The global spreadsheet software market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions and the rising demand for data analysis tools across various industries. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $150 billion by the end of the forecast period. This growth is fueled by several key factors. Firstly, the increasing reliance on data-driven decision-making across businesses, irrespective of size, necessitates efficient data management and analysis capabilities provided by spreadsheet software. Secondly, the proliferation of cloud-based spreadsheet applications offers enhanced collaboration, accessibility, and scalability, making them attractive to organizations of all sizes. Finally, continuous advancements in features like advanced analytics, data visualization, and integration with other business applications enhance the overall utility and appeal of these tools. Major players like Microsoft, Google, and Zoho are continuously innovating, adding new features and improving user experience to maintain their market leadership. However, the market also faces challenges. Security concerns related to data storage and access in cloud-based solutions, and the need for continuous training and upskilling to leverage advanced features, pose limitations to wider adoption. Despite these challenges, the long-term outlook for the spreadsheet software market remains positive. The increasing digitization of businesses and the expanding adoption of big data analytics will propel demand for sophisticated spreadsheet tools. The emergence of niche players focusing on specific industry needs and specialized functionalities will also contribute to market expansion. Competition will remain fierce among established players and newcomers, prompting innovation and improvement in the overall product offerings. The market will witness consolidation through mergers and acquisitions, and a shift towards subscription-based models, further driving market growth and shaping the competitive landscape. The geographic distribution of the market will see continued growth in developing economies, driven by increasing internet penetration and smartphone adoption.

The global spreadsheets software market is experiencing robust growth, driven by increasing digitalization across industries and the rising adoption of cloud-based solutions. The market, estimated at $20 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $35 billion by 2033. This growth is fueled by several factors, including the expanding need for data analysis and visualization across SMEs and large enterprises, the increasing availability of user-friendly and feature-rich spreadsheet software, and the growing preference for collaborative tools that facilitate seamless teamwork. The market is segmented by operating system (Windows, Macintosh, Linux, Others) and user type (SMEs, Large Enterprises). While Microsoft Excel maintains a dominant market share, the rise of cloud-based alternatives like Google Sheets and collaborative platforms is challenging this dominance, fostering competition and innovation. Furthermore, the increasing integration of spreadsheets with other business intelligence tools further enhances their utility and fuels demand. Geographic expansion, particularly in developing economies with rising internet penetration, also contributes significantly to market expansion. However, factors such as the high initial investment in software licenses and the need for specialized training can restrain market growth, particularly for smaller businesses with limited budgets and technical expertise. The increasing complexity of data analysis necessitates enhanced security features and data protection measures, which add cost and require ongoing investment. Moreover, the emergence of advanced analytical tools and specialized data visualization software presents a competitive challenge, demanding continuous innovation and adaptation from existing spreadsheet software providers. Nevertheless, the overall market outlook remains positive, driven by sustained demand from diverse industries and technological advancements within the software landscape.

The global spreadsheet editor market is experiencing robust growth, driven by the increasing digitization of businesses and the rising demand for efficient data management solutions across various industries. The market, estimated at $50 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 10% from 2025 to 2033, reaching approximately $130 billion by 2033. This growth is fueled by several factors, including the expanding adoption of cloud-based spreadsheet editors offering enhanced collaboration and accessibility features, the increasing need for data analysis and visualization tools within organizations of all sizes (Large Enterprises and SMBs), and the integration of spreadsheet software with other business applications through APIs offered by companies like Zapier. The free segment holds a significant market share, particularly among individual users and small businesses, while the paid segment, which offers advanced features and support, contributes substantially to overall market revenue. Key players such as Microsoft, Google, and LibreOffice dominate the market, but emerging players are continually introducing innovative features and pricing models to gain a competitive edge. Significant regional variations exist. North America currently holds the largest market share due to high technology adoption and a well-established digital infrastructure, followed by Europe and Asia-Pacific. However, the Asia-Pacific region is anticipated to experience the fastest growth in the forecast period due to rapid technological advancements and increasing internet penetration across countries like India and China. Growth restraints include security concerns related to cloud storage, the cost of implementation and training for complex software, and the increasing competition from specialized data analysis tools. Despite these challenges, the consistent demand for streamlined data management across diverse sectors ensures the continued expansion of the spreadsheet editor market in the coming years. The market’s evolution reflects a shift towards user-friendly, feature-rich, and collaborative solutions that are seamlessly integrated into broader business ecosystems.

Spreadsheet Editor Market Outlook

The global spreadsheet editor market size was valued at approximately $1.8 billion in 2023 and is expected to grow to $3.6 billion by 2032, at a compound annual growth rate (CAGR) of 8.2%. This robust growth is driven by increasing digitalization and the growing necessity for efficient data handling and analysis tools across multiple sectors.

One of the primary factors contributing to the growth of the spreadsheet editor market is the surge in demand for data analytics and business intelligence tools. Organizations are increasingly relying on data to drive decision-making processes, necessitating the use of advanced spreadsheet editors that offer more features than traditional tools. These modern spreadsheet editors are integral in compiling, analyzing, and visualizing data, thereby streamlining business operations and enhancing productivity.

Another significant growth driver is the adoption of cloud-based solutions. The transition from on-premises software to cloud-based platforms offers manifold advantages, such as scalability, accessibility from any location, and reduced IT overhead. Cloud-based spreadsheet editors enable real-time collaboration and data sharing, making them particularly appealing to global teams and remote workers. This shift to cloud computing is anticipated to further propel the market during the forecast period.

Moreover, the escalation of digital transformation initiatives across various industries has also spurred the adoption of sophisticated spreadsheet editing tools. Companies are increasingly investing in digital tools to automate and enhance their workflows, which includes investing in advanced spreadsheet editors with capabilities like artificial intelligence (AI) and machine learning (ML) integration, automated data entry, and predictive analytics. These features not only save time but also significantly reduce the risk of human error, thereby boosting operational efficiency.

Regionally, North America holds a dominant position in the spreadsheet editor market, primarily due to the high adoption rate of advanced technologies and the presence of key market players. The region's well-established IT infrastructure and the increasing demand for data-driven decision-making processes contribute to its market leadership. However, the Asia Pacific region is expected to witness the highest growth rate owing to rapid industrialization and the growing awareness of digital tools among small and medium enterprises (SMEs).

Component Analysis

The spreadsheet editor market is segmented by component into software and services. The software segment encompasses the actual spreadsheet applications that users interact with, while the services segment includes support, maintenance, and consulting services. The software segment currently holds the largest market share due to the high demand for advanced spreadsheet solutions that offer a multitude of functionalities beyond basic data entry and calculation.

Modern spreadsheet software offers features such as real-time collaboration, advanced data visualization, and integration with other business applications. These features are crucial for businesses that rely on data to make informed decisions. The integration of AI and ML into spreadsheet software is also a significant trend, enabling functionalities like automated data analysis, anomaly detection, and predictive analytics. This makes the software segment highly appealing to businesses aiming for operational efficiency and accuracy in data handling.

On the other hand, the services segment is witnessing substantial growth due to the increasing complexity of spreadsheet software and the need for specialized support. As organizations adopt more sophisticated tools, they require expert guidance for seamless integration, customization, and troubleshooting. Service providers offer essential support services, including training, maintenance, and consulting, which are vital for maximizing the effectiveness of spreadsheet software. Thus, the services segment is expected to experience steady growth alongside the software segment.

The demand for cloud-based spreadsheet software is also boosting the services segment. As more organizations migrate their operations to the cloud, the need for cloud consulting and support services has surged. These

The excelforms extension for CKAN provides a mechanism for users to input data into Table Designer tables using Excel-based forms, enhancing data entry efficiency. This extension focuses on streamlining the process of adding data rows to tables within CKAN's Table Designer. A key component of the functionality is the ability to import multiple rows in a single operation, which significant reduces overhead associated with entering multiple data points. Key Features: Excel-Based Forms: Users can enter data using familiar Excel spreadsheets, leveraging their existing skills and software. Table Designer Integration: Designed to work seamlessly with CKAN's Table Designer, extending its functionality to include Excel-based data entry. Multiple Row Import: Supports importing multiple rows of data at once, improving data entry efficiency, especially when dealing with large datasets. Data mapping: Simplifies the process of aligning excel column headers to their corresponding data fields in tables. Improved Data Entry Speed: Provides an alternative to manual data entry, resulting in faster population and easier updates. Technical Integration: The excelforms extension integrates with CKAN by introducing new functionalities and workflows around the Table Designer plugin. The installation instructions specify that this plugin to be added before the tabledesigner plugin. Benefits & Impact: By enabling Excel-based data entry, the excelforms extension improves the user experience for those familiar with spreadsheet software. The ability to import multiple rows simultaneously significantly reduces the time and effort required to populate tables, particularly when dealing with large amounts of data. The impact is better data accessibility through the streamlining of data population workflows.

Market Overview: The global spreadsheet editor market is projected to reach a value of XXX million by 2033, growing at a CAGR of XX% during the forecast period (2025-2033). The market is driven by the increasing adoption of digital tools for data management, collaboration, and analysis. The rise of cloud computing and the integration of AI and machine learning capabilities into spreadsheet software are further fueling market growth. Key trends in the market include the increasing popularity of free and open-source spreadsheet editors, the adoption of spreadsheet software by SMBs, and the integration of spreadsheet software with other business applications. Competitive Landscape: The spreadsheet editor market is dominated by a few major players, including Microsoft, Google, Apple, and Apache Software Foundation. Microsoft Excel is the market leader, with a significant share of the market. Other major players include Google Sheets, Apple Numbers, and Apache OpenOffice Calc. The market is also witnessing the emergence of new players offering innovative spreadsheet solutions. For example, Ragic provides a cloud-based spreadsheet software with advanced collaboration features, while Spreadsheetsoftware offers a spreadsheet editor specifically designed for financial modeling. The competitive landscape is expected to intensify in the coming years as more players enter the market with differentiated offerings.

Global Hybrid Integration Platform Market size was valued at USD 31.69 Billion in 2022 and is poised to grow from USD 35.49 Billion in 2023 to USD 87.88 Billion by 2031, growing at a CAGR of 12% in the forecast period (2024-2031).

This spreadsheet contains per-site metadata for the WIND Toolkit sites and serves as an index for the raw data hosted on Globus connect (nrel#globus:/globusro/met_data). Aside from the metadata, per site average power and capacity factor are given. This data was prepared by 3TIER under contract by NREL and is public domain.

Authoritative documentation on the creation of the underlying dataset is at:

Final Report on the Creation of the Wind Integration National Dataset (WIND) Toolkit and API: http://www.nrel.gov/docs/fy16osti/66189.pdf

This is the carbon monoxide data. Each sheet (tab) is formatted to be exported as a .csv for use with the R-code (AQ-June20.R). In order for this code to work properly, it is important that this file remain intact. Do not change the column names or codes for data, for example. And to be safe, don’t even sort. Just in case. One simple change in the excel file could make the code full of bugs.

This is the raw SO2 data. Each sheet (tab) is formatted to be exported as a .csv for use with the R-code (AQ-June20.R). In order for this code to work properly, it is important that this file remain intact. Do not change the column names or codes for data, for example. And to be safe, don’t even sort. One simple change in the excel file could make the code full of bugs.

EFO cell lines drawn from external sources. In the initial step of the EFO-CLO comparison and alignment process, there are 428 and 20 EFO cell lines which were imported from Cell Line Ontology and 20 in BRENDA Tissue and Enzyme Source Ontology respectively. These 448 EFO cell lines were excluded from the entire mapping process. File is stored in Microsoft Excel spreadsheet (xlsx) format. (XLSX 47Â kb)

The CE-Dredge Decision Support Tool (DST) is a web-based dashboard providing an integrated, comprehensive approach for strategic dredged material management. The DST integrates selected Corps enterprise data, knowledge, tool results, and limited external data to allow more efficient and effective real time and long-term planning, communication (internal and external), and collaborative decision-making regarding activities to improve the management and beneficial use of dredged material. The goal is to streamline preliminary or DMMP assessments by utilizing the USACE Navigation Data Integration Framework (NDIF) to develop a “living” DMMP capability.

This spreadsheet provides the data used to produce the figures in "Short-term integration costs of variable renewable energy: Wind curtailment and balancing in Britain and Germany" by Michael Joos and Iain Staffell.

Context: In response to the exponential growth of data and increasingly regulatory requirements, such as the General Data Protection Regulation (GDPR) and Brazil’s General Data Protection Law (LGPD), Data Governance (DG) has become a strategic priority for organizations. These regulations underscore the importance of structured strategies to ensure compliance, data quality, and security.

Objective: This study presents an overview of DG maturity models and practical approaches to assess and enhance organizational capabilities. Based on the evidence gathered, it proposes a conceptual framework composed of six dimensions to support the evaluation and advancement of DG maturity.

Method: We carried out a Systematic Literature Review (SLR), focusing on DG maturity assessments, tools, and best practices from academy and industry. After the conduction of the SLR, 22 primary studies were selected. These studies were analyzed and synthesized to highlight main features of existing models, tools, and practices applied in organizational data governance.

Results: The findings highlight widely used maturity models and a range of practices—such as policy formalization, staff training, and iterative quality assessment—that support organizations in addressing challenges related to data integration, security, and strategic alignment. Building on this synthesis, the study introduces a six-dimensional framework (DG2M) to guide organizations in assessing current capabilities and implementing targeted improvements.

Conclusions: This work reinforces the significance of DG maturity models and emerging best practices in structuring governance initiatives. The proposed framework serves as a practical tool to support organizations in identifying gaps and enhancing their data governance capabilities in alignment with regulatory and strategic demands.

Keywords: Data Governance, Data Maturity, Systematic Literature Review, Data Governance Framework, Data Quality

Website for the framework featuring an interactive view: https://datagovernancematurity.github.io/framework/" target="_blank" rel="noopener">https://datagovernancematurity.github.io/framework/

Available Resources

The following files are available for download and reference:

• Overview of the SLR Process: A detailed description of the methodology, including research questions, inclusion/exclusion criteria, and quality assessment protocols.
• Collected Articles and Selection Criteria: A spreadsheet documenting the collected studies and their evaluation against inclusion and exclusion criteria.
• Quality Assessment Results: A spreadsheet with the quality assessment of the selected studies, based on predefined questions to ensure methodological rigor.
• Data Extraction Results: A detailed spreadsheet capturing information extracted from the selected studies, including objectives, methods, and outcomes.
• Proposed Framework Construction: a spreadsheet that supported the development of this framework.

Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.

With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.

Why Choose Success.ai’s Ecommerce Store Data?

1. Verified Profiles for Precision Engagement

   • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.

2. Comprehensive Coverage of the APAC E-commerce Sector

   • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
   • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.

3. Continuously Updated Datasets

   • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
   • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Access business profiles for e-commerce professionals and organizations across APAC.
• Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
• Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
• Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

Key Features of the Dataset:

1. Comprehensive E-commerce Business Profiles

   • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
   • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.

2. Advanced Filters for Precision Campaigns

   • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
   • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.

3. Regional and Sector-specific Insights

   • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
   • Refine your marketing strategies and outreach efforts to align with market priorities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Outreach

   • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
   • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.

3. Market Research and Competitive Analysis

   • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
   • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...

Success.ai’s Ecommerce Market Data for South-east Asia E-commerce Contacts provides a robust and accurate dataset tailored for businesses and organizations looking to connect with professionals in the fast-growing e-commerce industry across South-east Asia. Covering roles such as e-commerce managers, digital strategists, logistics experts, and online marketplace leaders, this dataset offers verified contact details, professional insights, and actionable market data.

With access to over 170 million verified profiles globally, Success.ai ensures your outreach, marketing, and research strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in one of the world’s most dynamic e-commerce regions.

Why Choose Success.ai’s Ecommerce Market Data?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of e-commerce professionals across South-east Asia.
   • AI-driven validation ensures 99% accuracy, reducing communication inefficiencies and enhancing engagement rates.

2. Comprehensive Coverage of South-east Asia’s E-commerce Market

   • Includes professionals from key e-commerce hubs such as Singapore, Indonesia, Thailand, Vietnam, Malaysia, and the Philippines.
   • Gain insights into regional consumer trends, logistics challenges, and online marketplace dynamics.

3. Continuously Updated Datasets

   • Real-time updates capture changes in professional roles, company expansions, and market conditions.
   • Stay aligned with industry trends and emerging opportunities in South-east Asia’s e-commerce sector.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 170M+ Verified Global Profiles: Engage with e-commerce professionals and decision-makers across South-east Asia.
• Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precision targeting.
• Regional Insights: Understand key trends in e-commerce, logistics, and consumer preferences in South-east Asia.
• Leadership Insights: Connect with online marketplace leaders, logistics managers, and digital marketing professionals driving innovation in the sector.

Key Features of the Dataset:

1. Comprehensive Professional Profiles in E-commerce

   • Identify and connect with professionals managing e-commerce platforms, online marketplaces, and logistics operations.
   • Target individuals responsible for digital marketing, supply chain management, and e-commerce strategies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (apparel, electronics, food delivery), geographic location, or job function.
   • Tailor campaigns to align with specific business goals, such as logistics optimization, consumer engagement, or market entry.

3. Regional and Market-specific Insights

   • Leverage data on e-commerce trends, regional consumer behaviors, and logistics challenges unique to South-east Asia.
   • Refine marketing strategies and business plans based on actionable insights from the region.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Digital Outreach

   • Promote e-commerce solutions, logistics services, or online marketing tools to professionals in South-east Asia’s e-commerce industry.
   • Use verified contact data for multi-channel outreach, including email, phone, and digital campaigns.

2. Market Research and Competitive Analysis

   • Analyze e-commerce trends and consumer preferences across South-east Asia to refine product offerings and marketing strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

3. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce platforms, logistics providers, and digital marketing agencies exploring strategic partnerships.
   • Foster collaborations that enhance consumer experiences, improve delivery efficiency, or expand market reach.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry seeking candidates for logistics, digital marketing, and platform management roles.
   • Provide workforce optimization platforms or training solutions tailored to the sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce market data at competitive prices, ensuring strong ROI for your marketing, sales, and business development initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics ...

NoSQL Database Market size was valued at USD 7.43 Billion in 2024 and is projected to reach USD 60 Billion by 2031, growing at a CAGR of 30% during the forecast period from 2024 to 2031.

Global NoSQL Database Market Drivers

Big Data Management: The exponential growth of unstructured and semi-structured data necessitates flexible and scalable database solutions. Cloud Computing Adoption: The shift towards cloud-based applications and infrastructure is driving demand for NoSQL databases. Real-time Analytics: NoSQL databases excel at handling real-time data processing and analytics, making them suitable for applications like IoT and fraud detection.

Global NoSQL Database Market Restraints

Complexity and Management Challenges: NoSQL databases can be complex to manage and require specialized skills. Lack of Standardization: The absence of a standardized NoSQL query language can hinder data integration and migration.

Big Data Technology Market Outlook

The global big data technology market size was valued at approximately $162 billion in 2023 and is projected to reach around $471 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 12.6% during the forecast period. The growth of this market is primarily driven by the increasing demand for data analytics and insights to enhance business operations, coupled with advancements in AI and machine learning technologies.

One of the principal growth factors of the big data technology market is the rapid digital transformation across various industries. Businesses are increasingly recognizing the value of data-driven decision-making processes, leading to the widespread adoption of big data analytics. Additionally, the proliferation of smart devices and the Internet of Things (IoT) has led to an exponential increase in data generation, necessitating robust big data solutions to analyze and extract meaningful insights. Organizations are leveraging big data to streamline operations, improve customer engagement, and gain a competitive edge.

Another significant growth driver is the advent of advanced technologies like artificial intelligence (AI) and machine learning (ML). These technologies are being integrated into big data platforms to enhance predictive analytics and real-time decision-making capabilities. AI and ML algorithms excel at identifying patterns within large datasets, which can be invaluable for predictive maintenance in manufacturing, fraud detection in banking, and personalized marketing in retail. The combination of big data with AI and ML is enabling organizations to unlock new revenue streams, optimize resource utilization, and improve operational efficiency.

Moreover, regulatory requirements and data privacy concerns are pushing organizations to adopt big data technologies. Governments worldwide are implementing stringent data protection regulations, like the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States. These regulations necessitate robust data management and analytics solutions to ensure compliance and avoid hefty fines. As a result, organizations are investing heavily in big data platforms that offer secure and compliant data handling capabilities.

As organizations continue to navigate the complexities of data management, the role of Big Data Professional Services becomes increasingly critical. These services offer specialized expertise in implementing and managing big data solutions, ensuring that businesses can effectively harness the power of their data. Professional services encompass a range of offerings, including consulting, system integration, and managed services, tailored to meet the unique needs of each organization. By leveraging the knowledge and experience of big data professionals, companies can optimize their data strategies, streamline operations, and achieve their business objectives more efficiently. The demand for these services is driven by the growing complexity of big data ecosystems and the need for seamless integration with existing IT infrastructure.

Regionally, North America holds a dominant position in the big data technology market, primarily due to the early adoption of advanced technologies and the presence of key market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by increasing digitalization, the rapid growth of industries such as e-commerce and telecommunications, and supportive government initiatives aimed at fostering technological innovation.

Component Analysis

The big data technology market is segmented into software, hardware, and services. The software segment encompasses data management software, analytics software, and data visualization tools, among others. This segment is expected to witness substantial growth due to the increasing demand for data analytics solutions that can handle vast amounts of data. Advanced analytics software, in particular, is gaining traction as organizations seek to gain deeper insights and make data-driven decisions. Companies are increasingly adopting sophisticated data visualization tools to present complex data in an easily understandable format, thereby enhancing decision-making processes.

Presentation The objective of the programme is to mobilise and structure all actors in the educational community (State, local authorities, parents, associations, extracurricular workers, social workers, schools and colleges...) around shared educational issues to consolidate the care of children and young people in priority urban policy areas, from early childhood to their professional integration, at all times and in all living areas. Educational Cities are located in large neighbourhoods of social housing, with major urban dysfunctions and school mix issues. #### Data The dataset contains: — the list of educational cities | Name | Description | |---|---| | id_cite| ID of the Educational City | | lib_cite | Text of the Educational City | — the list of municipalities covered by the programme | Name | Description | |---|---| | insee_com| code insee de la commune | | lib_com | town label | | id_cite| ID of the Educational City | | lib_cite | Text of the Educational City | — the list of priority areas covered by the programme | Name | Description | |---|---| | yearnee| year of initiation of the device in the territory | | id_cite| ID of the Educational City | | quote_sister| Sister Educational City | | lib_cite| language of the Educational City | | qp_intercom | intercommunal priority neighbourhood | | com_cite | membership of the commune of qp in the perimeter of the educational city | #### Useful Links — crossing with other ANCT devices (data.gouv) — detailed presentation of the programme (ANCT) — Opening the data file If you are using the Microsoft Excel spreadsheet, a particular operation is required to open the data file: 1. Create a new Excel workbook 2. Click on the **Data tab located in the ribbon and then click from the text 3. Choose the location of the csv file and click Importer 4. In the window that opens, choose the option Delimited and in File Origin, choose 65001: Unicode UTF8. Click on Next 5. Select only the Separator Virgule. Click on Next 6. Choose the right column data format by referring to the dataset documentation. Click Finish.

The included files and script are to allow for reconstruction of the data directory and cleaned data used in "Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning" ( https://doi.org/10.1101/2022.07.29.502051 ). Code used is available at 10.5281/zenodo.7401113 .

This work was supported through funding from the USDA Agricultural Research Service, ARS project number 5070-21000-041-000-D. Raw data provided by the [Genomes to Field Initiative](https://www.genomes2fields.org/) and the [Daymet database](https://daymet.ornl.gov/).