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TwitterThe total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly. While it was estimated at ***** zettabytes in 2025, the forecast for 2029 stands at ***** zettabytes. Thus, global data generation will triple between 2025 and 2029. Data creation has been expanding continuously over the past decade. In 2020, the growth was higher than previously expected, caused by the increased demand due to the coronavirus (COVID-19) pandemic, as more people worked and learned from home and used home entertainment options more often.
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TwitterIn 2022, China's big data industry grew by almost ** percent compared to the previous year, exceeding a market size of *** trillion yuan. The Chinese government has plans to transform the country into a global technology leader and big data is one important vector in this development.
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Data Analytics Outsourcing Market size was valued at USD 10.2 Billion in 2024 and is projected to reach USD 55.44 Billion by 2032, growing at a CAGR of 26% from 2026 to 2032. Global Data Analytics Outsourcing Market DriversGrowing Volume of Big Data: The increasing volume of big data is leading firms to outsource analytics. According to IDC, the global datasphere is expected to increase from 33 zettabytes in 2018 to 175 zettabytes by 2025. This tremendous rise in data volume has compelled firms to seek external expertise for efficient data management and analytics.Cost-Effectiveness of Outsourcing: Outsourcing data analytics can be more cost-effective than having an in-house team. According to a Deloitte poll, 59% of organizations outsource primarily to save money. According to the same poll, 47% of organizations saved between 10 and 25% of their costs through outsourcing.Shortage of Skilled Data Professionals: Due to a shortage of experienced data analytics workers, organizations are increasingly outsourcing. The U.S. Bureau of Labor Statistics predicts that employment of data scientists and mathematical scientific occupations will expand 31% between 2019 and 2029, substantially faster than the national average, indicating a significant skills gap.
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According to Cognitive Market Research, the global WiFi Analystics Solution market size will be USD XX million in 2025. It will expand at a compound annual growth rate (CAGR) of XX% from 2025 to 2031.
North America held the major market share for more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Europe accounted for a market share of over XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Asia Pacific held a market share of around XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Latin America had a market share of more than XX% of the global revenue with a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. Middle East and Africa had a market share of around XX% of the global revenue and was estimated at a market size of USD XX million in 2025 and will grow at a CAGR of XX% from 2025 to 2031. KEY DRIVERS
Rise in Smart Device Adoption with Emergence of Cloud-Based Solutions Driving Wi-Fi Analytics Market Growth
The rise in smart device adoption, combined with the emergence of cloud-based solutions, is a significant driver of growth in the Wi-Fi analytics market. With the widespread use of smartphones, tablets, and IoT devices, businesses are increasingly turning to Wi-Fi analytics to gather actionable insights from connected users. This demand for data-driven decision-making stems from the need to understand customer behavior, optimize services, and enhance user engagement. For instance, retail chains like Starbucks employ Wi-Fi analytics to monitor customer visits, analyze dwell times, and identify peak hours.(https://www.forbes.com/sites/bernardmarr/2018/05/28/starbucks-using-big-data-analytics-and-artificial-intelligence-to-boost-performance/) This allows them to launch targeted marketing campaigns, improve store layouts, and ultimately increase customer retention and revenue. The proliferation of smart devices acts as a catalyst, making it easier for businesses to collect rich behavioral data through Wi-Fi networks. Wi-Fi analytics also holds transformative potential across a variety of industries beyond retail. In hospitality, hotels use these tools to capture guest data, such as visit frequency and service preferences—allowing for personalized experiences and improved guest satisfaction. Similarly, airports apply Wi-Fi analytics to track passenger flow, reduce congestion, and streamline check-in processes, contributing to operational efficiency. These insights are becoming increasingly accurate with the integration of advanced technologies like machine learning, which helps predict consumer behavior and refine service offerings. Furthermore, the adoption of cloud-based platforms enhances the scalability and accessibility of Wi-Fi analytics, making it a viable solution for sectors like healthcare, theme parks, and restaurants. These platforms enable real-time data processing and remote access, allowing businesses to remain agile and cost-effective while responding to dynamic customer needs. Thus, the synergy between smart device adoption and cloud computing is not only fueling market expansion but also transforming how industries operate and interact with consumers. Restraints
High initial investment hinders the Wi-Fi Analytics Market Growth
The Wi-Fi analytics market is significantly restrained by several key challenges, most notably high initial investment costs and rising concerns around data privacy and security. Small and medium-sized businesses often struggle to afford the implementation of advanced analytics platforms, which limits widespread adoption. Additionally, increasing regulatory pressure from laws like GDPR and CCPA requires businesses to handle customer data transparently and securely. High-profile incidents, such as Google's 2018 location tracking controversy(https://www.ncesc.com/geographic-faq/what-is-the-google-location-tracking-controversy/#:~:text=Yes%2C%20Google%20has%20reached%20a%20%2493%20million%20settlement,practices%20and%20its%20tracking%20of%20users%E2%80%99%20location%20information.) and the Equifax data breach in 2017,( https://www.csoonline.com/article/567833/equifax-data-breach-faq-what-happened-who-was-affected-what-was-the-impact.html) have heightened public and regulat...
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ABSTRACT Approximately 4 billion people have access to the Internet, additionally 23 billion devices are connected as of 2018. This has allowed for a substantial growth in data collection which has allowed for Big Data to flourish. The continued increase in user, devices, and Big Data usage has created a significant intensification in Internet traffic. This in turn has the potential to increase user delays when accessing data on the Internet. There are a number of ways to help reduce user latency, web caching is able to reduce web user delays in addition to reducing network traffic and the load on web servers. In this study we propose a proxy level web caching mechanism leveraging historical web patterns to help reduce user latency and accelerate the Internet. In addition we survey the state of the art of other caching approaches. Our investigation shows that using historical patterns as part of a proxy caching mechanisms in large scale networks can significantly shorten the latency for users in this era of Big Data.
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Data Center Network Architecture Market size was valued at USD 35.13 Billion in 2024 and is projected to reach USD 65.51 Billion by 2032, growing at a CAGR of 8.1% during the forecast period 2026 to 2032.Rapid Growth of Cloud Computing: The adoption of cloud services is rapidly increasing which boosts demand for scalable and flexible data center networks. According to the U.S. Census Bureau, cloud computing revenue grew over 20% annually from 2018 to 2023.Rising Data Traffic and Big Data Analytics: Data from IoT, social media, and enterprises is growing explosively. IDC estimates that by 2025, global data creation will reach 175 zettabytes. This increase drives the need for scalable and robust data center network architectures.
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TwitterThe global market research industry reached a record high market size of approximately ** billion U.S. dollars in 2023. Over the last decade, the global market research industry has performed contrary to broader economic trends as the industry has continued to grow. Figures for 2023 signaled an increase of about *** billion U.S. dollars compared to the previous year. Market research industryMarket research is the activity of gathering information about markets in which an organization sells their produces and/or services. This often includes detailed qualitative understandings of consumer attitudes and preferences through tools such interviews, surveys, and increasingly, big-data analytics. The leading market research company worldwide was U.S.-based Gartner in 2022. Slow growth in EuropeWhile growth in the United States has been significant, the revenue of the market research industry in Europe grew just slightly since 2014. Some analysts expect this poor performance to continue into the near future for *** reasons. First is the short- and mid-term uncertainty created by Brexit, impacting the reliability of any market research conducted prior to the issue being resolved. Second is the implementation of the EU General Data Protection Regulation (GDPR) laws in May 2018, which limit what companies are able to do with personal data. A majority of IT professionals in France, Germany and the UK agree the GDPR laws will prevent personal data being passed on to third parties, reducing the amount of data available to researchers in Europe compared to other regions.
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Hybrid Memory Cube and High Bandwidth Memory Market Size and Forecast
Hybrid Memory Cube and High Bandwidth Memory Market size was valued at USD 3.62 Billion in 2024 and is projected to reach USD 27.28 Billion by 2031, growing at a CAGR of 31.70% from 2024 to 2031.
Global Hybrid Memory Cube (HMC) And High-Bandwidth Memory (HBM) Market Drivers
Increasing Demand for High-performance Computing: The increased demand for quicker data processing and analysis in sectors such as artificial intelligence, machine learning, and big data propels the use of HMC and HBM technologies. According to research from the United States Department of Energy, high-performance computing workloads are expected to expand by 20-30% each year until 2025, needing more modern memory solutions.
Rising Popularity of Data-Intensive Applications: The expansion of data-intensive applications in finance, healthcare, and scientific research is driving up demand for high-bandwidth memory systems. According to a study conducted by the International Data Corporation (IDC), the global datasphere will rise from 33 zettabytes in 2018 to 175 zettabytes by 2025, reflecting a 61% compound annual growth rate.
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The Global Plastics extrusion market is valued at USD 119.97 Billion in 2018 and is expected to reach USD 202.21 Billion by the end of 2030, growing at a CAGR of 6.72% between 2023 and 2030.
The North America Plastics Extrusion market size was USD 3,386.51 Billion in 2018 and it will be USD 4,769.83 Billion in 2030.
The Europe Plastics Extrusion market size was USD 32.57 Billion in 2018 and it will be USD 52.68 Billion in 2030.
Market Dynamics of the Plastics Extrusion Market
Market Drivers of the Plastics Extrusion Market
The Growing Automotive Sector is Driving the Plastics Extrusion Market.
In both North America and Europe, the growing automotive sector has emerged as a significant driver of the plastics extrusion business. As these regions' automotive sectors expand rapidly, the need for plastic extrusion components has increased significantly. Plastics extrusion, a manufacturing technique that includes molding raw plastic materials into a continuous shape, is widely used in the automotive sector to produce components such as pipes, hoses, weather stripping, and window seals.
The automotive industry in North America has been on a rise, driven by factors such as technical innovations, rising consumer demand for fuel-efficient vehicles, and a recovery in manufacturing activity. The adaptability, durability, and cost-effectiveness of plastics extrusion promote its use in the automobile industry.
The automotive sector in the United States will generate roughly 10.06 million motor vehicles in 2022. Passenger automobiles, light commercial vehicles, big trucks, and buses and coaches are all included in the data. This increase in the automotive sector in North America would also propel the demand for the plastic extrusion market due to its growing application.
Similarly, the automotive industry is the foundation of the Europe industrial landscape. To be competitive in the global market, European automakers are at the forefront of innovation, using modern materials and production processes. Plastics extrusion has become an essential component of this strategy, enabling for the manufacturing of complicated and precisely designed components that match the automobile industry's high standards of quality. For instance, the automotive sector employs 13.8 million
Europeans directly and indirectly, accounting for 6.1% of total EU employment. Direct production of motor vehicles employs 2.6 million people, accounting for 8.5% of manufacturing employment in the EU. This rise would result in more application of plastic extrusion in this sector resulting in greater demand for this market.
Growing Application of Extruded Plastics in Different Industries.
The plastics extrusion market in North America and Europe is expanding rapidly due to the increasing use of extruded plastics in a variety of sectors. This increase in demand can be attributed to extruded plastics' diverse qualities, which make them an effective option for a wide range of applications. Extrusion includes melting raw plastic material and molding it into a continuous profile, producing products with consistent cross-sections.
The rising use of extruded plastics in the construction sector is one of the primary drivers for the plastics extrusion market in these areas. For instance, in the first quarter of 2023, there were about 919000 construction establishments in the United States. Similarly, most European countries' construction sectors will account for 4% to 7% of their GDP in 2022. Extruded plastic goods, such as pipes, profiles, and sheets, are widely used in construction applications because they provide advantages such as durability, corrosion resistance, and ease of installation. The construction industry's dependence on these materials for applications such as window profiles, door frames, and plumbing systems is driving the plastics extrusion market further.
The growing production of lighting, cables, wires and HVAC has also resulted in the growing application of extruded plastics.
From 2018 to 2023, the HVAC sector in the United States increased with revenue growing from $90.3 billion in 2018 to $123.2 billion in 2023. The greater number of established companies would result in the increased production of HVAC industry, which will result in the growth of plastics extrusion market.
Market Restraints of the Plastics Extrusion Market
G...
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TwitterIn 2024, the revenue change in the 'Games' segment of the media market worldwide was modeled to amount to 10.91 percent. Between 2018 and 2024, the figure dropped by 70.2 percentage points, though the decline followed an uneven course rather than a steady trajectory. The forecast shows the revenue change will steadily decline by 4.85 percentage points from 2024 to 2030.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Games.
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TwitterTrend-based projections Four variants of trend-based population projections and corresponding household projections are currently available to download. These are labelled as High, Central and Low and differ in their domestic migration assumptions beyond 2017. The economic crisis has been linked to a fall in migration from London to the rest of the UK and a rise in flows from the UK to London. The variants reflect a range of scenarios relating to possible return to pre-crisis trends in migration. High: In this scenario, the changes to domestic migration flows are considered to be structural and recent patterns persist regardless of an improving economic outlook. Low: Changes to domestic migration patterns are assumed to be transient and return to pre-crisis trends beyond 2018. Domestic outflow propensities increase by 10% and inflows decrease by 6% as compared to the High variant. Central: Assumes recent migration patterns are partially transient and partially structural. Beyond 2018, domestic outlow propensities increase by 5% and inflows by 3% as compared to the High variant. Central - incorporating 2012-based fertility assumptions: Uses the same migration assumptions as the Central projeciton above, but includes updated age-specific-fertility-rates based on 2011 birth data and future fertility trends taken from ONS's 2012-based National Population Projections. The impact of these changes is to increase fertility by ~10% in the long term. GLA 2013 round trend-based population projections: Borough: High Borough: Low Borough: Central Borough: Central - incorporating 2012-based NPP fertility assumptions Ward: Central GLA 2013 round trend-based household projections: Borough: High Borough: Low Borough: Central GLA 2013 round ethnic group population projections: Borough: Central Updates: Update 03-2014: GLA 2013 round of trend-based population projections - Methodology Update 04-2014: GLA 2013 round of trend-based population projections - Results Data to accompany Update 04-2014 Update 12-2014: GLA 2013 round ethnic group population projections Data to accompany Update 12-2014 Housing linked projections Two variants of housing-linked projections are available based on housing trajectories derived from the 2013 Strategic Housing Land Availability Assessment (SHLAA). The two variants are produced using different models to constrain the population to available dwellings. These are referred to as the DCLG-based model and the Capped Household Size model. These models will be explained in greater detail in an upcoming Intelligence Unit Update. Projection Models: DCLG-Based Model This model makes use of Household Representative Rates (HRR) from DCLG's 2011-based household projections to convert populations by age and gender into households. The models uses iteration to find a population that yields a total number of households that matches the number of available household spaces implied by the development data. This iterative process involves modulating gross migration flows between each London local authority and UK regions outside of London. HRRs beyond 2021 have been extrapolated forward by the GLA. The model also produces a set of household projections consistent with the population outputs. Capped Household Size Model This model was introduced to provide an alternative projection based on the SHLAA housing trajectories. While the projections given by the DCLG-Based Model appear realistic for the majority of London, there are concerns that it could lead to under projection for certain local authorities, namely those in Outer London where recent population growth has primarily been driven by rising household sizes. For these boroughs, the Capped Household Size model provides greater freedom for the population to follow the growth patterns shown in the Trend-based projections, but caps average household size at 2012 levels. For boroughs where the DCLG-based SHLAA model gave higher results than the Trend-based model, the projections follow the results of the former. Household projections are not available from this model. Development assumptions: SHLAA housing data These projections incorporate development data from the 2013 Strategic Housing Land Availability Assessment (SHLAA) database to determine populations for 2012 onwards. Development trajectories are derived from this data for four phases: 2015-20, 2021-25, 2026-30, and 2031-36. For 2012-14, data is taken from the 2009 SHLAA trajectories. No data is included in the database for beyond 2036 and the 2031-36 trajectories are extended forward to 2041. This data was correct as at February 2014 and may be updated in future. Assumed development figures will not necessarily match information in the SHLAA report as some data on estate renewals is not included in the database at this time. GLA 2013 round SHLAA-based population projections: Borough: SHLAA-based Borough: capped SHLAA-based Ward: SHLAA-based Ward: capped SHLAA-based GLA 2013 round SHLAA-based household projections: Borough: SHLAA-based GLA 2013 round SHLAA-based ethnic group population projections: Borough: SHLAA-based Zero-development projections The GLA produces so-called zero-development projections for London that assume that future dwelling stocks remain unchanged. These projections can be used in conjunction with the SHLAA-based projections to give an indication of the modelled impact of the assumed development. Variants are produced consistent with the DCLG-based and Capped Household Size projections. Due to the way the models operate, the former assumes no development beyond 2011 and the latter no development after 2012. GLA 2013 round zero development population projections: Borough: DCLG zero development Borough: capped zero development Ward: DCLG zero development Ward: capped zero development Frequently asked question: which projection should I use? The GLA Demography Team recommends using the Capped Household Size SHLAA projection for most purposes. The main exception to this is for work estimating future housing need, where it is more appropriate to use the trend-based projections. The custom-age population tool is here. To access the GLA's full range of demographic projections please click here.
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TwitterIn the games market worldwide in 2024, cloud gaming recorded the strongest revenue growth at approximately 59.41 percent. The games live streaming segment followed with growth of around 16.68 percent, while in-game advertising ranked third with an estimated 15.97 percent increase in revenue.
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I created this dataset as part of a data analysis project and concluded that it might be relevant for others who are interested in examining in analyzing content on YouTube. This dataset is a collection of over 6000 videos having the columns:
Comments: comments count for the video
Through the YouTube API and using Python, I collect data about some of these popular channels' videos that provide educational content about Machine Learning and Data Science in order to extract insights about which topics had been popular within the last couple of years. Featured in the dataset are the following creators:
Krish Naik
Nicholas Renotte
Sentdex
DeepLearningAI
Artificial Intelligence — All in One
Siraj Raval
Jeremy Howard
Applied AI Course
Daniel Bourke
Jeff Heaton
DeepLearning.TV
Arxiv Insights
These channels are features in multiple top AI channels to subscribe to lists and have seen a big growth in the last couple of years on YouTube. They all have a creation date since or before 2018.
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TwitterThe total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly. While it was estimated at ***** zettabytes in 2025, the forecast for 2029 stands at ***** zettabytes. Thus, global data generation will triple between 2025 and 2029. Data creation has been expanding continuously over the past decade. In 2020, the growth was higher than previously expected, caused by the increased demand due to the coronavirus (COVID-19) pandemic, as more people worked and learned from home and used home entertainment options more often.