A dataset for the 1st task Explain or teach basic data science concepts of the competition Google – AI Assistants for Data Tasks with Gemma. This dataset contains several glossaries of Data Science, where every sample contains two keys term(vocab name) and definition.

The Business Analytics Tools market is experiencing robust growth, driven by the increasing need for data-driven decision-making across diverse industries. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $150 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of big data and the need for efficient tools to analyze this data are creating significant demand. Secondly, the rising adoption of cloud-based solutions is contributing to accessibility and scalability, making these tools more affordable and user-friendly for businesses of all sizes. Finally, the growing emphasis on data security and compliance is pushing organizations to adopt sophisticated analytics tools that offer robust security features. Leading players like QlikView, Power BI, Tableau, and others are actively innovating and expanding their offerings to cater to this growing market. The market is segmented based on deployment (cloud, on-premise), industry (BFSI, healthcare, retail), and functionality (predictive analytics, descriptive analytics). Competition is fierce, with established players constantly innovating and newer entrants striving to carve a niche for themselves. Despite the positive outlook, several challenges persist. The complexity of implementing and integrating these tools can hinder adoption, particularly for smaller businesses with limited technical expertise. Data integration challenges and the need for skilled professionals to manage and interpret the insights generated also pose significant barriers. Furthermore, concerns surrounding data privacy and security remain paramount, requiring robust solutions and adherence to stringent regulations. Despite these restraints, the long-term growth prospects remain strong, fueled by the ever-increasing importance of data analytics in shaping business strategies and achieving competitive advantage. The market is expected to witness further consolidation as major players acquire smaller companies to enhance their product portfolios and expand their market reach.

The unsupervised learning market is experiencing robust growth, driven by the increasing need for businesses to extract meaningful insights from large, unstructured datasets. This market is projected to be valued at approximately $15 billion in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033. This significant expansion is fueled by several key factors. The proliferation of big data and the need for efficient data analysis are primary drivers. Businesses across various sectors, including finance, healthcare, and retail, are increasingly adopting unsupervised learning techniques like clustering and anomaly detection to identify patterns, predict customer behavior, and optimize operational efficiency. Furthermore, advancements in machine learning algorithms, improved computational power, and the availability of cloud-based solutions are further accelerating market growth. The segment dominated by cloud-based solutions is growing faster than the on-premise segment, reflecting a broader industry shift toward cloud computing and its scalability advantages. Large enterprises represent a significant portion of the market, owing to their greater resources and willingness to invest in sophisticated analytics capabilities. However, challenges remain, including the complexity of implementing and interpreting unsupervised learning models, the need for specialized expertise, and concerns regarding data privacy and security. Despite these challenges, the long-term outlook for the unsupervised learning market remains positive. The continuous evolution of machine learning algorithms and the increasing availability of user-friendly tools are expected to lower the barrier to entry for businesses of all sizes. Furthermore, the growing adoption of artificial intelligence (AI) across various industries will further fuel demand for unsupervised learning solutions. The market is witnessing considerable geographic expansion, with North America currently holding a significant market share due to the presence of major technology companies and a well-established IT infrastructure. However, other regions, particularly Asia-Pacific, are also witnessing substantial growth, driven by rapid digitalization and increasing investment in data analytics. Competition in the market is intense, with established players like Microsoft, IBM, and Google vying for market share alongside specialized vendors like RapidMiner and H2o.ai. The continued innovation and development of advanced algorithms and platforms will shape the competitive landscape in the coming years.

The Big Data Analytics Software market is projected to reach $900.3 million by 2033, exhibiting a CAGR of 8.9% from 2025 to 2033. The expanding volume of data generated across industries, coupled with the growing need for efficient data analysis and decision-making, is driving market growth. Cloud-based deployment models and the proliferation of artificial intelligence (AI) and machine learning (ML) technologies are also contributing to market growth. However, data security and privacy concerns, as well as the skills gap in big data analytics, pose challenges to market expansion. North America dominates the market, followed by Europe and Asia Pacific. Large enterprises constitute the primary customer base, leveraging big data analytics software to improve operational efficiency, customer service, and product development. Key players in the market include Sisense, Looker, Zoho Analytics, Yellowfin, Domo, Qlik Sense, GoodData, Birst, IBM, MATLAB, and Google Analytics. These companies offer a range of solutions tailored to different industry verticals and data analysis needs, driving innovation and competition in the market.

The Data Subscription Service market is experiencing robust growth, driven by the increasing demand for readily available, high-quality data across various industries. The market's value in 2025 is estimated at $15 billion, reflecting a compound annual growth rate (CAGR) of 15% from 2019. This expansion is fueled by several key factors, including the proliferation of big data, the rise of cloud computing, and the growing adoption of data analytics for informed decision-making. Companies across sectors—from finance and healthcare to retail and manufacturing—are increasingly relying on data subscription services to gain a competitive edge. This trend is further amplified by the increasing complexity of data management and the need for specialized expertise, making subscription models a cost-effective and efficient solution. Major players like Google, Amazon, Microsoft, and others are actively shaping this market, leading to increased innovation and competition, which ultimately benefits end-users. The market is segmented based on data type (e.g., financial, healthcare, IoT), deployment model (cloud, on-premises), and user type (individuals, businesses). Geographic expansion, particularly in emerging economies with rapidly developing digital infrastructure, presents significant growth opportunities. Restraints to growth could include data security and privacy concerns, along with potential regulatory hurdles related to data usage and ownership. The forecast period (2025-2033) anticipates continued strong growth, with the market expected to reach approximately $60 billion by 2033. This projection considers the sustained demand for data-driven insights, advancements in data analytics technologies, and ongoing investments in cloud infrastructure. While competition among major providers is intense, the market is largely fragmented, providing opportunities for smaller, specialized players to cater to niche requirements. Continuous innovation in data processing and analysis, alongside the development of more sophisticated data visualization tools, will be crucial factors driving further market expansion. The focus on data governance and compliance will also play a significant role, shaping market practices and influencing growth trajectory. Successfully navigating these factors will be key to success for market participants in the coming decade.

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The Indonesia Big Data Analytics Software market is experiencing robust growth, projected to reach a market size of $43.15 million in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 9.35% from 2019 to 2033. This expansion is driven by several key factors. The increasing adoption of cloud-based solutions offers scalability and cost-effectiveness, appealing to both SMEs and large enterprises. Furthermore, various end-user verticals, including manufacturing, oil and gas, retail, healthcare, and others, are increasingly leveraging big data analytics to gain valuable insights from their data, improve operational efficiency, and enhance decision-making processes. Government initiatives promoting digital transformation and technological advancement within Indonesia are also contributing significantly to market growth. The preference for on-premises solutions remains, catering to organizations with stringent data security and compliance requirements. However, this segment's growth might be comparatively slower than the cloud segment due to higher initial investment costs and ongoing maintenance needs. Competition is fierce, with established players like Teradata, SAS, SAP, Tableau, IBM, Oracle, Google, Microsoft, and Cloudera, among others, vying for market share. This competitive landscape fosters innovation and drives the development of advanced analytics solutions tailored to the specific needs of the Indonesian market. The forecast period (2025-2033) anticipates continued strong growth, fueled by increasing digitalization across industries and a rising demand for data-driven insights. While precise figures for individual market segments and regional breakdowns within Indonesia are unavailable, extrapolating from the overall market size and CAGR suggests a substantial expansion across all segments. Growth will likely be unevenly distributed, with the cloud deployment mode and large enterprise segments potentially outpacing others due to their higher adoption rates and greater budgets for advanced analytics technology. The success of individual vendors will depend on factors such as their ability to adapt to the local market’s specific needs, provide strong customer support, and offer competitive pricing and technological advancements. Recent developments include: June 2024: Indosat Ooredoo Hutchison (Indosat) and Google Cloud expanded their long-term alliance to accelerate Indosat’s transformation from telco to AI Native TechCo. The collaboration will combine Indosat’s vast network, operational, and customer datasets with Google Cloud’s unified AI stack to deliver exceptional experiences to over 100 million Indosat customers and generative AI (GenAI) solutions for businesses across Indonesia. These include geospatial analytics and predictive modeling, real-time conversation analysis, and back-office transformation. Indosat’s early adoption of an AI-ready data analytics platform exemplifies its forward-thinking approach., June 2024: Palo Alto Networks launched a new cloud facility in Indonesia, catering to the rising demand for local data residency compliance. The move empowers organizations in Indonesia with access to Palo Alto Networks' Cortex XDR advanced AI and analytics platform that offers a comprehensive security solution by unifying endpoint, network, and cloud data. With this new infrastructure, Indonesian customers can ensure data residency by housing their logs and analytics within the country.. Key drivers for this market are: Higher Emphasis on the Use of Analytics Tools to Empower Decision Making, Rapid Increase in the Generation of Data Coupled with Availability of Several End User Specific Tools due to the Growth in the Local Landscape. Potential restraints include: Higher Emphasis on the Use of Analytics Tools to Empower Decision Making, Rapid Increase in the Generation of Data Coupled with Availability of Several End User Specific Tools due to the Growth in the Local Landscape. Notable trends are: Small and Medium Enterprises to Hold Major Market Share.

The Data Science Platform market is experiencing robust growth, projected to reach $10.15 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 23.50% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume and complexity of data generated across diverse industries necessitates sophisticated platforms for analysis and insights extraction. Businesses are increasingly adopting cloud-based solutions for their scalability, cost-effectiveness, and accessibility, driving the growth of the cloud deployment segment. Furthermore, the rising demand for advanced analytics capabilities across sectors like BFSI (Banking, Financial Services, and Insurance), retail and e-commerce, and IT & Telecom is significantly boosting market demand. The availability of robust and user-friendly platforms is empowering businesses of all sizes, from SMEs to large enterprises, to leverage data science effectively for improved decision-making and competitive advantage. The market is witnessing the emergence of innovative solutions such as automated machine learning (AutoML) and integrated platforms that combine data preparation, model building, and deployment capabilities. The market segmentation reveals significant opportunities across various offerings and deployment models. While the platform segment holds a larger share, the services segment is poised for significant growth driven by the need for expert consulting and support in data science projects. Geographically, North America currently dominates the market, but the Asia-Pacific region is expected to witness faster growth due to increasing digitalization and technological advancements. Key players like IBM, Google, Microsoft, and Amazon are driving innovation and competition, with new entrants continuously emerging, adding to the market's dynamism. While challenges such as data security and privacy concerns remain, the overall market outlook is exceptionally positive, promising considerable growth over the forecast period. Continued technological innovation, coupled with rising adoption across a wider array of industries, will be central to the market's continued expansion. Recent developments include: November 2023 - Stagwell announced a partnership with Google Cloud and SADA, a Google Cloud premier partner, to develop generative AI (gen AI) marketing solutions that support Stagwell agencies, client partners, and product development within the Stagwell Marketing Cloud (SMC). The partnership will help in harnessing data analytics and insights by developing and training a proprietary Stagwell large language model (LLM) purpose-built for Stagwell clients, productizing data assets via APIs to create new digital experiences for brands, and multiplying the value of their first-party data ecosystems to drive new revenue streams using Vertex AI and open source-based models., May 2023 - IBM launched a new AI and data platform, watsonx, it is aimed at allowing businesses to accelerate advanced AI usage with trusted data, speed and governance. IBM also introduced GPU-as-a-service, which is designed to support AI intensive workloads, with an AI dashboard to measure, track and help report on cloud carbon emissions. With watsonx, IBM offers an AI development studio with access to IBMcurated and trained foundation models and open-source models, access to a data store to gather and clean up training and tune data,. Key drivers for this market are: Rapid Increase in Big Data, Emerging Promising Use Cases of Data Science and Machine Learning; Shift of Organizations Toward Data-intensive Approach and Decisions. Potential restraints include: Rapid Increase in Big Data, Emerging Promising Use Cases of Data Science and Machine Learning; Shift of Organizations Toward Data-intensive Approach and Decisions. Notable trends are: Small and Medium Enterprises to Witness Major Growth.

The global Big Data Software market, valued at $57.69 billion in 2025, is projected to experience steady growth, driven by the increasing volume of data generated across industries and the rising need for efficient data processing and analytics. The market's Compound Annual Growth Rate (CAGR) of 2.8% from 2025 to 2033 reflects a consistent demand for advanced software solutions capable of handling complex datasets and extracting actionable insights. Key drivers include the expanding adoption of cloud-based solutions offering scalability and cost-effectiveness, the growing prevalence of IoT devices generating massive amounts of data, and the increasing sophistication of Big Data analytics techniques for improved business decision-making. The market segmentation reveals strong demand across various application areas, with large enterprises leading the way due to their substantial data volumes and complex analytical requirements. However, SMEs are also adopting Big Data software at an increasing rate, driven by the availability of affordable cloud-based solutions and the realization of the competitive advantages offered by data-driven insights. Furthermore, the different software types, such as Big Data Analytics, Processing & Distribution, and Event Stream Processing, reflect the diverse needs of various businesses and industries. This diversity fuels innovation and competition within the market, leading to continuous advancements in Big Data technologies and analytical capabilities. Significant growth is expected in regions such as North America and Asia Pacific, fueled by the presence of key technology players and a high concentration of data-intensive industries. While Europe and other regions also contribute significantly, the pace of adoption might vary depending on technological maturity and regulatory factors. The competitive landscape is highly dynamic, with established players like IBM, Google, and Microsoft alongside specialized providers like Snowflake and Cloudera constantly innovating and expanding their offerings. The continuous evolution of Big Data technologies, including advancements in machine learning and artificial intelligence (AI), is expected to further drive market expansion. Competition is intense, leading to continuous innovation in pricing models, features, and integration capabilities. This competitive environment is crucial for sustaining market growth and providing organizations with robust and accessible Big Data solutions.

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The global location analysis market is experiencing robust growth, driven by the increasing adoption of location intelligence across diverse sectors. The market, valued at approximately $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This expansion is fueled by several key factors. The rise of big data and advanced analytics empowers businesses to leverage location data for improved decision-making, resulting in enhanced operational efficiency and competitive advantage. Furthermore, the burgeoning adoption of IoT devices generates massive location-based data streams, further fueling market growth. Key application areas driving demand include banking and financial services (risk assessment, branch optimization), medical and life sciences (epidemic monitoring, healthcare resource allocation), and retail and consumer goods (targeted advertising, supply chain optimization). Technological advancements, such as the integration of AI and machine learning into location analytics platforms, are also contributing to this market's upward trajectory. The market is segmented geographically, with North America currently holding a significant share, followed by Europe and Asia-Pacific. However, rapidly developing economies in Asia-Pacific, particularly India and China, are expected to witness substantial growth in the coming years, driven by increasing digitalization and infrastructure development. While the market faces some restraints, such as data privacy concerns and the high cost of implementation of advanced location analytics solutions, these challenges are anticipated to be mitigated by the development of robust data security protocols and more cost-effective solutions. The competitive landscape is characterized by the presence of both established technology giants like IBM, Google, and Oracle, and specialized location analytics providers like ESRI and TomTom, fostering innovation and competition within the market. This dynamic environment ensures a continued trajectory of growth and advancement in location analysis technologies and applications.

The Audience Analytics market, valued at $5.04 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 12.10% from 2025 to 2033. This surge is driven by several key factors. The increasing reliance on data-driven decision-making across diverse sectors like BFSI (Banking, Financial Services, and Insurance), Telecom & IT, and Retail fuels the demand for sophisticated audience analytics solutions. Furthermore, the proliferation of digital channels and the resulting explosion of user data necessitate robust analytics tools for effective marketing campaigns, improved customer experiences, and enhanced business intelligence. The rising adoption of AI and machine learning in audience analytics is further accelerating market expansion, enabling more precise targeting, personalized content delivery, and predictive modeling capabilities. Segmentation of the market by application (Sales & Marketing, Customer Experience, Other) and end-user industry allows for targeted solutions, leading to higher market penetration. North America, particularly the United States, currently holds a significant market share due to the advanced technological infrastructure and the presence of major technology companies. However, other regions like Asia and Europe are exhibiting rapid growth, indicating substantial future potential. The competitive landscape is characterized by a mix of established technology giants like Oracle, Adobe, and IBM, and specialized analytics providers. Intense competition fosters innovation and drives the development of more advanced and cost-effective solutions. While data privacy concerns and the complexity of integrating various data sources present certain challenges, the overall market trajectory remains highly positive. Continued technological advancements and the growing need for actionable insights will contribute to the sustained expansion of the audience analytics market throughout the forecast period. The market's substantial growth reflects a clear shift towards data-driven strategies across various industries, establishing audience analytics as a crucial component of modern business operations. Recent developments include: June 2024: LoopMe, a tech firm leveraging artificial intelligence (AI) to boost brand advertising outcomes, unveiled its Audience and Measurement platform (AMP). This innovative platform merges LoopMe's PurchaseLoop Audiences with its measurement tools., February 2024: LinkedIn introduced a solution aimed at deepening audience insights, streamlining the process of forecasting and enhancing campaign performance. Thanks to the platform's new Media Planning API, users can harness real-time data signals to gauge a campaign's anticipated reach and frequency, all before budget allocation.. Key drivers for this market are: Huge Demand for Personalised Content, Strong Focus on Competitive Intelligence. Potential restraints include: Huge Demand for Personalised Content, Strong Focus on Competitive Intelligence. Notable trends are: Media & Entertainment is Expected to Experience Major Market Share.

According to Cognitive Market Research, the global data analytics outsourcing market size will be USD 22634.8 million in 2025. It will expand at a compound annual growth rate (CAGR) of 36.20% from 2025 to 2033.

North America held the major market share for more than 40% of the global revenue with a market size of USD 8374.88 million in 2025 and will grow at a compound annual growth rate (CAGR) of 34.0% from 2025 to 2033.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 6564.09 million.
APAC held a market share of around 23% of the global revenue with a market size of USD 5432.35 million in 2025 and will grow at a compound annual growth rate (CAGR) of 38.2% from 2025 to 2033.
South America has a market share of more than 5% of the global revenue with a market size of USD 860.12 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.2% from 2025 to 2033.
Middle East had a market share of around 2% of the global revenue and was estimated at a market size of USD 905.39 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.5% from 2025 to 2033.
Africa had a market share of around 1% of the global revenue and was estimated at a market size of USD 497.97 million in 2025 and will grow at a compound annual growth rate (CAGR) of 35.9% from 2025 to 2033.
Banking, financial services, & insurance (BFSI) category is the fastest growing segment of the data analytics outsourcing industry

Market Dynamics of Data Analytics Outsourcing Market

Key Drivers for Data Analytics Outsourcing Market

Rising Demand for Customer-Centric Solutions to Boost Market Growth

The growing emphasis on personalized customer experiences is a major driver of the data analytics outsourcing market. Businesses increasingly rely on advanced analytics to understand customer behaviour, preferences, and purchasing patterns. Outsourcing enables access to specialized expertise and tools that help derive actionable insights from complex datasets. These insights allow companies to tailor products, services, and marketing strategies to individual customer needs, enhancing satisfaction and loyalty. As competition intensifies across industries, customer-centricity becomes a key differentiator, driving demand for outsourced analytics services that offer agility, accuracy, and faster time-to-market for customer-driven innovations. In June 2023, Genpact, a global professional services company focused on delivering outcomes that transform businesses, declared it is working with Google Cloud to assist businesses accelerate artificial intelligence (AI) strategies, such as taking advantage of generative AI's adoption to drive actionable business insights.

https://genpact.gcs-web.com/news-releases/news-release-details/genpact-teams-google-cloud-accelerate-artificial-intelligence

Advancement in Technology to Boost Market Growth

Technological advancements are a key driver in the data analytics outsourcing market, enabling faster, more accurate, and scalable analytics solutions. Innovations in artificial intelligence (AI), machine learning (ML), big data platforms, and cloud computing have transformed how data is collected, processed, and interpreted. These technologies allow outsourcing firms to offer sophisticated analytics capabilities at lower costs and with higher efficiency. Real-time analytics, automation of data workflows, and predictive modelling are now more accessible, empowering businesses to gain deeper insights quickly. As a result, companies increasingly outsource to leverage these advanced tools without building in-house infrastructure.

Restraint Factor for the Data Analytics Outsourcing Market

High Cost of Investment Will Limit Market Growth

The high cost of investment in data analytics outsourcing acts as a significant restraint in the market. While outsourcing analytics can offer cost savings in the long run, the initial investment in setting up proper data infrastructure, integrating advanced technologies like AI and machine learning, and maintaining secure cloud platforms can be substantial. Smaller businesses or those with limited budgets may find it challenging to afford such investments. Additionally, the cost of hiring skilled professionals from outsourcing firms with expertise in advanced analytics tools and techniques can also add to the overall financial burden, slowing market adoption.

Market Tren...

The immersive analytics software market, valued at $453 million in 2025, is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 33.2% from 2025 to 2033. This explosive growth is fueled by several key drivers. The increasing adoption of virtual and augmented reality (VR/AR) technologies across diverse sectors, including healthcare, education, and business applications, is significantly boosting demand. Businesses are leveraging immersive analytics to gain crucial insights from complex datasets through interactive visualizations, leading to improved decision-making and enhanced operational efficiency. Furthermore, the rising need for data-driven insights in public policy decisions and the growing accessibility of VR/AR devices are accelerating market expansion. The market is segmented by application (business applications, education, public policy decisions, healthcare, and others) and device type (PC, Mac, iOS, and VR/AR devices). While significant growth is anticipated across all segments, business applications and healthcare currently hold considerable market share due to their immediate need for data-driven solutions and the potential for improved patient care and treatment planning. Geographic expansion is another significant factor, with North America and Europe currently dominating the market, but significant growth potential exists in rapidly developing economies in Asia-Pacific and other regions. Competition in the immersive analytics software market is intensifying, with major players like Microsoft, IBM, Google, and SAP alongside specialized firms like Immersion Analytics and Magic Leap. This competitive landscape encourages innovation and the development of sophisticated features that cater to the evolving needs of diverse industries. However, challenges remain, including the high initial investment costs associated with implementing VR/AR technologies and the need for skilled professionals to manage and interpret data visualizations effectively. Despite these challenges, the overall market outlook for immersive analytics software remains highly positive, driven by sustained technological advancements, expanding applications, and increasing global adoption across a wide array of sectors. The market's future will be defined by the development of more user-friendly interfaces, increased integration with existing business intelligence (BI) platforms, and the proliferation of affordable VR/AR hardware.

Explore our public notebook content!

Meta Kaggle Code is an extension to our popular Meta Kaggle dataset. This extension contains all the raw source code from hundreds of thousands of public, Apache 2.0 licensed Python and R notebooks versions on Kaggle used to analyze Datasets, make submissions to Competitions, and more. This represents nearly a decade of data spanning a period of tremendous evolution in the ways ML work is done.

Why we’re releasing this dataset

By collecting all of this code created by Kaggle’s community in one dataset, we hope to make it easier for the world to research and share insights about trends in our industry. With the growing significance of AI-assisted development, we expect this data can also be used to fine-tune models for ML-specific code generation tasks.

Meta Kaggle for Code is also a continuation of our commitment to open data and research. This new dataset is a companion to Meta Kaggle which we originally released in 2016. On top of Meta Kaggle, our community has shared nearly 1,000 public code examples. Research papers written using Meta Kaggle have examined how data scientists collaboratively solve problems, analyzed overfitting in machine learning competitions, compared discussions between Kaggle and Stack Overflow communities, and more.

The best part is Meta Kaggle enriches Meta Kaggle for Code. By joining the datasets together, you can easily understand which competitions code was run against, the progression tier of the code’s author, how many votes a notebook had, what kinds of comments it received, and much, much more. We hope the new potential for uncovering deep insights into how ML code is written feels just as limitless to you as it does to us!

Sensitive data

While we have made an attempt to filter out notebooks containing potentially sensitive information published by Kaggle users, the dataset may still contain such information. Research, publications, applications, etc. relying on this data should only use or report on publicly available, non-sensitive information.

Joining with Meta Kaggle

The files contained here are a subset of the KernelVersions in Meta Kaggle. The file names match the ids in the KernelVersions csv file. Whereas Meta Kaggle contains data for all interactive and commit sessions, Meta Kaggle Code contains only data for commit sessions.

File organization

The files are organized into a two-level directory structure. Each top level folder contains up to 1 million files, e.g. - folder 123 contains all versions from 123,000,000 to 123,999,999. Each sub folder contains up to 1 thousand files, e.g. - 123/456 contains all versions from 123,456,000 to 123,456,999. In practice, each folder will have many fewer than 1 thousand files due to private and interactive sessions.

The ipynb files in this dataset hosted on Kaggle do not contain the output cells. If the outputs are required, the full set of ipynbs with the outputs embedded can be obtained from this public GCS bucket: kaggle-meta-kaggle-code-downloads. Note that this is a "requester pays" bucket. This means you will need a GCP account with billing enabled to download. Learn more here: https://cloud.google.com/storage/docs/requester-pays

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The Content Analytics Market is experiencing robust growth, projected to reach $6.25 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 11.01% from 2025 to 2033. This expansion is fueled by several key drivers. The increasing volume of unstructured data generated across various sources like social media, customer interactions, and operational systems necessitates sophisticated analytics for actionable insights. Businesses across sectors are increasingly adopting content analytics to improve customer experience, optimize operational efficiency, and gain a competitive edge. Specifically, the demand for real-time insights from social media analytics and the rise of AI-powered sentiment analysis are significant catalysts. Furthermore, the growing adoption of cloud-based deployment models offers scalability and cost-effectiveness, contributing to market expansion. While data security and privacy concerns pose a restraint, the market is adapting with robust security protocols and compliance measures. The BFSI and Healthcare sectors are leading adopters, driven by the need for risk management, customer relationship improvement, and regulatory compliance. Other significant segments include Retail & Consumer Goods, IT & Telecom, and Manufacturing, each leveraging content analytics for specific applications like brand monitoring, customer service enhancement, and predictive maintenance. The competition is intense, with established players like Oracle, Google, IBM, and SAP competing alongside specialized analytics providers. The market's future growth hinges on several factors. Continued advancements in artificial intelligence and machine learning will enhance the accuracy and efficiency of content analytics platforms. The integration of content analytics with other technologies, such as big data and business intelligence tools, will further drive adoption. Expansion into emerging markets, particularly in the Asia-Pacific region, represents a significant opportunity. However, challenges remain, including the need for skilled professionals to manage and interpret the complex data generated by these systems and the need for ongoing investments in research and development to maintain a competitive edge in this rapidly evolving technological landscape. The shift towards more sophisticated analytics techniques like natural language processing (NLP) and deep learning will continue to reshape the market landscape, creating opportunities for innovative solutions and driving further growth. Recent developments include: October 2023 : Oracle NetSuite announced the latest updates to NetSuite Analytics Warehouse the first and only AI-enabled, prebuilt cloud A data warehouse and an analytics solution for NetSuite customers. The latest updates will help companies to improve the management of data, enabling customers to quickly create analyses that increase efficiency and decrease costs, gain a better knowledge of their customer as well as make it easier for them to innovate and grow faster., November 2022: In order to assist businesses in quickly making data-driven decisions and dealing with unforeseen disruptions, IBM launched new software that is intended to help organizations break down data and analytics silos. This package comprises IBM Cognos Analytics with Watson and IBM Planning Analytics with Watson, in addition to a new IBM Analytics Content Hub that makes it simpler for customers to find and access analytics and planning solutions from many suppliers in a single, customized dashboard view.IBM Business Analytics Enterprise incorporates a new IBM Analytics Content Hub, expanding on IBM's current portfolio of business intelligence capabilities., September 2022: Azena launched updates to its open platform for smart cameras that give smart cameras greater integration possibilities into current video surveillance systems and tools for more effective device management for systems integrators. Integrators using the Azena platform and the AI-enabled video analytics from the Azena Application Store now have greater control over huge groups of devices, apps, and settings operating on their clients' smart cameras with the Azena Operating System due to this deeper feature.. Key drivers for this market are: Growing Demand for Social Media Analytics, Rising Practice of Predictive Analytics; Rise in Highly Customized and Industry-Specific Applications. Potential restraints include: Growing Demand for Social Media Analytics, Rising Practice of Predictive Analytics; Rise in Highly Customized and Industry-Specific Applications. Notable trends are: Video Analytics to have a significant growth rate.

The Internet of Things (IoT) Data Management market is experiencing robust growth, projected to reach a significant size by 2033. A Compound Annual Growth Rate (CAGR) of 16.58% from 2019 to 2033 indicates substantial expansion driven by several key factors. The increasing number of connected devices generating massive volumes of data necessitates efficient and scalable data management solutions. Furthermore, the rising demand for real-time analytics and insights from IoT data across diverse industries fuels market expansion. Automotive, healthcare, and manufacturing sectors are leading adopters, leveraging IoT data for improved operational efficiency, predictive maintenance, and enhanced customer experiences. The market is segmented by solution (integration, migration, analytics, storage, security) and end-user, reflecting the diverse applications and technological components involved. While challenges such as data security and interoperability exist, ongoing technological advancements and increasing regulatory compliance initiatives are likely to mitigate these restraints. Companies such as SAP, IBM, PTC, Cisco, and others are at the forefront of providing sophisticated solutions, driving innovation and competition within the market. The North American region currently holds a significant market share, but the Asia-Pacific region is poised for rapid growth due to increasing digitalization and industrial automation. The forecast period (2025-2033) promises continued expansion, with significant opportunities for players who can offer comprehensive, secure, and scalable solutions. The market's growth is intertwined with the overall advancement of IoT technology and the broader digital transformation underway across various industries. As more organizations adopt IoT technologies, the demand for effective data management solutions will continue to escalate. This growth will be influenced by factors such as the increasing adoption of cloud-based solutions, the development of advanced analytics capabilities, and a growing focus on data security and privacy. The competition in this rapidly evolving market is intense, with established players and new entrants vying for market share through innovation and strategic partnerships. Key drivers for this market are: , Proliferation of Connected Devices and Snowballing Growth in Data Volumes; Need for Data Security and Data Traffic Management. Potential restraints include: , Proliferation of Connected Devices and Snowballing Growth in Data Volumes; Need for Data Security and Data Traffic Management. Notable trends are: Security Solutions to Witness the Fastest Growth.

The GPU cloud server rental market is experiencing robust growth, driven by increasing demand for high-performance computing (HPC) resources across diverse sectors. The market's expansion is fueled by the rising adoption of AI, machine learning, deep learning, and data analytics, all of which require substantial computational power readily accessible through cloud-based GPU servers. The shift towards cloud computing, offering scalability, cost-effectiveness, and on-demand access to powerful resources, is a primary catalyst. Major cloud providers like AWS, Azure, and Google Cloud are actively expanding their GPU offerings, fostering competition and driving innovation. While the initial investment in infrastructure can be significant, the operational efficiency and reduced capital expenditure associated with cloud-based solutions are attractive to businesses of all sizes, from startups to large enterprises. Furthermore, advancements in GPU technology, leading to increased processing power and efficiency, contribute to market expansion. However, factors such as data security concerns, latency issues in certain regions, and the potential for fluctuating pricing models pose challenges to widespread adoption. The market's compound annual growth rate (CAGR) is expected to remain strong, reflecting the continuous growth in data volume and the increasing complexity of computational tasks. This growth is not uniform across all regions, with North America and Europe currently holding significant market share due to established technological infrastructure and a higher concentration of businesses utilizing HPC resources. However, regions like Asia-Pacific are witnessing rapid growth, driven by expanding technological adoption and a burgeoning demand for AI and data analytics services. Competition is fierce among established cloud providers and emerging players, leading to innovation in pricing models, service offerings, and technological advancements. This competitive landscape is ultimately beneficial to consumers, driving down costs and improving the overall quality of services available. The forecast period indicates a sustained market expansion, with the market size predicted to significantly increase.

The Content Analytics Software market is experiencing robust growth, driven by the increasing need for businesses to understand and optimize their content performance across various digital channels. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the rise of digital marketing and the consequent explosion of online content necessitates sophisticated analytics tools to measure effectiveness and ROI. Secondly, the growing adoption of cloud-based solutions offers scalability, cost-effectiveness, and accessibility to businesses of all sizes. Thirdly, the increasing focus on personalization and data-driven decision-making further bolsters market demand. Large enterprises are currently the dominant segment, but the SME sector shows significant growth potential as these businesses increasingly recognize the value of content analytics for improved marketing and sales outcomes. While the market faces challenges such as data privacy concerns and the complexity of integrating various analytics platforms, the overall trend points toward continued expansion and innovation in the sector. The competitive landscape is characterized by a blend of established players like Google Analytics and SEMrush, along with emerging specialized solutions. The market is witnessing increased competition from both large, established technology companies and nimble startups. The geographical distribution shows strong growth across North America and Europe, followed by Asia-Pacific. However, emerging markets in regions like the Middle East and Africa also present considerable untapped potential. The ongoing trend toward Artificial Intelligence (AI) and Machine Learning (ML) integration within content analytics platforms promises further efficiency improvements and insightful data analysis for clients, further pushing market expansion. This integration enhances predictive capabilities, allowing businesses to proactively adapt their content strategies and improve performance.

The data discovery market, projected at $XX million in 2025, is experiencing robust growth, fueled by a compound annual growth rate (CAGR) of 21%. This expansion is driven by several key factors. The increasing volume and complexity of data generated by businesses across diverse sectors necessitate efficient tools for data analysis and insights extraction. The rise of big data analytics and the growing adoption of cloud-based solutions are further propelling market growth. Businesses across industries, particularly Banking, Financial Services, and Insurance (BFSI), Telecommunications and IT, and Retail and E-commerce, are increasingly recognizing the value of data-driven decision-making, leading to higher adoption rates of data discovery platforms. The market is segmented by component (software and services), enterprise size (SMEs and large enterprises), and industry vertical, with each segment contributing uniquely to overall market dynamics. While the market faces challenges such as the need for skilled professionals and the complexity of integrating data from disparate sources, the overall trend suggests sustained growth, driven by the continuous rise in data generation and the expanding need for actionable insights. The competitive landscape is characterized by a mix of established players like Tableau, SAP, and Oracle, and emerging innovative companies. This competition fosters innovation and drives down costs, making data discovery solutions more accessible to a broader range of businesses. While North America currently holds a significant market share, regions like Asia Pacific are expected to witness rapid growth driven by increasing digitalization and adoption of advanced analytics. The forecast period (2025-2033) anticipates sustained growth, though the rate of expansion may gradually moderate as the market matures. The market's future trajectory will depend on factors such as technological advancements, regulatory changes, and the overall economic climate. Continued investment in research and development, coupled with strategic partnerships and acquisitions, will be key to success in this dynamic and rapidly evolving market. Recent developments include: August 2022: CoreLogic, a major global provider of analytics-driven and property data solutions, expanded its partnership with Google Cloud to assist in the introduction of its novel CoreLogic Discovery Platform. Discovery Platform, which is fully built on Google Cloud's safe and sustainable technology, offers a complete asset analytics platform and cloud-based data interchange for enterprises in a variety of industries., June 2022: Select Star established an official collaboration with dbt Labs. Dbt has been one of Select Star's most significant integrations, with over 15,000 models and 225,000 columns linked up to date. Select Star is intended to facilitate the data discovery required by companies in order to harness the potential of their data and generate effective outcomes. As a result, Select Star and Dbt Labs have a shared goal, to empower analytics engineers to convert information better and keep appropriate documentation so that business users and data analysts can trust their data., June 2022: TD SYNNEX's SNX Tech Data established a collaboration with Instructure INST, a Learning Management Systems ("LMS") company, to utilize advanced learning capabilities in India. TD SYNNEX earned a substantial advantage with this deal, in addition to developing its data, Internet of Things, and analytics products. By enabling end-to-end business analytics powered by self-service data discovery, corporate reporting, mobile apps, and embedded analytics, TD SYNNEX's partners were able to offer complete business analytics propelled by data-driven business culture.. Key drivers for this market are: Increasing Number of Multi-Structured Data Sources, Growing Importance for Data-Driven Decision-Making. Potential restraints include: Increasing Number of Multi-Structured Data Sources, Growing Importance for Data-Driven Decision-Making. Notable trends are: The Banking, Financial Services, and Insurance Sector Holds a Dominant Position.