Smart Data Collective

MARCH 16, 2022

Companies spent nearly $11 billion on financial analytics in 2020. A large portion of this market is driven by investment companies and mutual funds. This is because accurate data about consumer movement can help you know about consumer trends and corresponding market movements.

Big Data 103

Big Data Deep Learning Finance Data-driven 103

bridgei2i

FEBRUARY 21, 2020

In fact, statistics from Maryville University on Business Data Analytics predict that the US market will be valued at more than $95 billion by the end of this year. With that in mind, here are the latest growth drivers, trends, and developments that will likely shape the world of business data analytics in 2020: 1.

IoT 83

IoT Analytics Deep Learning B2B 83

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends. billion by 2030.

Enterprise 104

Enterprise Interactive Data-driven Key Performance Indicator 104

IBM Big Data Hub

JULY 11, 2023

According to Statista , the artificial intelligence (AI) healthcare market, valued at $11 billion in 2021, is projected to be worth $187 billion in 2030. One use case example is out of the University of Hawaii, where a research team found that deploying deep learning AI technology can improve breast cancer risk prediction.

Deep Learning 58

Deep Learning Cost-Benefit Insurance Machine Learning 58

IBM Big Data Hub

MAY 17, 2024

Early iterations of e-commerce used traditional AI largely to create dynamic marketing campaigns , improve the online shopping experience, or triage customer requests. However, generative AI can create value by generating multilingual support and personalized marketing content.

B2B 70

B2B Interactive Optimization Forecasting 70

datapine

AUGUST 14, 2019

Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights. But being an inquisitive Sherlock Holmes of data is no easy task.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

JUNE 22, 2023

Organizations are also seeking more established IT skills such as predictive analytics, natural language processing, deep learning, and machine learning, says Mike Hendrickson, VP of tech and dev products at Skillsoft.

IT 105

IT Machine Learning Deep Learning Technology 105

Domino Data Lab

JULY 28, 2021

To model anything highly technical and computationally — machine learning, deep learning, big data analytics, and natural-language processing, to name a few — code-based tools (such as R and Python) are usually preferred. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

JULY 6, 2023

One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. An e-commerce conglomeration uses predictive analytics in its recommendation engine. Python is the most common programming language used in machine learning.

Machine Learning 58

Machine Learning Data Science Statistics Deep Learning 58

Smart Data Collective

MARCH 22, 2019

Marketers have utilized deep learning technology to get a better understanding of their customers, so they can refine their creative and targeting strategies. This is especially important for marketers trying to reach customers in other regions of the world, due to the logistics of getting the website to load quickly.

Big Data 45

Big Data Deep Learning Machine Learning Marketing 45

IBM Big Data Hub

FEBRUARY 14, 2024

Not only will this help scale the AOT tech across markets, but it will also help tackle integrations including additional languages, dialects and menu variations. Clean up with predictive maintenance AI can be used for predictive maintenance by analyzing data directly from machinery to identify problems and flag required maintenance.

Cost-Benefit 87

Cost-Benefit Insurance Unstructured Data Machine Learning 87

Cloudera

SEPTEMBER 12, 2018

Voya Financial prevented millions of dollars of fraudulent transactions by deploying predictive analytic capabilities on Cloudera. AbbVie’s platform uses analytics and machine learning, including natural language processing, deep learning, and unsupervised learning, to proactively identify issues and opportunities.

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

O'Reilly on Data

MARCH 18, 2020

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. Two functional areas—marketing/advertising/PR and operations/facilities/fleet management—see usage share of about 20%.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

BizAcuity

MARCH 31, 2022

By 2025, AI will be the top category driving infrastructure decisions, due to the maturation of the AI market, resulting in a tenfold growth in compute requirements. 85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: AI in Marketing. Source: Gartner Research).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

AWS Big Data

MAY 16, 2024

In essence, insights derived from H3-based analytics empower businesses to make informed decisions, swiftly adapt to market changes, and elevate customer satisfaction through efficient deliveries. Ioanna Tsalouchidou is a software development engineer in the Amazon Redshift team focusing on spatial analytics and query processing.

Data Warehouse 103

Data Warehouse Visualization Cost-Benefit Optimization 103

IBM Big Data Hub

DECEMBER 20, 2023

Supervised learning is commonly used for risk assessment, image recognition, predictive analytics and fraud detection, and comprises several types of algorithms. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g., temperature, salary).

Machine Learning 80

Machine Learning Modeling Deep Learning Predictive Modeling 80

CIO Business Intelligence

APRIL 15, 2022

Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus. The marketing department could then target high-scoring customers with coupons and marketing messages.

Analytics 145

Analytics Machine Learning Insurance Testing 145

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 platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

Domino Data Lab

JULY 22, 2019

You know, case in point, if you were to talk about predictive analytics 20 years ago, the main people in the field would have laughed you out of the room. Predictive analytics, yeah, not so much.” Now, Google is spending what, 10 figures marketing TensorFlow? They would’ve said, “You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Ontotext

FEBRUARY 26, 2024

Ontotext’s Relation and Event Detector (RED) is designed to assess and analyze the impact of market-moving events. A risk and opportunity event refers to an occurrence that may positively or negatively impact the stock market performance of a company or industry sector. and “What is the financial impact?”.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

datapine

NOVEMBER 19, 2019

If you don’t pay attention to new changes or keep up the pace, it’s easy to fall behind the times (and the market) while other companies beat you to the punch. Get the inside scoop and learn all the new buzzwords in tech for 2020! Visual analytics: Around three million images are uploaded to social media every single day.

Technology 279

Technology Internet of Things IT IoT 279

Smart Data Collective

MAY 19, 2021

Many energy conglomerates have started embracing data analytics to expand their markets, respond to new trends, streamline operations and bolster efficiency. They are exploring the wonders of AI and predictive analytics to drive these changes. The clean energy sector has not been untouched by the big data revolution.

Data Analytics 89

Data Analytics Analytics Big Data Predictive Analytics 89