In July 2024, global industrial production, excluding the United States, increased by 1.5 percent compared to the same time in the previous year, based on three month moving averages. This is compared to an increase of 0.2 percent in advanced economies (excluding the United States) for the same time period. The global industrial production collapsed after the outbreak of COVID-19, but increased steadily in the months after, peaking at 23 percent in June 2021. Industrial growth rate tracks the output production in the industrial sector.

CompanyData.com, powered by BoldData, is your global partner for high-quality, verified B2B company information. Our Japan company database includes 6,535,597 verified business records, sourced directly from official trade registers and government data, offering unmatched coverage of one of the world’s largest economies.

Each Japanese company profile contains comprehensive firmographic and structural data, including company name, registration number, corporate ID, legal form, business type (NACE or JSIC classification), size, revenue estimates, and employee count. Many records also feature contact information, such as emails, phone numbers, and names of key decision-makers, enabling precise and effective outreach.

Our Japan dataset is ideal for a wide range of use cases — from compliance, KYC, and AML checks, to B2B marketing, sales prospecting, market research, CRM data enrichment, and AI model training. Whether you're targeting tech firms in Tokyo or manufacturers in Osaka, our database supports smart, targeted growth.

We provide flexible data delivery options to fit your workflow — including custom-built lists, full database exports in Excel or CSV, real-time API access, and a convenient self-service platform. Need help optimizing your own data? Our enrichment and cleansing services can update and enhance your existing records using verified data from Japan.

With access to 6,535,597 verified companies worldwide, CompanyData.com helps you scale locally in Japan and globally across borders. Leverage our deep local data and global expertise to make confident, data-driven decisions that move your business forward.

Context

From GLOBAL 2000

Forbes’ 18th annual ranking of the world’s 2,000 largest public companies illustrates the magnitude of the global shutdowns and serves as a warning for more trouble ahead in the coming months.

Acknowledgements

Most companies on this year’s Global 2000 list have seen their market values drop considerably since last year, and woeful first-quarter earnings provide a painful insight into the impact of the Great Cessation. The past few months have been especially brutal for the airlines, which saw demand drop lower than after 9/11. American Airlines, for instance, fell from No. 372 on the list to 967th after losing a staggering $2.2 billion in its first quarter.

Not all companies are being negatively affected by the pandemic, however. The biggest players in e-commerce —including Amazon, Alibaba and Walmart—have all experienced growth thanks to the rise in online shopping. All three moved up on this year’s list.

On the financial front, the Industrial and Commercial Bank of China remained in the top spot for the eighth straight year with more than $4.3 trillion in assets. China’s “big four” state-owned banks all wound up in this year’s top 10. JPMorgan Chase is the largest U.S. company at No. 3, falling one spot from last year.

In other bright spots, the largest IPO of 2019, Saudi Aramco, debuted at No. 5 on the list, while Zoom and Slack (which both IPOed last year) have also been instant beneficiaries of the new work-from-home realities. Both companies made an inaugural appearance on the Global 2000—virtually overnight.

Techsalerator’s Sound and Audio Data for Denmark

Techsalerator’s Sound and Audio Data for Denmark provides a crucial and detailed collection of information for businesses, researchers, and developers in the sound and audio industry. This dataset offers comprehensive insights into audio technologies, sound engineering, and acoustic data across various sectors in Denmark, enabling innovation and informed decision-making.

For access to the full dataset, contact us at info@techsalerator.com or visit Techsalerator Contact Us.

Techsalerator’s Sound and Audio Data for Denmark

Techsalerator’s Sound and Audio Data for Denmark delivers an extensive analysis of sound and audio-related information across multiple industries. This dataset includes essential metrics, technical specifications, and real-world applications related to audio research, sound engineering, and acoustic technology.

Top 5 Key Data Fields

• Audio Frequency Ranges: Provides detailed data on frequency ranges captured in different environments, including urban, rural, and industrial settings.

• Acoustic Properties: Includes information on sound absorption, reflection, and transmission for various materials used in Danish architecture and product design.

• Environmental Noise Levels: Captures real-time and historical data on noise pollution levels across different regions in Denmark, aiding urban planning and noise reduction strategies.

• Speech and Voice Recognition Data: Offers high-quality datasets for speech processing applications, including Danish language accents, dialects, and background noise variations.

• Audio Equipment Market Insights: Provides market trends, sales data, and technical specifications of sound equipment, including microphones, speakers, and headphones in Denmark.

Top 5 Sound and Audio Trends in Denmark

• Sustainable Acoustics: Growing focus on eco-friendly soundproofing materials and sustainable audio solutions in construction and design.

• AI-Driven Sound Processing: Increased adoption of AI and machine learning for voice recognition, audio enhancement, and real-time noise reduction applications.

• 3D and Spatial Audio Technologies: Rising interest in immersive audio experiences, particularly in gaming, virtual reality (VR), and home entertainment systems.

• Smart Home Audio Systems: Expansion of smart speakers and integrated home audio solutions, enhancing user experiences with voice-activated controls.

• Hearing Aid and Assistive Audio Technologies: Advancements in hearing aid devices and assistive listening technologies to improve accessibility for individuals with hearing impairments.

Top 5 Companies Leading in Sound and Audio Innovation in Denmark

• Bang & Olufsen: A globally recognized brand known for high-end audio solutions, including speakers, headphones, and home entertainment systems.

• Oticon: A leader in hearing aid technology, pioneering advanced solutions for individuals with hearing impairments.

• Dynaudio: Specializes in high-fidelity loudspeakers for professional, home, and automotive audio applications.

• TC Electronic: Develops industry-leading audio processing tools, including studio effects and sound engineering equipment.

• Jabra: A top innovator in wireless audio solutions, including headsets, earbuds, and enterprise communication tools.

Accessing Techsalerator’s Sound and Audio Data

To obtain Techsalerator’s Sound and Audio Data for Denmark, contact info@techsalerator.com with your specific data requirements. We provide a customized quote based on the required data fields and records, with delivery available within 24 hours. Ongoing access and subscription options are also available.

Included Data Fields:

• Audio Frequency Ranges
• Acoustic Properties
• Environmental Noise Levels
• Speech and Voice Recognition Data
• Audio Equipment Market Insights
• Soundproofing and Acoustic Materials
• AI and Machine Learning in Audio Processing
• Hearing Aid and Assistive Technology Data
• Consumer Preferences in Audio Products
• Contact Information

For businesses, researchers, and developers, Techsalerator’s dataset is an essential resource for understanding and leveraging sound and audio trends in Denmark.

Cloud Computing Market Growth | Industry Analysis, Size & Forecast Report

Dataset updated: Jun 27, 2024

Dataset authored and provided by: Mordor Intelligence

License: https://www.mordorintelligence.com/privacy-policy

Time period covered: 2019 - 2029

Area covered: Global

Variables measured: CAGR, Market size, Market share analysis, Global trends, Industry forecast

Description: The Cloud Computing Market size is estimated at USD 0.68 trillion in 2024, and is expected to reach USD 1.44 trillion by 2029, growing at a CAGR of 16.40% during the forecast period (2024-2029).

Report Attribute

Quantitative Units: Revenue in USD Billion, Volumes in Units, Pricing in USD

Regions and Countries Covered:

Industry Segmentation Covered:

By Cloud Computing: IaaS, SaaS, PaaS

By End-User: IT and Telecom, BFSI, Retail and Consumer Goods, Manufacturing, Healthcare, Media and Entertainment

Market Players Covered: Amazon Web Services, Google LLC, Microsoft Corporation, Alibaba Cloud, and Salesforce

Introduction

This Punjabi Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of Punjabi speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 30 Hours of dual-channel call center conversations between native Punjabi speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

The Gross Domestic Product (GDP) in Iran was worth 436.91 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Iran represents 0.41 percent of the world economy. This dataset provides - Iran GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

➡️ You can choose from multiple data formats, delivery frequency options, and delivery methods;

➡️ You can select raw or clean and AI-enriched datasets;

➡️ Multiple APIs designed for effortless search and enrichment (accessible using a user-friendly self-service tool);

➡️ Fresh data: daily updates, easy change tracking with dedicated data fields, and a constant flow of new data;

➡️ You get all necessary resources for evaluating our data: a free consultation, a data sample, or free credits for testing our APIs.

Coresignal's employee data enables you to create and improve innovative data-driven solutions and extract actionable business insights. These datasets are popular among companies from different industries, including HR and sales technology and investment.

Employee Data use cases:

✅ Source best-fit talent for your recruitment needs

Coresignal's Employee Data can help source the best-fit talent for your recruitment needs by providing the most up-to-date information on qualified candidates globally.

✅ Fuel your lead generation pipeline

Enhance lead generation with 712M+ up-to-date employee records from the largest professional network. Our Employee Data can help you develop a qualified list of potential clients and enrich your own database.

✅ Analyze talent for investment opportunities

Employee Data can help you generate actionable signals and identify new investment opportunities earlier than competitors or perform deeper analysis of companies you're interested in.

➡️ Why 400+ data-powered businesses choose Coresignal:

1. Experienced data provider (in the market since 2016);
2. Exceptional client service;
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Techsalerator’s Business Technographic Data for Djibouti: Unlocking Insights into Djibouti's Technology Landscape

Techsalerator’s Business Technographic Data for Djibouti provides a comprehensive and detailed collection of information crucial for businesses, market analysts, and technology vendors looking to understand and engage with companies operating in Djibouti. This dataset offers an in-depth exploration of the technological landscape, capturing and categorizing data related to technology stacks, digital tools, and IT infrastructure within Djiboutian businesses.

Please reach out to us at info@techsalerator.com or visit Techsalerator Contact.

Top 5 Most Utilized Data Fields

Company Name: This field lists the names of companies being analyzed in Djibouti. Understanding the companies helps technology vendors target their solutions effectively and enables market analysts to evaluate technology adoption trends within specific businesses.

Technology Stack: This field details the technologies and software solutions a company utilizes, such as ERP systems, CRM software, and cloud services. Knowledge of a company’s technology stack is crucial for understanding its operational capabilities and technology needs.

Deployment Status: This field indicates whether the technology is currently in use, planned for deployment, or under evaluation. This status helps vendors gauge the level of interest and current adoption among businesses in Djibouti.

Industry Sector: This field identifies the industry sector in which the company operates, such as logistics, telecommunications, or trade. Segmenting by industry sector helps vendors tailor their offerings to specific market needs and trends within Djibouti.

Geographic Location: This field provides the geographic location of the company's headquarters or primary operations within Djibouti. This information is vital for regional market analysis and understanding local technology adoption patterns.

Top 5 Technology Trends in Djibouti

Mobile Technology and Telecommunications: Djibouti’s strategic location makes its telecommunications sector pivotal in regional connectivity. The country is seeing a rise in mobile technology and internet penetration, serving as a hub for East Africa.

Cybersecurity: As Djibouti’s economy becomes increasingly digital, companies are investing more in cybersecurity solutions to protect sensitive information and infrastructure, especially in sectors like finance and telecommunications.

Data Centers and Cloud Computing: Djibouti is positioning itself as a data hub for the region due to its connectivity infrastructure. Cloud computing adoption is rising, providing businesses with scalable and flexible IT solutions.

Renewable Energy Initiatives: With an emphasis on sustainable development, there is a growing interest in renewable energy technologies, particularly solar and wind, to support the country's energy needs and promote sustainability.

Digital Port and Logistics Technologies: As a major regional trade hub, Djibouti is investing in smart port technologies and digital logistics solutions to streamline operations and maintain its position as a key gateway for global trade.

Top 5 Companies with Notable Technographic Data in Djibouti

Djibouti Telecom: The primary telecommunications provider in Djibouti, Djibouti Telecom is driving innovation in mobile services, internet connectivity, and regional telecommunications infrastructure, including undersea cables.

Port of Djibouti: As a critical asset for international trade, the Port of Djibouti is investing in advanced digital logistics and port management technologies to enhance efficiency and remain competitive in the global market.

Electricité de Djibouti (EDD): Djibouti’s national electricity company is embracing renewable energy technologies, including solar and wind projects, as part of the country’s goal to diversify its energy sources and achieve greater sustainability.

Commercial Bank of Djibouti: The Commercial Bank of Djibouti is modernizing its operations by adopting digital banking platforms and investing in secure IT infrastructures to enhance financial services in the region.

Djibouti Free Zone: The Djibouti Free Zone is leveraging digital technologies to attract international investments, providing businesses with state-of-the-art logistics and communication solutions to facilitate global trade.

Accessing Techsalerator’s Business Technographic Data

If you’re interested in obtaining Techsalerator’s Business Technographic Data for Djibouti, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide a customized quote based on the number of data fields and records you need, with the dataset available for delivery within 24 hours. Ongoing access options can ...

Overview This comprehensive dataset offers an in-depth look at the financial performance of five major entities within the coffee industry from 2014 to 2024 (up to May 8, 2024). Included are stock prices of Keurig Dr Pepper, Starbucks, J.M. Smucker, Luckin Coffee, and Nestlé, paired with the corresponding periodical commodity prices for coffee. This data facilitates robust analyses including time series analysis, correlation studies, volatility analysis, and Vector Autoregression (VAR) analysis.

Key Companies Profiled Keurig Dr Pepper (KDP) and J.M. Smucker: These companies are leaders in the North American coffee market, known for their extensive portfolios of coffee products. Their data can provide insights into market strategies and financial health in response to fluctuating coffee prices. Starbucks: As a global leader in coffee retail, Starbucks' data reflects trends in consumer coffee consumption worldwide, offering a unique view of the retail sector's dynamics. Luckin Coffee: Representing a rapidly growing market, Luckin Coffee's data highlights the expansion and consumer trends within the Chinese coffee market. Nestlé: This global giant provides a broader perspective on how multinational food and beverage companies adapt to global commodity price changes, with a particular focus on coffee.

Applications of the Dataset This dataset is ideal for researchers, economists, and data scientists interested in: Market Trend Analysis: Understand how global events and market forces influence coffee prices and, in turn, affect company stocks. Consumer Behaviour Studies: Analyse consumption patterns across different regions, especially with a focus on the burgeoning Asian markets. Risk Management and Forecasting: Develop models to predict future trends and prepare risk management strategies for companies within the food and beverage sector. Sustainability Studies: Explore how price volatility relates to environmental factors and sustainability initiatives.

The data in this dataset were collected in the result of the survey of Latvian society (2021) aimed at identifying high-value data set for Latvia, i.e. data sets that, in the view of Latvian society, could create the value for the Latvian economy and society.
The survey is created for both individuals and businesses.
It being made public both to act as supplementary data for "Towards enrichment of the open government data: a stakeholder-centered determination of High-Value Data sets for Latvia" paper (author: Anastasija Nikiforova, University of Latvia) and in order for other researchers to use these data in their own work.

The survey was distributed among Latvian citizens and organisations. The structure of the survey is available in the supplementary file available (see Survey_HighValueDataSets.odt)

***Description of the data in this data set: structure of the survey and pre-defined answers (if any)***
1. Have you ever used open (government) data? - {(1) yes, once; (2) yes, there has been a little experience; (3) yes, continuously, (4) no, it wasn’t needed for me; (5) no, have tried but has failed}
2. How would you assess the value of open govenment data that are currently available for your personal use or your business? - 5-point Likert scale, where 1 – any to 5 – very high
3. If you ever used the open (government) data, what was the purpose of using them? - {(1) Have not had to use; (2) to identify the situation for an object or ab event (e.g. Covid-19 current state); (3) data-driven decision-making; (4) for the enrichment of my data, i.e. by supplementing them; (5) for better understanding of decisions of the government; (6) awareness of governments’ actions (increasing transparency); (7) forecasting (e.g. trendings etc.); (8) for developing data-driven solutions that use only the open data; (9) for developing data-driven solutions, using open data as a supplement to existing data; (10) for training and education purposes; (11) for entertainment; (12) other (open-ended question)
4. What category(ies) of “high value datasets” is, in you opinion, able to create added value for society or the economy? {(1)Geospatial data; (2) Earth observation and environment; (3) Meteorological; (4) Statistics; (5) Companies and company ownership; (6) Mobility}
5. To what extent do you think the current data catalogue of Latvia’s Open data portal corresponds to the needs of data users/ consumers? - 10-point Likert scale, where 1 – no data are useful, but 10 – fully correspond, i.e. all potentially valuable datasets are available
6. Which of the current data categories in Latvia’s open data portals, in you opinion, most corresponds to the “high value dataset”? - {(1)Foreign affairs; (2) business econonmy; (3) energy; (4) citizens and society; (5) education and sport; (6) culture; (7) regions and municipalities; (8) justice, internal affairs and security; (9) transports; (10) public administration; (11) health; (12) environment; (13) agriculture, food and forestry; (14) science and technologies}
7. Which of them form your TOP-3? - {(1)Foreign affairs; (2) business econonmy; (3) energy; (4) citizens and society; (5) education and sport; (6) culture; (7) regions and municipalities; (8) justice, internal affairs and security; (9) transports; (10) public administration; (11) health; (12) environment; (13) agriculture, food and forestry; (14) science and technologies}
8. How would you assess the value of the following data categories?
8.1. sensor data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable
8.2. real-time data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable
8.3. geospatial data - 5-point Likert scale, where 1 – not needed to 5 – highly valuable
9. What would be these datasets? I.e. what (sub)topic could these data be associated with? - open-ended question
10. Which of the data sets currently available could be valauble and useful for society and businesses? - open-ended question
11. Which of the data sets currently NOT available in Latvia’s open data portal could, in your opinion, be valauble and useful for society and businesses? - open-ended question
12. How did you define them? - {(1)Subjective opinion; (2) experience with data; (3) filtering out the most popular datasets, i.e. basing the on public opinion; (4) other (open-ended question)}
13. How high could be the value of these data sets value for you or your business? - 5-point Likert scale, where 1 – not valuable, 5 – highly valuable
14. Do you represent any company/ organization (are you working anywhere)? (if “yes”, please, fill out the survey twice, i.e. as an individual user AND a company representative) - {yes; no; I am an individual data user; other (open-ended)}
15. What industry/ sector does your company/ organization belong to? (if you do not work at the moment, please, choose the last option) - {Information and communication services; Financial and ansurance activities; Accommodation and catering services; Education; Real estate operations; Wholesale and retail trade; repair of motor vehicles and motorcycles; transport and storage; construction; water supply; waste water; waste management and recovery; electricity, gas supple, heating and air conditioning; manufacturing industry; mining and quarrying; agriculture, forestry and fisheries professional, scientific and technical services; operation of administrative and service services; public administration and defence; compulsory social insurance; health and social care; art, entertainment and recreation; activities of households as employers;; CSO/NGO; Iam not a representative of any company
16. To which category does your company/ organization belong to in terms of its size? - {small; medium; large; self-employeed; I am not a representative of any company}
17. What is the age group that you belong to? (if you are an individual user, not a company representative) - {11..15, 16..20, 21..25, 26..30, 31..35, 36..40, 41..45, 46+, “do not want to reveal”}
18. Please, indicate your education or a scientific degree that corresponds most to you? (if you are an individual user, not a company representative) - {master degree; bachelor’s degree; Dr. and/ or PhD; student (bachelor level); student (master level); doctoral candidate; pupil; do not want to reveal these data}

***Format of the file***
.xls, .csv (for the first spreadsheet only), .odt

***Licenses or restrictions***
CC-BY

The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027.

What is Big data?

Big data is a term that refers to the kind of data sets that are too large or too complex for traditional data processing applications. It is defined as having one or some of the following characteristics: high volume, high velocity or high variety. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets.

Big data analytics

Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate new business insights. The global big data and business analytics market was valued at 169 billion U.S. dollars in 2018 and is expected to grow to 274 billion U.S. dollars in 2022. As of November 2018, 45 percent of professionals in the market research industry reportedly used big data analytics as a research method.

This statistic shows the ranking of the global top 10 biotech and pharmaceutical companies worldwide, based on revenue. The values are based on a 2025 database. U.S. pharmaceutical company Pfizer was ranked first, with a total revenue of around ** billion U.S. dollars. Biotech and pharmaceutical companiesPharmaceutical companies are best known for manufacturing pharmaceutical drugs. These drugs have the aim to diagnose, to cure, to treat, or to prevent diseases. The pharmaceutical sector represents a huge industry, with the global pharmaceutical market being worth around *** trillion U.S. dollars. The best known top global pharmaceutical players are Pfizer, Merck, and Johnson & Johnson from the U.S., Novartis and Roche from Switzerland, Sanofi from France, etc. Most of these companies are involved not only in pure pharmaceutical business, but also manufacture medical technology and consumer health products, vaccines, etc. There are both pure play biotechnology companies and pharmaceutical companies which among other products also produce biotech products within their biotechnological divisions. Most of the leading global pharmaceutical companies have biopharmaceutical divisions. Although not a pure play biotech firm, Roche from Switzerland is among the companies with the largest revenues from biotechnology products worldwide. In contrast, California-based company Amgen was one of the world’s first large pure play biotech companies. Biotech companies use biotechnology to generate their products, most often medical drugs or agricultural genetic engineering. The latter segment is dominated by companies like Bayer CropScience and Syngenta. The United Nations Convention on Biological Diversity defines biotechnology as follows: "Any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use." In fact, biotechnology is thousands of years old, used in agriculture, food manufacturing and medicine.

The Gross Domestic Product (GDP) in Nigeria was worth 187.76 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Nigeria represents 0.18 percent of the world economy. This dataset provides the latest reported value for - Nigeria GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

As of June 2024, the most popular database management system (DBMS) worldwide was Oracle, with a ranking score of *******; MySQL and Microsoft SQL server rounded out the top three. Although the database management industry contains some of the largest companies in the tech industry, such as Microsoft, Oracle and IBM, a number of free and open-source DBMSs such as PostgreSQL and MariaDB remain competitive. Database Management Systems As the name implies, DBMSs provide a platform through which developers can organize, update, and control large databases. Given the business world’s growing focus on big data and data analytics, knowledge of SQL programming languages has become an important asset for software developers around the world, and database management skills are seen as highly desirable. In addition to providing developers with the tools needed to operate databases, DBMS are also integral to the way that consumers access information through applications, which further illustrates the importance of the software.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

CompanyData.com, powered by BoldData, delivers high-quality, verified B2B company information from official trade registers around the world. Our India company database includes 32,468,995 verified business records, giving you powerful insight into one of the fastest-growing economies on the planet.

Each company profile is rich with firmographic data, including company name, CIN (Corporate Identification Number), registration number, legal status, industry classification (NIC codes), revenue range, and employee size. Many records are enhanced with contact details such as email addresses, phone numbers, and names of key decision-makers, supporting direct outreach and smarter segmentation.

Our India dataset is designed for a wide range of business applications — from KYC and AML compliance, due diligence, and regulatory checks, to B2B sales, lead generation, marketing campaigns, CRM enrichment, and AI model training. Whether you’re targeting local startups or large enterprises, our data helps you connect with the right businesses at the right time.

Delivery is flexible to suit your needs. Choose from customized lists, full databases in Excel or CSV, access via our real-time API, or our intuitive self-service platform. We also offer data enrichment and cleansing services to refresh and improve your existing datasets with accurate, up-to-date company information from India.

With access to 32,468,995 verified companies across more than 200 countries, CompanyData.com helps businesses grow confidently — in India and beyond. Rely on our precise, structured data to fuel your strategies and scale with speed and accuracy.

Introduction

Presenting the UK English Scripted Monologue Speech Dataset for the Telecom Domain, a purpose-built dataset created to accelerate the development of English speech recognition and voice AI models specifically tailored for the telecommunications industry.

Speech Data

This dataset includes over 6,000 high-quality scripted prompt recordings in UK English, representing real-world telecom customer service scenarios. It’s designed to support the training of speech-based AI systems used in call centers, virtual agents, and voice-powered support tools.

Topic Coverage

The dataset reflects a wide variety of common telecom customer interactions, including:

Contextual Depth

To maximize contextual richness, prompts include:

Transcription

Each audio file is paired with an accurate, verbatim transcription for precise model training:

Metadata

Detailed metadata is included to

Introduction

This Hindi Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of Hindi speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 30 Hours of dual-channel call center conversations between native Hindi speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

The Gross Domestic Product (GDP) in Pakistan was worth 373.07 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Pakistan represents 0.35 percent of the world economy. This dataset provides - Pakistan GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.