

JUNE 1, 2022

These supercomputers power exciting innovations in deep learning, disease control, and physics—think bionic eyes, DNA sequencing for infectious disease research, and the study of time crystals. . CSIRO’s Bracewell Delivers Deep Learning, Bionic Vision. Ready to evolve your analytics strategy or improve your data quality?

Deep Learning 83

Deep Learning Snapshot Optimization Data Quality 83

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 53

Data mining Machine Learning Deep Learning Marketing 53

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. from 2022 to 2028.

Predictive Analytics 136

Predictive Analytics Analytics Predictive Modeling Forecasting 136

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 78

Marketing Technology Advertising ROI 78

Cloudera

SEPTEMBER 12, 2018

It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Enterprise Machine Learning: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Generally, companies will store data in local databases or public clouds. Programming Languages.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

CIO Business Intelligence

MAY 27, 2024

“Contrariamente alla tradizionale visione dell’IA come sistema autonomo, l’augmented intelligence usa il machine learning e il deep learning per fornire alle persone dei dati su cui basare le decisioni e agire”, si legge nel “Digital Reality White Paper” dell’IEEE [in inglese] , associazione professionale dell’IT.

Visualization 52

Visualization Data-driven Deep Learning Digital Transformation 52

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is now able to automatically create and maintain materialized views and then transparently rewrite queries to use the materialized views using the machine-learned automated materialized view autonomics feature in Amazon Redshift. Aamer Shah is a Senior Engineer in the Amazon Redshift Service team.

Data Warehouse 95

Data Warehouse Cost-Benefit Dashboards Optimization 95

Smart Data Collective

SEPTEMBER 9, 2019

. Artificial intelligence is upending the financial management industry in spectacular ways. The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. Will deep learning and AI finally make technical analysis a mainstream financial management strategy?

Deep Learning 65

Deep Learning Forecasting Machine Learning Strategy 65

Cloudera

NOVEMBER 19, 2020

In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors. Fraudulent Activity Detection.

Machine Learning 119

Machine Learning Data-driven Modeling Deep Learning 119

datapine

NOVEMBER 19, 2019

In business intelligence, we are evolving from static reports on what has already happened to proactive analytics with a live dashboard assisting businesses with more accurate reporting. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI technology is quickly proving to be a critical component of business intelligence within organizations across industries.

Machine Learning 71

Machine Learning Manufacturing Cost-Benefit Deep Learning 71

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 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. Ludwig is a TensorFlow-based toolbox that aims to allow people to use machine learning during their data work without having extensive prior knowledge. In short, it makes big data analysis more accessible.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. But few organizations have made the strategic shift to managing “data as a product.”

Strategy 104

Strategy Cost-Benefit Data-driven Measurement 104

Alation

APRIL 14, 2022

A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. It’s More Important to Know What Your Data Means Than Where It Is. On-premises business intelligence and databases. Cloud governance.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year.

Machine Learning 244

Machine Learning Technology Deep Learning Data Science 244

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

CIO Business Intelligence

JANUARY 20, 2023

Here’s what to consider: Ingesting the data : To be able to analyze more data at greater speeds, organizations need faster processing via high-powered servers and the right chips for AI—whether CPUs or GPUs. Protecting the data : Cyber threats are everywhere—at the edge, on-premises and across cloud providers.

Analytics 125

Analytics Key Performance Indicator Unstructured Data IoT 125