This dataset collection comprises a set of related data tables sourced from the 'Tilastokeskus' (Statistics Finland) website, based in Finland. These tables are organized in a column-and-row format, each containing relevant and interconnected data. The content of this collection is derived from the Statistics Finland's service interface, providing a wealth of information that is integral to statistical analysis. The collection can encompass one or several tables, depending on the breadth and depth of the data being covered. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).
This graph presents the results of a survey, conducted by BARC in 2014/15, into the current and planned use of technology for the analysis of big data. At the beginning of 2015, 13 percent of respondents indicated that their company was already using a big data analytical appliance for big data.
This data set contains the output from a keyword search document analysis of MassBays NEP Assessment Area communities. S1 is the list of keyword search terms. S2 is the list of planning documents included in the search. S3 are graphs of beneficiary profiles and ecosystem services profiles for each assessment area. S4 are graphs of ecosystem frequencies, beneficiary profiles, and ecosystem services for each cluster. S5 is the table of socio-economic and ecological variables for each assessment area. S6 are graphs of socio-economic and ecological variables for each cluster. S7 are post-hoc statistical analysis to relate socio-economic and ecological variables to ecosystem services priorities. S8 are the frequency at which ecosystems are mentioned in documents for each assessment area. S9 is the table of beneficiary profiles for each assessment area. S10 are the relative importance of ecosystem services attributes to each beneficiary type for each assessment area. S11 are the final ecosystem services profiles for each assessment area. S12 is the full list of final ecosystem services (an ecosystem + a beneficiary + an ecosystem services attribute) from all search documents. This dataset is associated with the following publication: Yee, S., L. Sharpe, B. Branoff, C. Jackson, G. Cicchetti, S. Jackson, M. Pryor, and E. Shumchenia. Ecosystem Services Profiles for Communities Benefitting from Estuarine Habitats along the Massachusetts Coast, USA. Ecological Informatics. Elsevier Science Ltd, New York, NY, USA, 77: 102182, (2023).
This graph presents the results of a survey, conducted by BARC in 2014/15, into the current and planned distribution of big data projects within companies. At the beginning of 2015, 25 percent of respondents indicated that their company's marketing department had already begun using big data analysis.
Big Data as a Service Market Size 2024-2028
The big data as a service market size is forecast to increase by USD 41.20 billion at a CAGR of 28.45% between 2023 and 2028.
The market is experiencing significant growth due to the increasing volume of data and the rising demand for advanced data insights. Machine learning algorithms and artificial intelligence are driving product quality and innovation in this sector. Hybrid cloud solutions are gaining popularity, offering the benefits of both private and public cloud platforms for optimal data storage and scalability. Industry standards for data privacy and security are increasingly important, as large amounts of data pose unique risks. The BDaaS market is expected to continue its expansion, providing valuable data insights to businesses across various industries.
What will be the Big Data as a Service Market Size During the Forecast Period?
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Big Data as a Service (BDaaS) has emerged as a game-changer in the business world, enabling organizations to harness the power of big data without the need for extensive infrastructure and expertise. This service model offers various components such as data management, analytics, and visualization tools, enabling businesses to derive valuable insights from their data. BDaaS encompasses several key components that drive market growth. These include Business Intelligence (BI), Data Science, Data Quality, and Data Security. BI provides organizations with the ability to analyze data and gain insights to make informed decisions.
Data Science, on the other hand, focuses on extracting meaningful patterns and trends from large datasets using advanced algorithms. Data Quality is a critical component of BDaaS, ensuring that the data being analyzed is accurate, complete, and consistent. Data Security is another essential aspect, safeguarding sensitive data from cybersecurity threats and data breaches. Moreover, BDaaS offers various data pipelines, enabling seamless data integration and data lifecycle management. Network Analysis, Real-time Analytics, and Predictive Analytics are other essential components, providing businesses with actionable insights in real-time and enabling them to anticipate future trends. Data Mining, Machine Learning Algorithms, and Data Visualization Tools are other essential components of BDaaS.
How is this market segmented and which is the largest segment?
The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Type
Data analytics-as-a-Service
Hadoop-as-a-service
Data-as-a-service
Deployment
Public cloud
Hybrid cloud
Private cloud
Geography
North America
Canada
US
APAC
China
Europe
Germany
UK
South America
Middle East and Africa
By Type Insights
The data analytics-as-a-service segment is estimated to witness significant growth during the forecast period.
Big Data as a Service (BDaaS) is a significant market segment, highlighted by the availability of Hadoop-as-a-Service solutions. These offerings enable businesses to access essential datasets on-demand without the burden of expensive infrastructure. DAaaS solutions facilitate real-time data analysis, empowering organizations to make informed decisions. The DAaaS landscape is expanding rapidly as companies acknowledge its value in enhancing internal data. Integrating DAaaS with big data systems amplifies analytics capabilities, creating a vibrant market landscape. Organizations can leverage diverse datasets to gain a competitive edge, driving the growth of the global BDaaS market. In the context of digital transformation, cloud computing, IoT, and 5G technologies, BDaaS solutions offer optimal resource utilization.
However, regulatory scrutiny poses challenges, necessitating stringent data security measures. Retail and other industries stand to benefit significantly from BDaaS, particularly with distributed computing solutions. DAaaS adoption is a strategic investment for businesses seeking to capitalize on the power of external data for valuable insights.
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The Data analytics-as-a-Service segment was valued at USD 2.59 billion in 2018 and showed a gradual increase during the forecast period.
Regional Analysis
North America is estimated to contribute 35% to the growth of the global market during the forecast period.
Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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Big Data as a Service Market analysis, North America is experiencing signif
This page lists ad hoc statistics released during the period July-September 2021. These are additional analyses not included in any of the Department for Digital, Culture, Media and Sport’s standard publications.
If you would like any further information please contact evidence@dcms.gov.uk
This analysis provides estimates of data use amongst UK organisations, using the UK Business Survey (UKBDS). This accompanies analysis within the consultation for UK data reform. This is an abridged set of specific findings from the UKBDS, a telephone-based quantitative and qualitative study of UK businesses, which seeks to understand the role and importance of personal and non-personal data in UK businesses, domestic and international transfers of data, and the awareness of, and attitudes toward, data protection legislation and policy.
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The size and share of the market is categorized based on Type (Data Mining, Predictive Data Analysis, Cluster Analysis, Data Summary, Others) and Application (SMEs, Large Enterprises) and geographical regions (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).
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The need for advanced analytical approaches to provide HPDA solutions is driving the market growth of High Performance Data Analytics (HPDA). According to the analyst from Verified Market Research, The High Performance Data Analytics (HPDA) Market is estimated to reach a valuation of USD 597.06 Billion over the forecast period 2031, by subjugating around USD 113.23 Billion in 2023.
The adoption of an open-source framework for big data analytics is driving market growth. This surge in demand enables the market to grow at a CAGR of 23.1% from 2024 to 2031.
High Performance Data Analytics (HPDA) Market: Definition/ Overview
HPDA refers to big data analytics that uses High-Performance Computing (HPC) techniques. Big data analytics has always relied on high-performance computing (HPC), but as data grows exponentially, new forms of high-performance computing will be required to access previously unimaginable volumes of data. The combination of big data analytics and high-performance computing is called “high-performance data analytics.” High-performance data analytics is the process of quickly finding insights from large data sets by running powerful analytical tools in parallel on high-performance computing systems.
Furthermore, high-performance data analytics infrastructure is a rapidly expanding market for government and commercial organizations that need to combine high-performance computing with data-intensive analysis. For complex modeling and simulations, big data analytics techniques like Hadoop and Spark have long required high-performance computing, which they lack.
This page lists ad-hoc statistics released during the period April - June 2019. These are additional analyses not included in any of the Department for Digital, Culture, Media and Sport’s standard publications.
If you would like any further information please contact evidence@culture.gov.uk.
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MS Excel Spreadsheet, 36.9 KB
Expert industry market research on the Market Research and Statistical Services in Australia (2008-2031). Make better business decisions, faster with IBISWorld's industry market research reports, statistics, analysis, data, trends and forecasts.
This statistic shows the size of the global big data analytics services market related to healthcare in 2016 and a forecast for 2025, by application. It is predicted that by 2025 the market for health-related financial analytics services using big data will increase to over 13 billion U.S. dollars.
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Business Analytics Market was valued at USD 84.42 Billion in 2024 and is projected to reach USD 176.14 Billion by 2031, growing at a CAGR of 9.63% from 2024 to 2031.
Global Business Analytics Market Drivers
The market drivers for the Business Analytics Market can be influenced by various factors. These may include:
Growing Adoption of Big Data Analytics: In order to extract meaningful insights from their data, organizations are progressively using big data analytics in response to the exponential expansion of data. Making educated decisions through data analysis is facilitated by business analytics.
Growing Need for Data-driven Decision Making: In order to obtain a competitive edge, businesses are realizing the significance of data-driven decision making. The methods and instruments for data analysis and significant insights extraction for improved decision-making are offered by business analytics.
Growing Need for Predictive and Prescriptive Analytics: Predictive and prescriptive analytics are becoming more and more in demand as a means of projecting future trends and results. Businesses can use business analytics to prescribe activities to achieve desired outcomes and forecast future outcomes based on previous data.
Growing Emphasis on Customer Analytics: As e-commerce and digital marketing gain traction, companies are putting more of an emphasis on comprehending the behavior and preferences of their customers. In order to increase consumer engagement and personalize marketing efforts, business analytics is used to analyze customer data.
Emergence of Advanced Technologies: The use of advanced analytics solutions is being propelled by developments in fields like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Businesses may now analyze data more effectively and gain deeper insights thanks to these technologies.
Operational Efficiency and Cost Optimization Are Necessary: Companies are always under pressure to increase operational efficiency and reduce costs. Business analytics promotes market expansion by assisting in the identification of opportunities for process and cost-cutting enhancements.
Compliance and Regulatory Requirements: The use of business analytics solutions for risk management and compliance reporting is being fueled by the growing regulatory requirements in a number of industries, including healthcare, banking, and retail.
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Switzerland Data Center Server Market is Segmented by Form Factor (Blade Server, Rack Server, and Tower Server) and End User (Banking, Financial Services, and Insurance, IT and Telecommunications, Government, Media and Entertainment, and Other End-Users). The Market Sizes and Forecasts are Provided in Terms of Value in USD for all the Above Segments.
Service generated by the map Statistical analysis of bocagère dynamics in Normandy
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License information was derived automatically
Metabolomics data analysis depends on the utilization of bioinformatics tools. To meet the evolving needs of metabolomics research, several integrated platforms have been developed. Our group has developed a desktop platform IP4M (integrated Platform for Metabolomics Data Analysis) which allows users to perform a nearly complete metabolomics data analysis in one-stop. With the extensive usage of IP4M, more and more demands were raised from users worldwide for a web version and a more customized workflow. Thus, iMAP (integrated Metabolomics Analysis Platform) was developed with extended functions, improved performances, and redesigned structures. Compared with existing platforms, iMAP has more methods and usage modes. A new module was developed with an automatic pipeline for train-test set separation, feature selection, and predictive model construction and validation. A new module was incorporated with sufficient editable parameters for network construction, visualization, and analysis. Moreover, plenty of plotting tools have been upgraded for highly customized publication-ready figures. Overall, iMAP is a good alternative tool with complementary functions to existing metabolomics data analysis platforms. iMAP is freely available for academic usage at https://imap.metaboprofile.cloud/ (License MPL 2.0).
Envestnet®| Yodlee®'s Online Purchase Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.
Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.
We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.
Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?
Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.
Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking
Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)
Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence
Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis
This dataset collection comprises a series of related data tables sourced from the website of 'Tilastokeskus' (Statistics Finland), based in Finland. The tables within this collection contain data retrieved from the Statistics Finland's service interface (WFS). The content of the tables is organized in a structured format with rows and columns, showcasing a correlation between different sets of data. The collection, while primarily intended for statistical analysis, can be utilized in a variety of ways, depending on the specific needs of the user. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).
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The global data center services market size was valued at USD XX million in 2019 and is projected to reach USD XX million by 2033, exhibiting a CAGR of XX% during the forecast period. This growth can be attributed to the increasing demand for secure and reliable data storage and management solutions, as well as the proliferation of cloud computing and artificial intelligence (AI). Key market drivers include:
Rising data volumes: The amount of data generated worldwide is growing exponentially, driven by the proliferation of connected devices and the adoption of data-intensive applications. This growth is fueling the demand for data center services to store and manage this data. Increasing cloud adoption: Cloud computing is becoming increasingly popular as businesses seek to reduce costs and improve flexibility. As cloud adoption increases, so does the demand for data center services to support cloud workloads. Growing AI adoption: AI is a rapidly growing field that requires significant computational resources. This growth is fueling the demand for data center services to support AI applications.
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Data Analytics Market Valuation – 2024-2031
Data Analytics Market was valued at USD 68.83 Billion in 2024 and is projected to reach USD 482.73 Billion by 2031, growing at a CAGR of 30.41% from 2024 to 2031.
Data Analytics Market Drivers
Data Explosion: The proliferation of digital devices and the internet has led to an exponential increase in data generation. Businesses are increasingly recognizing the value of harnessing this data to gain competitive insights.
Advancements in Technology: Advancements in data storage, processing power, and analytics tools have made it easier and more cost-effective for organizations to analyze large datasets.
Increased Business Demand: Businesses across various industries are seeking data-driven insights to improve decision-making, optimize operations, and enhance customer experiences.
Data Analytics Market Restraints
Data Quality and Integrity: Ensuring the accuracy, completeness, and consistency of data is crucial for effective analytics. Poor data quality can hinder insights and lead to erroneous conclusions.
Data Privacy and Security Concerns: As organizations collect and analyze sensitive data, concerns about data privacy and security are becoming increasingly important. Breaches can have significant financial and reputational consequences.
This page lists ad-hoc statistics released during the period April - June 2020. These are additional analyses not included in any of the Department for Digital, Culture, Media and Sport’s standard publications.
If you would like any further information please contact evidence@culture.gov.uk.
These are experimental estimates of the quarterly GVA in chained volume measures by DCMS sectors and subsectors between 2010 and 2018, which have been produced to help the department estimate the effect of shocks to the economy. Due to substantial revisions to the base data and methodology used to construct the tourism satellite account, estimates for the tourism sector are only available for 2017. For this reason “All DCMS Sectors” excludes tourism. Further, as chained volume measures are not available for Civil Society at present, this sector is also not included.
The methods used to produce these estimates are experimental. The data here are not comparable to those published previously and users should refer to the annual reports for estimates of GVA by businesses in DCMS sectors.
GVA generated by businesses in DCMS sectors (excluding Tourism and Civil Society) increased by 31.0% between the fourth quarters of 2010 and 2018. The UK economy grew by 16.7% over the same period.
All individual DCMS sectors (excluding Tourism and Civil Society) grew faster than the UK average between quarter 4 of 2010 and 2018, apart from the Telecoms sector, which decreased by 10.1%.
MS Excel Spreadsheet, 57KB
This data shows the proportion of the total turnover in DCMS sectors in 2017 that was generated by businesses according to individual businesses turnover, and by the number of employees.
In 2017 a larger share of total turnover was generated by DCMS sector businesses with an annual turnover of less than one million pounds (11.4%) than the UK average (8.6%). In general, individual DCMS sectors tended to have a higher proportion of total turnover generated by businesses with individual turnover of less than one million pounds, with the exception of the Gambling (0.2%), Digital (8.2%) and Telecoms (2.0%, wholly within Digital) sectors.
DCMS sectors tended to have a higher proportion of total turnover generated by large (250 employees or more) businesses (57.8%) than the UK average (51.4%). The exceptions were the Creative Industries (41.7%) and the Cultural sector (42.4%). Of all DCMS sectors, the Gambling sector had the highest proportion of total turnover generated by large businesses (97.5%).
MS Excel Spreadsheet, 43.4KB
This dataset collection comprises a set of related data tables sourced from the 'Tilastokeskus' (Statistics Finland) website, based in Finland. These tables are organized in a column-and-row format, each containing relevant and interconnected data. The content of this collection is derived from the Statistics Finland's service interface, providing a wealth of information that is integral to statistical analysis. The collection can encompass one or several tables, depending on the breadth and depth of the data being covered. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).