Our most comprehensive database of AI models, containing over 800 models that are state of the art, highly cited, or otherwise historically notable. It tracks key factors driving machine learning progress and includes over 300 training compute estimates.

The AI Powered Storage Market size was valued at USD 18.56 USD Billion in 2023 and is projected to reach USD 89.50 USD Billion by 2032, exhibiting a CAGR of 25.2 % during the forecast period. The AI-Powered Storage Market encompasses that part of the storage sector which incorporates AI-based technologies to optimize storage of data via implementation of advanced AI algorithms and knowledge base systems. These systems are self-governing and predictive due to the application of AI algorithms for data usage pattern analysis, memory storage determining, and data transfer automation. AI-driven storage systems are used because now they allow faster data temperature and cut the storage cost as well for the organization to protect the data. For example, the applications form a database of self-learning data tiering, self-learning data classification, and predictive maintenance of storage hardware. The market features include AI analytics for real-time monitoring and assessment of the state storage performance, machine learning algorithms for the detection and anticipation of abnormalities, and autonomous storage solutions that can self-optimize and heal themselves in response to the problem of AI diagnostics. With data being a critical component of numerous organizations, AI-extended storage solutions now become imperative in terms of optimally employing the storage infrastructure and also in making the data more valuable. Recent developments include: October 2023: Pure Storage, Inc., an advanced data storage technology and service provider, enhanced its Evergreen portfolio to pay for its customers’ rack space and power costs for Evergreen’s Flex subscriptions and One Storage-as-a-Service (STaaS). The company also expanded its Evergreen range with new zero data loss, no data migration, and power & space efficiency guarantees complemented by flexible upgrades and financing., July 2023: Lenovo launched a new range of innovative data management solutions through ThinkSystem DG and DM3010H Enterprise Storage Arrays. This launch would make it easier for organizations to enable the use of AI workloads and unlock value in their data., June 2023: Dropbox, a cloud storage provider, launched a suite of AI products designed to simplify knowledge work. To enhance productivity, streamline processes, and deliver a more personalized work experience for users, the company rolled out new products, such as Dropbox Dash and Dropbox AI., March 2023: NVIDIA announced the NVIDIA DGX Cloud, an AI supercomputing offering that provides enterprises with instant access to the software and infrastructure required to train advanced models of generative AI, storage, and other groundbreaking applications., December 2022: IBM announced that it added storage solution roadmaps and Red Hat partner groups to the IBM Storage business unit, which would bring consistency in data and application through cloud and on-premises infrastructures.. Key drivers for this market are: Rising Demand for Effective Security Solutions Among Organizations to Drive Market Growth. Potential restraints include: Lack of Experienced Professionals and Knowledge of AI Hardware to Hinder Market Expansion. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

AI-Driven Analytics Platform Market Outlook

The AI-driven analytics platform market size is projected to grow from $10 billion in 2023 to $45 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 18%. This growth is driven by increasing demand for advanced data analytics solutions across various industries to enhance decision-making processes and operational efficiencies.

One of the primary growth factors for the AI-driven analytics platform market is the exponential growth of data generated globally. With the proliferation of IoT devices, social media, and other digital platforms, the volume of data being created is unprecedented. Organizations are increasingly recognizing the value of this data, and AI-driven analytics platforms are becoming essential tools for extracting actionable insights from it. These platforms leverage machine learning and artificial intelligence technologies to analyze vast datasets quickly and accurately, providing a competitive advantage to businesses.

Another significant driver is the rising adoption of cloud computing. Cloud-based AI-driven analytics platforms offer several benefits, including scalability, flexibility, and cost-efficiency. They allow organizations to access advanced analytics capabilities without the need for significant upfront investments in hardware and software. Furthermore, cloud platforms facilitate real-time data processing and analysis, enabling businesses to make informed decisions promptly. The ease of integration with existing systems and the ability to handle large volumes of data make cloud-based solutions particularly attractive to enterprises of all sizes.

The growing emphasis on personalized customer experiences is also fueling market growth. In sectors such as retail, healthcare, and finance, companies are leveraging AI-driven analytics platforms to gain deeper insights into customer behavior and preferences. These insights enable businesses to tailor their products, services, and marketing strategies to individual customers, thereby enhancing customer satisfaction and loyalty. The ability to predict customer needs and provide personalized recommendations is becoming a key differentiator in today's competitive market landscape.

From a regional perspective, North America holds a significant share of the AI-driven analytics platform market, driven by the presence of major technology players and high adoption rates of advanced analytics solutions. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the rapid digitalization and increasing investments in AI and data analytics technologies by governments and enterprises in countries like China and India.

Component Analysis

The AI-driven analytics platform market is segmented by components into Software, Hardware, and Services. The software segment dominates the market, primarily due to the extensive use of AI algorithms and machine learning models that drive analytics capabilities. AI-driven software solutions are designed to process and analyze large datasets, providing insights that help organizations make data-driven decisions. They also offer predictive analytics, helping businesses anticipate future trends and behaviors, thereby optimizing operations and strategies. The continuous advancements in AI algorithms and the integration of sophisticated tools like natural language processing (NLP) and computer vision further bolster the software segment's growth.

Hardware components in AI-driven analytics platforms include servers, storage devices, and networking equipment necessary to support the deployment and operation of analytics software. While software is the primary driver of value, robust hardware infrastructure is essential to manage the computational demands of AI algorithms. High-performance computing (HPC) systems and graphics processing units (GPUs) are particularly vital for processing large volumes of data at high speeds. The hardware segment, though smaller than the software segment, is expected to grow steadily as organizations continue to invest in upgrading their IT infrastructure to support advanced analytics workloads.

The services segment includes various professional services such as consulting, implementation, training, and maintenance. These services are crucial for the successful deployment and operation of AI-driven analytics platforms. Consulting services help organizations identify their analytics needs and develop tailored solutions. Implementation services ensure that the analytics platforms are correct

As of June 2024, 71 percent of countries worldwide had data privacy legislation in place. Furthermore, nine percent had the legislation drafted. Overall, 15 percent of markets worldwide had no data privacy legislation yet, and five percent have not provided any data on such laws.

Allforce is a leading data intelligence company specializing in comprehensive audience targeting solutions. We maintain one of the most extensive and accurate databases of professional contact information, with a focus on delivering verified, actionable data that drives measurable marketing results for our clients.

Dataset Overview: Our US Human Resources Professional Contact Database provides access to 2.4 million verified HR professionals across 475,000 companies nationwide. This premium dataset is specifically curated for B2B marketers seeking to connect with decision-makers in the HR ecosystem.

Key Features & Benefits: 2.4M+ HR professionals across all specialties 475,000+ companies represented Segmented by HR function: Benefits, Payroll, Recruiting, Training, Compensation, and more Decision-maker level contacts included

Data Quality & Verification: LinkedIn URL verification for each contact Regular database updates and maintenance High deliverability rates (Email Safe certification) Active professional verification process

Multi-Channel Marketing Support: Email addresses (newsletter-safe, verified deliverable) Direct phone numbers for telemarketing Postal addresses for direct mail campaigns LinkedIn profile matching for social outreach Digital advertising - Programmatic audiences

Data Compliance & Safety: All data is collected and maintained in compliance with applicable privacy regulations. Our "Safe to Email" certification ensures subscribers have opted into professional communications, reducing bounce rates and compliance risks.

Industries Served: Healthcare, Technology, Manufacturing, Financial Services, Retail, Education, Government, and all major industry verticals with HR departments.

Transform your HR marketing strategy with verified, actionable contact data that delivers results.

This data submission is for Phase 2 of Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations, which focuses on multi-fluid (CO2 and brine) geothermal energy production and diurnal bulk energy storage in geologic settings that are suitable for geologic CO2 storage. This data submission includes all data used in the Geosphere Journal article by Buscheck et al (2016). All assumptions are discussed in that article.

Point-of-interest (POI) is defined as a physical entity (such as a business) in a geo location (point) which may be (of interest).

We strive to provide the most accurate, complete and up to date point of interest datasets for all countries of the world. The United Arab Emirates POI Dataset is one of our worldwide POI datasets with over 98% coverage.

This is our process flow:

Our machine learning systems continuously crawl for new POI data
Our geoparsing and geocoding calculates their geo locations
Our categorization systems cleanup and standardize the datasets
Our data pipeline API publishes the datasets on our data store

POI Data is in a constant flux - especially so during times of drastic change such as the Covid-19 pandemic.

Every minute worldwide on an average day over 200 businesses will move, over 600 new businesses will open their doors and over 400 businesses will cease to exist.

In today's interconnected world, of the approximately 200 million POIs worldwide, over 94% have a public online presence. As a new POI comes into existence its information will appear very quickly in location based social networks (LBSNs), other social media, pictures, websites, blogs, press releases. Soon after that, our state-of-the-art POI Information retrieval system will pick it up.

We offer our customers perpetual data licenses for any dataset representing this ever changing information, downloaded at any given point in time. This makes our company's licensing model unique in the current Data as a Service - DaaS Industry. Our customers don't have to delete our data after the expiration of a certain "Term", regardless of whether the data was purchased as a one time snapshot, or via a recurring payment plan on our data update pipeline.

The main differentiators between us vs the competition are our flexible licensing terms and our data freshness.

The core attribute coverage is as follows:

Poi Field Data Coverage (%) poi_name 100 brand 4 poi_tel 48 formatted_address 100 main_category 96 latitude 100 longitude 100 neighborhood 2 source_url 47 email 6 opening_hours 43

The data may be visualized on a map at https://store.poidata.xyz/ae and a data sample may be downloaded at https://store.poidata.xyz/datafiles/ae_sample.csv