United States US: GDP: Growth: Gross Value Added: Services data was reported at 2.621 % in 2015. This records an increase from the previous number of 2.221 % for 2014. United States US: GDP: Growth: Gross Value Added: Services data is updated yearly, averaging 2.335 % from Dec 1998 (Median) to 2015, with 18 observations. The data reached an all-time high of 4.456 % in 1999 and a record low of -1.772 % in 2009. United States US: GDP: Growth: Gross Value Added: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Annual Growth Rate. Annual growth rate for value added in services based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

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Big Data Market Size 2025-2029

The big data market size is forecast to increase by USD 193.2 billion at a CAGR of 13.3% between 2024 and 2029.

The market is experiencing a significant rise due to the increasing volume of data being generated across industries. This data deluge is driving the need for advanced analytics and processing capabilities to gain valuable insights and make informed business decisions. A notable trend in this market is the rising adoption of blockchain solutions to enhance big data implementation. Blockchain's decentralized and secure nature offers an effective solution to address data security concerns, a growing challenge in the market. However, the increasing adoption of big data also brings forth new challenges. Data security issues persist as organizations grapple with protecting sensitive information from cyber threats and data breaches.
Companies must navigate these challenges by investing in robust security measures and implementing best practices to mitigate risks and maintain trust with their customers. To capitalize on the market opportunities and stay competitive, businesses must focus on harnessing the power of big data while addressing these challenges effectively. Deep learning frameworks and machine learning algorithms are transforming data science, from data literacy assessments to computer vision models.

What will be the Size of the Big Data Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In today's data-driven business landscape, the demand for advanced data management solutions continues to grow. Companies are investing in business intelligence dashboards and data analytics tools to gain insights from their data and make informed decisions. However, with this increased reliance on data comes the need for robust data governance policies and regular data compliance audits. Data visualization software enables businesses to effectively communicate complex data insights, while data engineering ensures data is accessible and processed in real-time. Data-driven product development and data architecture are essential for creating agile and responsive business strategies. Data management encompasses data accessibility standards, data privacy policies, and data quality metrics.
Data usability guidelines, prescriptive modeling, and predictive modeling are critical for deriving actionable insights from data. Data integrity checks and data agility assessments are crucial components of a data-driven business strategy. As data becomes an increasingly valuable asset, businesses must prioritize data security and privacy. Prescriptive and predictive modeling, data-driven marketing, and data culture surveys are key trends shaping the future of data-driven businesses. Data engineering, data management, and data accessibility standards are interconnected, with data privacy policies and data compliance audits ensuring regulatory compliance.
Data engineering and data architecture are crucial for ensuring data accessibility and enabling real-time data processing. The data market is dynamic and evolving, with businesses increasingly relying on data to drive growth and inform decision-making. Data engineering, data management, and data analytics tools are essential components of a data-driven business strategy, with trends such as data privacy, data security, and data storytelling shaping the future of data-driven businesses.

How is this Big Data Industry segmented?

The big data industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  On-premises
  Cloud-based
  Hybrid


Type

  Services
  Software


End-user

  BFSI
  Healthcare
  Retail and e-commerce
  IT and telecom
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

In the realm of big data, on-premise and cloud-based deployment models cater to varying business needs. On-premise deployment allows for complete control over hardware and software, making it an attractive option for some organizations. However, this model comes with a significant upfront investment and ongoing maintenance costs. In contrast, cloud-based deployment offers flexibility and scalability, with service providers handling infrastructure and maintenance. Yet, it introduces potential security risks, as data is accessed through multiple points and stored on external servers. Data

Quarter by quarter updates of the number of maps, charts and datasets made available to the public

We show that the conditional distribution of forecasted GDP growth depends on financial conditions in a panel of 11 advanced economies. Financial conditions have a larger effect on the lower 5th percentile of conditional growth—which we call growth-at-risk (GaR)—than the median. In addition, the term structure of GaR reflects that when initial financial conditions are loose, downside risks are lower in the near-term but increase in later quarters. This intertemporal tradeoff for loose financial conditions is amplified when credit-to-GDP growth is rapid. Using granular instrumental variables, we also provide evidence that the relationship from loose financial conditions to future downside risks is causal. Our results suggest that models of macrofinancial linkages should incorporate the endogeneity of higher-order moments to systematically account for downside risks to growth in the medium run.

The source forecast that, in 2024, business-to-business (B2B) marketing data spending in the United States will grow by *** percent to over *** billion U.S. dollars. The value was projected to increase by nearly **** percent in the following year and reach about **** billion dollars.

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The Global Population Growth Dataset provides a comprehensive record of population trends across various countries over multiple decades. It includes detailed information such as the country name, ISO3 country code, year-wise population data, population growth, and growth rate. This dataset is valuable for researchers, demographers, policymakers, and data analysts interested in studying population dynamics, demographic trends, and economic development.

Key features of the dataset:

✅ Covers multiple countries and regions worldwide
✅ Includes historical and recent population data
✅ Provides year-wise population growth and growth rate (%)
✅ Categorizes data by country and decade for better trend analysis

This dataset serves as a crucial resource for analyzing global population trends, understanding demographic shifts, and supporting socio-economic research and policy-making.

FILE INFORMATION

The dataset consists of structured records related to country-wise population data, compiled from official sources. Each file contains information on yearly population figures, growth trends, and country-specific data. The structured format makes it useful for researchers, economists, and data scientists studying demographic patterns and changes. The file type is CSV.

COLUMNS DESCRIPTION

• Country – The name of the country.
• ISO3 – The three-letter ISO code of the country.
• Year – The year corresponding to the population data, useful for trend analysis.
• Population – The total population of the country for the given year.
• Population Growth – The absolute increase in population compared to the previous year.
• Growth Rate (%) – The percentage change in population compared to the previous year.
• Decade – The decade classification (e.g., 1990s, 2000s) for grouping long-term trends.

Key information about United States New Orders Growth

• United States New Orders increased 3.2 % YoY in Jan 2025, compared with a drop of 0.9 % in the previous month
• US New Orders Growth data is updated monthly, available from Feb 1993 to Jan 2025, with an average YoY change of 3.8 %
• The data reached an all-time high of 39.3 % in Apr 2021 and a record low of -30.0 % in Apr 2009

This dataset provides values for GDP ANNUAL GROWTH reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Data Governance Market is Segmented by Component (Software, Services), Deployment (Cloud, On-Premise), Organization Size (Large Enterprises, Small and Medium Enterprises), Business Function (IT and Operations, Legal and Compliance, and More) Application (Compliance Management, Risk Management, and More), End-User Industry (BFSI, IT and Telecom, and More), Geography. The Market Forecasts are Provided in Terms of Value (USD).

Italy - Real GDP growth rate was 0.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Italy - Real GDP growth rate - last updated from the EUROSTAT on July of 2025. Historically, Italy - Real GDP growth rate reached a record high of 8.90% in December of 2021 and a record low of -8.90% in December of 2020.

Economic growth, quarterly in Sweden, March, 2025 The most recent value is -0.2 percent as of Q1 2025, a decline compared to the previous value of 0.5 percent. Historically, the average for Sweden from Q2 1993 to Q1 2025 is 0.56 percent. The minimum of -8.6 percent was recorded in Q2 2020, while the maximum of 5.8 percent was reached in Q3 2020. | TheGlobalEconomy.com

The Data Observability Market is Segmented by Component (Solutions [Platform, and More], Services [Professional Services, and More), Deployment Model (Public Cloud, Private Cloud, and More), End-User Industry (BFSI, IT and Telecom, and More), End-User Enterprise Size (Large Enterprises, and More), Data-Pipeline Type (Batch Processing, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Economic growth, quarterly in Germany, March, 2025 The most recent value is 0.4 percent as of Q1 2025, an increase compared to the previous value of -0.2 percent. Historically, the average for Germany from Q2 1991 to Q1 2025 is 0.3 percent. The minimum of -8.9 percent was recorded in Q2 2020, while the maximum of 8.7 percent was reached in Q3 2020. | TheGlobalEconomy.com

This dataset contains growth curve data of a series of E. coli cells carrying reduced genomes, in the media of LB (rich medium), MAA (M63 supplied with 20 amino acids) and M63 (minimal medium).The dataset consists of three .xlsx files accessible via MS Excel and open office formats. Each file contains experimental growth curve data by time in a series of tabs, each representing one strain with the tab name bearing n. Individual columns in a tab represent individual wells per strain. Each separate file corresponds to one of the growth media above: LB, MAA, and M63, which represent the rich, supplementary, and poor growth conditions, respectively.Measurement data are provided at 30 minute or one hour intervals for all growth media and groupings.KHK growth curves_LB.xlsx - E. coli growth curve data by strain for LB (rich medium)KHK growth curves_M63.xlsx - E. coli growth curve data by strain for M63 (minimal medium)KHK growth curves_MAA.xlsx - E. coli growth curve data by strain for MAA (M63 supplied with 20 amino acids)Methodology (see related publication for full details)E. coli culture cell growth was detected at an absorbance of 600 nm, with readings obtained at 30-min or 1-h intervals for 24 to 48 h. The growth curves were obtained for each well. Repeated tests were performed, which resulted in 11 to 30 growth curves used for further calculations of growth rate and population density for each strain at each growth condition (medium). Growth curves were acquired in three different media: LB, M63 and MAA.BackgroundGenome reduction by removing dispensable genomic sequences in bacteria is commonly used in both fundamental and applied studies to determine the minimal genetic requirements for a living system or to develop highly efficient bioreactors. Nevertheless, whether and how the accumulative loss of dispensable genomic sequences disturbs bacterial growth remains unclear. To investigate the relationship between genome reduction and growth, a series of Escherichia coli strains carrying genomes reduced in a stepwise manner were used. Intensive growth analyses revealed that the accumulation of multiple genomic deletions caused decreases in the exponential growth rate and the saturated cell density in a deletion-length-dependent manner as well as gradual changes in the patterns of growth dynamics, regardless of the growth media. Accordingly, a perspective growth model linking genome evolution to genome engineering was proposed. This study provides the first demonstration of a quantitative connection between genomic sequence and bacterial growth, indicating that growth rate is potentially associated with dispensable genomic sequences.

The Gross Domestic Product (GDP) in Argentina expanded 5.80 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - Argentina GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset consists of growth and yield data for each season when soybean [Glycine max (L.) Merr.] was grown for seed at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL). In the 1994, 2003, 2004, and 2010 seasons, soybean was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field. In 2019, soybean was grown on four large, precision weighing lysimeters and their surrounding 4.4 ha fields. The square fields are themselves arranged in a larger square with four fields in four adjacent quadrants of the larger square. Fields and lysimeters within each field are thus designated northeast (NE), southeast (SE), northwest (NW), and southwest (SW). Soybean was grown on different combinations of fields in different years. Irrigation was by linear move sprinkler system in 1995, 2003, 2004, and 2010 although in 2010 only one irrigation was applied to establish the crop after which it was grown as a dryland crop. Irrigation protocols described as full were managed to replenish soil water used by the crop on a weekly or more frequent basis as determined by soil profile water content readings made with a neutron probe to 2.4-m depth in the field. Irrigation protocols described as deficit typically involved irrigations to establish the crop early in the season, followed by reduced or absent irrigations later in the season (typically in the later winter and spring). The growth and yield data include plant population density, height, plant row width, leaf area index, growth stage, total above-ground biomass, leaf and stem biomass, head mass (when present), kernel or seed number, and final yield. Data are from replicate samples in the field and non-destructive (except for final harvest) measurements on the weighing lysimeters. In most cases yield data are available from both manual sampling on replicate plots in each field and from machine harvest. Machine harvest yields are commonly smaller than hand harvest yields due to combine losses. These datasets originate from research aimed at determining crop water use (ET), crop coefficients for use in ET-based irrigation scheduling based on a reference ET, crop growth, yield, harvest index, and crop water productivity as affected by irrigation method, timing, amount (full or some degree of deficit), agronomic practices, cultivar, and weather. Prior publications have focused on soybean ET, crop coefficients, and crop water productivity. Crop coefficients have been used by ET networks. The data have utility for testing simulation models of crop ET, growth, and yield and have been used for testing, and calibrating models of ET that use satellite and/or weather data. See the README for descriptions of each data file. Resources in this dataset:Resource Title: 1995 Bushland, TX, west soybean growth and yield data. File Name: 1995 West Soybean_Growth_and_Yield-V2.xlsxResource Title: 2003 Bushland, TX, east soybean growth and yield data. File Name: 2003 East Soybean_Growth_and_Yield-V2.xlsxResource Title: 2004 Bushland, TX, east soybean growth and yield data. File Name: 2004 East Soybean_Growth-and_Yield-V2.xlsxResource Title: 2019 Bushland, TX, east soybean growth and yield data. File Name: 2019 East Soybean_Growth_and_Yield-V2.xlsxResource Title: 2019 Bushland, TX, west soybean growth and yield data. File Name: 2019 West Soybean_Growth_and_Yield-V2.xlsxResource Title: 2010 Bushland, TX, west soybean growth and yield data. File Name: 2010 West_Soybean_Growth_and_Yield-V2.xlsxResource Title: README. File Name: README_Soybean_Growth_and_Yield.txt

The Data Classification Market Report is Segmented by Component (Software and Services), Classification Method (Content-Based, Context-Based, and More), Organization Size (Large Enterprises and Small and Medium Enterprises (SMEs)), Application (Access Control and IAM, Governance and Compliance, and More), Industry Vertical (BFSI, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Data Subscription Service Market Outlook

The global data subscription service market size was valued at approximately USD 45 billion in 2023 and is expected to reach about USD 120 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% during the forecast period. This impressive growth is driven by the increasing reliance on data-driven decision-making across various industries. Businesses and individuals are increasingly subscribing to data services to gain insights, optimize operations, and drive innovation, which in turn fuels market expansion.

Several factors contribute to the robust growth of the data subscription service market. First, the exponential increase in data generation and the need for real-time analytics are primary drivers. In today’s digital age, vast amounts of data are generated every second through various channels such as social media, IoT devices, and e-commerce platforms. Organizations require sophisticated data services to analyze and interpret this data, drawing actionable insights that can enhance their business strategies, optimize operations, and improve customer experiences. Therefore, the demand for data subscription services is soaring, leading to significant market expansion.

Second, the growing adoption of artificial intelligence (AI) and machine learning (ML) technologies is a pivotal growth factor. Data subscription services are integral to the functioning of AI and ML systems as they provide the necessary data inputs for training and refining algorithms. As these technologies become more prevalent across industries such as healthcare, finance, and retail, the reliance on high-quality data services increases. Companies are investing more in data subscription services to harness the full potential of AI and ML, thereby driving market growth.

Third, the rise of remote work and digital transformation initiatives has further augmented the demand for data subscription services. With the shift towards remote and hybrid work models, organizations are increasingly leveraging cloud-based data services to ensure seamless access to vital information regardless of location. Additionally, digital transformation efforts are pushing companies to modernize their data infrastructure, thereby increasing the uptake of subscription-based data services. These trends are expected to continue, contributing significantly to the growth of the market.

Regionally, North America holds the lion’s share of the market, driven by the early adoption of advanced technologies and a strong presence of key industry players. The region's technological infrastructure and focus on innovation make it a fertile ground for the proliferation of data subscription services. However, the Asia Pacific region is projected to witness the highest growth rate, fueled by rapid digitalization, increasing internet penetration, and growing investments in AI and ML technologies. European markets are also notable, with a strong emphasis on regulatory compliance and data privacy driving the adoption of sophisticated data management solutions.

Type Analysis

The data subscription service market can be segmented by type into individual and corporate subscriptions. Individual subscriptions are generally tailored for personal use, providing users with access to specific datasets, market reports, or analytics tools that assist in personal projects, research, or small business operations. As digital literacy increases and more consumers become data-savvy, the demand for individual data subscription services is on the rise. These services are often more affordable and offer flexible payment options, making them accessible to a broader audience.

On the other hand, corporate subscriptions command a significant share of the market due to their comprehensive service offerings and value propositions tailored for businesses. Corporate subscriptions often include access to a vast array of datasets, advanced analytics tools, and dedicated support services. These subscriptions are critical for enterprises looking to enhance their data-driven decision-making processes, optimize operations, and gain a competitive edge. The complexity and volume of data required by corporations necessitate robust data subscription services, driving significant market demand in this segment.

A notable trend in the corporate segment is the increasing preference for customized data solutions. Businesses are seeking subscription services that can be tailored to their unique needs and industry-specific requirements. This customization trend is prompting servi

The Nordic Data Center Market Report is Segmented by Data Center Size (Large, Massive, Medium, Mega, and Small), Tier Type (Tier 1 and 2, Tier 3, and Tier 4), Absorption (Non-Utilized and Utilized), and Country (Denmark, Norway, Sweden, Finland, and Iceland). The Market Sizes and Forecasts are Provided in Terms of Volume in Megawatt (MW) for all the Above Segments.

Consumption growth in Romania, March, 2025 The most recent value is 6.89 percent as of Q1 2025, a decline compared to the previous value of 13.19 percent. Historically, the average for Romania from Q1 1996 to Q1 2025 is 22.28 percent. The minimum of -8.33 percent was recorded in Q2 2020, while the maximum of 147.8 percent was reached in Q3 1997. | TheGlobalEconomy.com