Daily utilization metrics for data.lacity.org and geohub.lacity.org. Updated monthly

In the second quarter of 2025, mobile devices (excluding tablets) accounted for 62.54 percent of global website traffic. Since consistently maintaining a share of around 50 percent beginning in 2017, mobile usage surpassed this threshold in 2020 and has demonstrated steady growth in its dominance of global web access. Mobile traffic Due to low infrastructure and financial restraints, many emerging digital markets skipped the desktop internet phase entirely and moved straight onto mobile internet via smartphone and tablet devices. India is a prime example of a market with a significant mobile-first online population. Other countries with a significant share of mobile internet traffic include Nigeria, Ghana and Kenya. In most African markets, mobile accounts for more than half of the web traffic. By contrast, mobile only makes up around 45.49 percent of online traffic in the United States. Mobile usage The most popular mobile internet activities worldwide include watching movies or videos online, e-mail usage and accessing social media. Apps are a very popular way to watch video on the go and the most-downloaded entertainment apps in the Apple App Store are Netflix, Tencent Video and Amazon Prime Video.

Snapshot img

Global network traffic analytics Industry Overview

Technavio’s analysts have identified the increasing use of network traffic analytics solutions to be one of major factors driving market growth. With the rapidly changing IT infrastructure, security hackers can steal valuable information through various modes. With the increasing dependence on web applications and websites for day-to-day activities and financial transactions, the instances of theft have increased globally. Also, the emergence of social networking websites has aided the malicious attackers to extract valuable information from vulnerable users. The increasing consumer dependence on web applications and websites for day-to-day activities and financial transactions are further increasing the risks of theft. This encourages the organizations to adopt network traffic analytics solutions.

Want a bigger picture? Try a FREE sample of this report now!

See the complete table of contents and list of exhibits, as well as selected illustrations and example pages from this report.

Companies covered

The network traffic analytics market is fairly concentrated due to the presence of few established companies offering innovative and differentiated software and services. By offering a complete analysis of the competitiveness of the players in the network monitoring tools market offering varied software and services, this network traffic analytics industry analysis report will aid clients identify new growth opportunities and design new growth strategies.

The report offers a complete analysis of a number of companies including:

Allot
Cisco Systems
IBM
Juniper Networks
Microsoft
Symantec

Network traffic analytics market growth based on geographic regions

Americas
APAC
EMEA

With a complete study of the growth opportunities for the companies across regions such as the Americas, APAC, and EMEA, our industry research analysts have estimated that countries in the Americas will contribute significantly to the growth of the network monitoring tools market throughout the predicted period.

Network traffic analytics market growth based on end-user

Telecom
BFSI
Healthcare
Media and entertainment

According to our market research experts, the telecom end-user industry will be the major end-user of the network monitoring tools market throughout the forecast period. Factors such as increasing use of network traffic analytics solutions and increasing use of mobile devices at workplaces will contribute to the growth of the market shares of the telecom industry in the network traffic analytics market.

Key highlights of the global network traffic analytics market for the forecast years 2018-2022:

CAGR of the market during the forecast period 2018-2022
Detailed information on factors that will accelerate the growth of the network traffic analytics market during the next five years
Precise estimation of the global network traffic analytics market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
Growth of the network traffic analytics industry across various geographies such as the Americas, APAC, and EMEA
A thorough analysis of the market’s competitive landscape and detailed information on several vendors
Comprehensive information about factors that will challenge the growth of network traffic analytics companies

Get more value with Technavio’s INSIGHTS subscription platform! Gain easy access to all of Technavio’s reports, along with on-demand services. Try the demo

This market research report analyzes the market outlook and provides a list of key trends, drivers, and challenges that are anticipated to impact the global network traffic analytics market and its stakeholders over the forecast years.

The global network traffic analytics market analysts at Technavio have also considered how the performance of other related markets in the vertical will impact the size of this market till 2022. Some of the markets most likely to influence the growth of the network traffic analytics market over the coming years are the Global Network as a Service Market and the Global Data Analytics Outsourcing Market.

Technavio’s collection of market research reports offer insights into the growth of markets across various industries. Additionally, we also provide customized reports based on the specific requirement of our clients.

In November 2025, mobile devices excluding tablets accounted for over ***** percent of web page views worldwide. Meanwhile, over ***** percent of webpage views in Africa were generated via mobile. In contrast, just over half of web traffic in North America still took place via desktop connections, with mobile only accounting for ***** percent of total web traffic. While regional infrastructure remains an important factor in broadband vs. mobile coverage, most of the world has had their eyes on the recent 5G rollout across the globe, spearheaded by tech leaders China and the United States. The number of mobile 5G subscriptions worldwide is forecast to reach more than ***** billion by 2028. Social media: room for growth in Africa and southern Asia Overall, more than ** percent of the world’s mobile internet subscribers are also active on social media. A fast-growing market, with newcomers such as TikTok taking the world by storm, marketers have been cashing in on social media’s reach. Overall, social media penetration is highest in Europe and America, while in Africa and southern Asia, there is still room for growth. As of 2021, Facebook and Google-owned YouTube are the most popular social media platforms worldwide. Facebook and Instagram are most effective With nearly ***** billion users, it is no wonder that Facebook remains the social media avenue of choice for the majority of marketers across the world. Instagram, meanwhile, was the second most popular outlet. Both platforms are low-cost and support short-form content, known for its universal consumer appeal and answering to the most important benefits of using these kinds of platforms for business and advertising purposes.

The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

Unlock the Power of Behavioural Data with GDPR-Compliant Clickstream Insights.

Swash clickstream data offers a comprehensive and GDPR-compliant dataset sourced from users worldwide, encompassing both desktop and mobile browsing behaviour. Here's an in-depth look at what sets us apart and how our data can benefit your organisation.

User-Centric Approach: Unlike traditional data collection methods, we take a user-centric approach by rewarding users for the data they willingly provide. This unique methodology ensures transparent data collection practices, encourages user participation, and establishes trust between data providers and consumers.

Wide Coverage and Varied Categories: Our clickstream data covers diverse categories, including search, shopping, and URL visits. Whether you are interested in understanding user preferences in e-commerce, analysing search behaviour across different industries, or tracking website visits, our data provides a rich and multi-dimensional view of user activities.

GDPR Compliance and Privacy: We prioritise data privacy and strictly adhere to GDPR guidelines. Our data collection methods are fully compliant, ensuring the protection of user identities and personal information. You can confidently leverage our clickstream data without compromising privacy or facing regulatory challenges.

Market Intelligence and Consumer Behaviuor: Gain deep insights into market intelligence and consumer behaviour using our clickstream data. Understand trends, preferences, and user behaviour patterns by analysing the comprehensive user-level, time-stamped raw or processed data feed. Uncover valuable information about user journeys, search funnels, and paths to purchase to enhance your marketing strategies and drive business growth.

High-Frequency Updates and Consistency: We provide high-frequency updates and consistent user participation, offering both historical data and ongoing daily delivery. This ensures you have access to up-to-date insights and a continuous data feed for comprehensive analysis. Our reliable and consistent data empowers you to make accurate and timely decisions.

Custom Reporting and Analysis: We understand that every organisation has unique requirements. That's why we offer customisable reporting options, allowing you to tailor the analysis and reporting of clickstream data to your specific needs. Whether you need detailed metrics, visualisations, or in-depth analytics, we provide the flexibility to meet your reporting requirements.

Data Quality and Credibility: We take data quality seriously. Our data sourcing practices are designed to ensure responsible and reliable data collection. We implement rigorous data cleaning, validation, and verification processes, guaranteeing the accuracy and reliability of our clickstream data. You can confidently rely on our data to drive your decision-making processes.

Snapshot img

Web Analytics Market Size 2025-2029

The web analytics market size is forecast to increase by USD 3.63 billion, at a CAGR of 15.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the rising preference for online shopping and the increasing adoption of cloud-based solutions. The shift towards e-commerce is fueling the demand for advanced web analytics tools that enable businesses to gain insights into customer behavior and optimize their digital strategies. Furthermore, cloud deployment models offer flexibility, scalability, and cost savings, making them an attractive option for businesses of all sizes. However, the market also faces challenges associated with compliance to data privacy and regulations. With the increasing amount of data being generated and collected, ensuring data security and privacy is becoming a major concern for businesses.
Regulatory compliance, such as GDPR and CCPA, adds complexity to the implementation and management of web analytics solutions. Companies must navigate these challenges effectively to maintain customer trust and avoid potential legal issues. To capitalize on market opportunities and address these challenges, businesses should invest in robust web analytics solutions that prioritize data security and privacy while providing actionable insights to inform strategic decision-making and enhance customer experiences.

What will be the Size of the Web Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market continues to evolve, with dynamic market activities unfolding across various sectors. Entities such as reporting dashboards, schema markup, conversion optimization, session duration, organic traffic, attribution modeling, conversion rate optimization, call to action, content calendar, SEO audits, website performance optimization, link building, page load speed, user behavior tracking, and more, play integral roles in this ever-changing landscape. Data visualization tools like Google Analytics and Adobe Analytics provide valuable insights into user engagement metrics, helping businesses optimize their content strategy, website design, and technical SEO. Goal tracking and keyword research enable marketers to measure the return on investment of their efforts and refine their content marketing and social media marketing strategies.

Mobile optimization, form optimization, and landing page optimization are crucial aspects of website performance optimization, ensuring a seamless user experience across devices and improving customer acquisition cost. Search console and page speed insights offer valuable insights into website traffic analysis and help businesses address technical issues that may impact user behavior. Continuous optimization efforts, such as multivariate testing, data segmentation, and data filtering, allow businesses to fine-tune their customer journey mapping and cohort analysis. Search engine optimization, both on-page and off-page, remains a critical component of digital marketing, with backlink analysis and page authority playing key roles in improving domain authority and organic traffic.

The ongoing integration of user behavior tracking, click-through rate, and bounce rate into marketing strategies enables businesses to gain a deeper understanding of their audience and optimize their customer experience accordingly. As market dynamics continue to evolve, the integration of these tools and techniques into comprehensive digital marketing strategies will remain essential for businesses looking to stay competitive in the digital landscape.

How is this Web Analytics Industry segmented?

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

Deployment

  Cloud-based
  On-premises


Application

  Social media management
  Targeting and behavioral analysis
  Display advertising optimization
  Multichannel campaign analysis
  Online marketing


Component

  Solutions
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

.

By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period.

In today's digital landscape, web analytics plays a pivotal role in driving business growth and optimizing online performance. Cloud-based deployment of web analytics is a game-changer, enabling on-demand access to computing resources for data analysis. This model streamlines business intelligence processes by collecting, integra

The global Clickstream Analytics Market was valued at $615.37 Million in 2022, and is projected to $1,298.63 Million by 2030, growing at a CAGR of 11.26%.

This is a dynamic traffic map service with capabilities for visualizing traffic speeds relative to free-flow speeds as well as traffic incidents which can be visualized and identified. The traffic data is updated every five minutes. Traffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows: Green (fast): 85 - 100% of free flow speeds Yellow (moderate): 65 - 85% Orange (slow); 45 - 65% Red (stop and go): 0 - 45%Esri's historical, live, and predictive traffic feeds come directly from TomTom (www.tomtom.com). Historical traffic is based on the average of observed speeds over the past year. The live and predictive traffic data is updated every five minutes through traffic feeds. The color coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation and field operations. The traffic map layer contains two sublayers: Traffic and Live Traffic. The Traffic sublayer (shown by default) leverages historical, live and predictive traffic data; while the Live Traffic sublayer is calculated from just the live and predictive traffic data only. A color coded traffic map image can be requested for the current time and any time in the future. A map image for a future request might be used for planning purposes. The map layer also includes dynamic traffic incidents showing the location of accidents, construction, closures and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis. The service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. In the coverage map, the countries color coded in dark green support visualizing live traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, including a data coverage map, visit the directions and routing documentation and ArcGIS Help.

In August 2025, Google.com was the most visited website worldwide, with an average of 98.2 billion monthly visits. The platform has maintained its leading position since June 2010, when it surpassed Yahoo to take first place. YouTube ranked second during the same period, recording over 48 billion monthly visits. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

Representative applications that can directly collect 5G da-tasets from mobile terminals without using specialized equipment include G-NetTrack Pro and PCAPdroid. The for-mer allows for the monitoring and logging of the header and payload information of the medium access control (MAC) frame passing through the 5G air interface. The latter is an open-source network capture and monitoring tool that works without root privileges, analyzing connections made by ap-plications installed on the user's mobile device. The latter can also dump mobile traffic to PCAP (also known as libpcap) and send it to the well-known Wireshark for further analysis. We created 5G datasets by measuring 5G traffic directly from a major mobile operator in South Korea. The model name of the mobile terminal used for traffic measurement is the Samsung Galaxy A90 5G, and it was equipped with a Qualcomm Snapdragon X50 5G modem. The packet sniffer software used for traffic measurement, PCAPdroid, was in-stalled in the terminal through Google play. Traffic was measured sequentially per application on two stationary ter-minals (only one terminal was used for non-interactive ser-vices) with no background traffic. The collected dataset is representative resource-intensive video traffic that has the greatest impact on 5G network planning and provisioning, and background traffic was not mixed to measure the unique characteristics of each type of traffic. The video streaming dataset includes data directly meas-ured while watching Netflix and Amazon Prime, which are representative over-the-top (OTT) services, on mobile devic-es. The live streaming dataset was measured while watching YouTube Live and South Korea's representative live broad-casts (Naver NOW and Afreeca TV). Video conferencing data were measured by holding an actual meeting on the widely used Zoom, MS Teams, and Google Meet platform. Two types of metaverse traffic were acquired: Zepeto and Roblox. Zepeto traffic was collected while staying in the 'camping world' for 15 hours. Roblox traffic was collected over 25 hours of playing the 'Collect All Pets' game using an auto clicker. We collected two types of mobile network gaming traffic. The first was cloud gaming, an online game setup that runs video games on remote servers and streams them direct-ly to the user's device. The second was a traditional mobile game connected to the Internet. The dataset was collected from May to October 2022, is a massive 328 hours in total, and is provided in the csv file format. The dataset we collected is a timestamp-mapped time series dataset with packet header information, and traffic analysis by application is possible because it includes source and destination addresses. To make it more usable as a traffic source model, Section III describes how to use it as a training dataset for the traffic simulator platform's source generator.

A 5G traffic dataset measured by PCAPdroid has been re-leased and can be used as a training dataset for various ML models. However, since the size of this dataset is very large, it is inconvenient to handle, and additional data preprocessing is required to use it for its intended purpose.

This data set can be used to learn GANs, time-series forcasting deep learning models.

Our implementation is given on GitHub. https://github.com/0913ktg/5G-Traffic-Generator

IL Coverage of the Gateway camera snapshots. The Gateway provides camera snapshot images throughout its coverage area in the form of camera icons on its maps and images in its camera report. With a free subscription, users can also access the Gateway ftp server which contains the most up to date versions of the images available.ImgPath - this is a link to the travelmidwest.com/lmiga/showCamera.jsp popup window that allows the user to select another direction, if availableCameraLocation - a text description of where the camera is locatedCameraDirection - the direction the camera is facing (NONE, N, E, S, W, NE, NW, SE, or SW)y - latitude in decimal degreesx - longitude in decimal degreesSnapShot - public URL of camera's image file that is suitable for placement in a tag, for instanceWarningAge - "true" if the camera is more than 10 minutes old, false otherwiseTooOld - "true" if more than 30 minutes old, "false" otherwiseAgeInMinutes - integer age of camera image in minutes

Context

• Time Series: Time series is a set of observations recorded over regular interval of time, Time series can be beneficial in many fields like stock market prediction, weather forecasting. - Accounts for the fact that data points taken over time may have an internal structure (such as auto correlation, trend or seasonal variation) that should be accounted for.

• Web traffic: Amount of data sent and received by visitors to a website. - Sites monitor the incoming and outgoing traffic to see which parts or pages of their site are popular and if there are any apparent trends, such as one specific page being viewed mostly by people in a particular country

Content

Contains Page Views for 60k Wikipedia articles in 8 different languages taken on a daily basis for 2 years.

https://i.ibb.co/h1JCgpY/DSLC.png" alt="DSLC">

A Data Science Life Cycle can be used to create a project. Forecasting can be done for any interval provided sufficient dataset is available. Refer the Github link in the tasks to view the forecast done using ARIMA and Prophet. Further feel free to contribute. Several other models can be used including a neural network to improve the results by many folds.

Acknowledgements

Credits :
1. Wikipedia 2. Google

Waze maps provide information about specific routes to assist motorists in avoiding traffic jams. Waze provides information about traffic jams and events that affect road conditions, either from drivers using Waze or from external sources. MTO has partnered with Waze through their Connected Citizen Program to publish Waze reported information on the Ontario 511 website. MTO iCorridor leverages such traffic jams to generate summaries of delay, duration, speed, and length by weekly, monthly, time of day, and day of week. The objective is to determine the pattern of congestion on all provincial highway corridors. The delay analysis was comprised of the followings:Estimation of corridor delay;Estimation of duration and length of congestion; andIdentification of true peak period."It must be noted that a “no congestion scenario” does not necessarily imply that there is no traffic on a specific road. Even when congestion is reduced to zero there may still be vehicles driving on the road. Waze creates “jam lines” that indicate continuous portions of streets where speed has slowed. Waze data provides the exact geographic location, length, speed, and time delay for these jam lines compared to the time it would normally take to transverse the jam line by car. A categorization for the severity of the jam is also provided.the jam data is composed of jam lines (which can change over time) measured at different time intervals. Given the crowd-sourced nature of the data, it cannot be determined if fluctuations in jam line activity are due to actual changes in traffic conditions or due to fluctuations in the number of active Wazers. Evidence from on-the-ground measures supports the notion that changes in jam activity are generally due to actual changes in traffic conditions"ElementValueDescriptionpubDateTimePublication date.linqmap:typeStringTRAFFIC_JAM.georss:lineList of longitude and latitude coordinatesTraffic jam line string (supplied when available).linqmap:speedFloatCurrent average speed on jammed segments in meter/second.linqmap:lengthIntegerJam length in meters.linqmap:delayIntegerDelay of jam compared to free flow speed, in seconds (in case of block, 1).linqmap:streetStringStreet name (as is written in database, no canonical form (supplied when available).linqmap:cityStringCity and state name [City, State] in case both are available, [State] if not associated with a city (supplied when available).linqmap:countryStringAvailable on EU (world) server (see two letters codes in https://en.wikipedia.org/wiki/ISO-31661).linqmap:roadTypeIntegerRoad type (see road types table in the appendix).linqmap:startNodeStringNearest Junction/street/city to jam start (supplied when available).linqmap:endNodeStringNearest Junction/street/city to jam end (supplied when available).linqmap:level0-5Traffic congestion level (0 = free flow 5 = blocked).linqmap:uuidStringUnique jam identifier.linqmap:turnLineCoordinatesA set of coordinates of a turn only when the jam is in a turn (supplied when available).linqmap:turnTypeStringWhat kind of turn it is: left, right, exit R or L, continue straight, or NONE (no info) (supplied when available).linqmap:blockingAlertUuidStringIf the jam is connected to a block (see alerts).ElementValueDescriptionpubDateTimePublication date.georss:pointCoordinatesLocation per report (Lat long).linqmap:uuidStringUnique system ID.linqmap:magvarInteger (0359)Event direction (Driver heading at report time. 0 degrees at North, according to the driver's device).linqmap:typeSee alert type tableEvent type.linqmap:subtypeSee alert subtypes tableEvent subtype depends on parameter.linqmap:reportDescriptionStringReport description (supplied when available).linqmap:streetStringStreet name (as is written in database, no canonical form, may be null).linqmap:cityStringCity and state name [City, State] in case both are available, [State] if not associated with a city (supplied when available).linqmap:countryStringSee two letters codes in .linqmap:roadTypeIntegerRoad type (see road types table in the appendix).linqmap:reportRatingIntegerUser rank between 16 (6 = high ranked user).linqmap:jamUuidStringIf the alert is connected to a jam jam ID.linqmap:Reliability (new)0-10How reliable is the report, 10 being most reliable. Based on reporter level and user respon-reference from (https://ops.fhwa.dot.gov/publications/fhwahop18084/ch2.htm)

Snapshot img

Digital Map Market Size 2025-2029

The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.

The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.

What will be the Size of the Digital Map Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.

Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.

How is this Digital Map Industry segmented?

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

Application

  Navigation
  Geocoders
  Others


Type

  Outdoor
  Indoor


Solution

  Software
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Indonesia
    Japan
    South Korea


  Rest of World (ROW)

By Application Insights

The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.

Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance applications,

Dataset

This dataset was created by Merve Afranur ARTAR

Contents

HTPA Dataset

Dataset Name: HTPA(HTTPS Tunneling Predictive Analysis Dataset)

Table of Contents

1. Overview
2. Dataset Structure
3. Data Collection Methodology
4. Privacy Considerations
5. Feature Descriptions
6. Usage Instructions
7. Contact

Overview

The HTPA dataset is designed for research and development in detecting HTTPS tunnel traffic versus normal HTTPS traffic. It is especially suitable for knowledge-graph-based algorithms, such as the HINT method, due to its inclusion of multi-dimensional traffic features and large-scale network interactions.

Key Features

• HTTPS tunnel traffic, VPN.

Dataset Structure

The HTPA dataset is provided as a compressed file with the following structure:

HTPA/
├── tunnel_traffic.pickle 
├── normal_traffic.pickle 
├── load_data.py 
└── splited_data/                    
  ├── test_data_split_by_date.pickle 
  ├── test_data_split_by_service.pickle 
  ├── train_data_split_by_date.pickle 
  └── train_data_split_by_service.pickle 

Data Collection Methodology

HTPA was generated to capture diverse traffic interactions in a server-client setup. Tunnel traffic data was gathered from popular VPN services—Hotspot Shield Free, Browsec VPN, ZenMate VPN, Hoxx VPN, and ShadowsocksR—all of which utilize HTTPS tunneling for data transfer. In collecting HTTPS tunnel traffic, we developed a crawler script that automated the process of visiting websites via these VPNs. To simulated realistic user behavior patterns, the crawler script was designed to browse at preset intervals with random pauses, closely mimicking human interaction habits. Specifically, clients (computers and mobile devices) were connected to VPN servers with configured client software. The crawler then launched a Chrome browser to visit randomly chosen sites from the Alexa Top 10,000 websites. All traffic was routed through a configured router that mirrored it to a storage server, archiving it in pcap format, and this process was repeated multiple times to ensure dataset diversity.

For non-VPN (normal HTTPS) traffic, data was collected passively from a corporate network environment with over one hundred users. Five volunteers logged their regular online activities without VPNs or proxies over a month, allowing us to record their service IPs and ports as non-VPN traffic.

Privacy Considerations

Due to the dataset's scale and privacy concerns, we provide extracted features rather than raw network packets. All IP addresses and domain names have been hashed to preserve anonymity.

Feature Descriptions

The feature data files (tunnel_traffic.pickle and normal_traffic.pickle) include:

Usage Instructions

In past experiments, using a simple random sampling to split train and test data led to very high accuracy (around 0.99) for some baseline models like Random Forest. However, in real-world scenarios, models face greater challenges, including unknown data and concept drift. To better mimic open-world scenarios, we suggest using the following two data split strategies:

By Service: Here, we used 'ServerIP' and 'ServerPort' as unique identifiers for each service, ensuring the same service wasn’t present in both train and test data. This approach prevent...

QUIC Traffic Analysis for Security Market Outlook

According to our latest research, the global QUIC Traffic Analysis for Security market size reached USD 1.24 billion in 2024, reflecting robust growth driven by increasing cyber threats and the rapid adoption of QUIC protocol in enterprise networks. The market is poised for significant expansion, projected to reach USD 4.31 billion by 2033, growing at a strong CAGR of 14.8% during the forecast period. This growth is primarily fueled by the urgent need for advanced security solutions capable of deciphering and monitoring encrypted QUIC traffic, as organizations move toward more secure and efficient internet protocols.

The rapid proliferation of QUIC (Quick UDP Internet Connections) protocol across global internet infrastructure is one of the primary growth factors for the QUIC Traffic Analysis for Security market. QUIC, originally developed by Google and now standardized by the IETF, offers significant improvements in performance, latency, and security over traditional protocols like TCP. However, these advantages also bring new security challenges, as QUIC’s encryption and multiplexing features make traditional traffic inspection and threat detection methods less effective. As a result, enterprises and security vendors are increasingly investing in advanced QUIC traffic analysis tools to maintain visibility into network activity, detect sophisticated threats, and ensure regulatory compliance. The growing reliance on cloud services, remote work environments, and high-speed internet applications is further accelerating the demand for specialized QUIC security solutions.

Another major driver for the market is the evolving threat landscape and the sophistication of cyberattacks targeting encrypted traffic. Attackers are leveraging QUIC’s encrypted channels to bypass conventional security appliances, making it difficult for organizations to identify malicious activity or data exfiltration. This has heightened the focus on next-generation security solutions that can analyze QUIC traffic without compromising user privacy or network performance. Vendors are responding by developing innovative software and hardware appliances, as well as managed security services, tailored specifically for QUIC analysis. The integration of artificial intelligence and machine learning into these solutions is also enabling faster and more accurate detection of anomalies, further boosting market growth.

Regulatory requirements and industry standards are also playing a crucial role in shaping the QUIC Traffic Analysis for Security market. As governments and industry bodies enforce stricter data protection and cybersecurity regulations, organizations are compelled to adopt more comprehensive security frameworks. This includes the ability to inspect and analyze encrypted traffic, such as QUIC, to prevent data breaches and ensure compliance with standards like GDPR, HIPAA, and PCI DSS. The increasing frequency of high-profile cyber incidents involving encrypted protocols has also raised awareness among enterprises regarding the importance of robust QUIC traffic analysis. As a result, security spending is on the rise across various sectors, including BFSI, healthcare, government, and IT, contributing to the sustained growth of this market.

From a regional perspective, North America is expected to maintain its dominance in the QUIC Traffic Analysis for Security market, driven by the presence of leading cybersecurity vendors, high adoption rates of advanced internet protocols, and stringent regulatory frameworks. However, Asia Pacific is emerging as the fastest-growing region, supported by rapid digital transformation, expanding internet infrastructure, and increasing investments in cybersecurity across countries like China, India, Japan, and South Korea. Europe is also witnessing substantial growth, fueled by GDPR compliance requirements and heightened focus on data privacy and security. Meanwhile, Latin America and the Middle East & Africa are gradually catching up, as organizations in these regions recognize the critical need to secure their networks against evolving threats associated with QUIC traffic.

Global Traffic Manager Market Outlook

According to our latest research, the global traffic manager market size reached USD 3.21 billion in 2024 and is projected to expand at a robust CAGR of 13.7% from 2025 to 2033. By the end of the forecast period, the market is expected to attain a value of USD 9.13 billion. This strong growth trajectory is primarily fueled by the escalating demand for efficient network management solutions, rising internet traffic, and the proliferation of cloud-based applications across multiple industry verticals. As organizations increasingly rely on digital infrastructures to support their operations, the need for advanced traffic management solutions that ensure seamless connectivity, optimized network performance, and enhanced security has become more pronounced than ever.

One of the most significant growth factors driving the global traffic manager market is the exponential surge in data consumption and internet usage worldwide. The widespread adoption of smartphones, IoT devices, and high-bandwidth applications has led to unprecedented network congestion, necessitating the deployment of sophisticated traffic management systems. These solutions enable organizations to efficiently balance loads, prioritize critical data, and mitigate latency issues, thereby enhancing overall user experience. Furthermore, the transition to hybrid and multi-cloud environments has intensified the need for dynamic traffic management to ensure consistent application performance and business continuity, especially as enterprises expand their digital footprints.

Another key factor contributing to market expansion is the increasing emphasis on network security and compliance. As cyber threats become more sophisticated and frequent, organizations are prioritizing the integration of security features within their network traffic management frameworks. Modern traffic managers are now equipped with advanced security protocols, real-time threat detection, and automated response capabilities, making them indispensable for safeguarding sensitive data and ensuring regulatory compliance. Additionally, the growing trend of remote work and distributed workforces has amplified the complexity of network management, prompting enterprises to invest in scalable and resilient traffic management solutions that can adapt to evolving security challenges.

Technological advancements and the emergence of artificial intelligence (AI) and machine learning (ML) in traffic management are further propelling market growth. AI-powered traffic managers can analyze vast volumes of network data in real time, predict traffic patterns, and automatically optimize routing decisions to prevent bottlenecks. This not only improves operational efficiency but also reduces the need for manual intervention, allowing IT teams to focus on strategic initiatives. The integration of AI and ML is also enabling predictive maintenance and proactive issue resolution, which are critical for minimizing downtime and ensuring uninterrupted service delivery. As organizations continue to prioritize digital transformation, the adoption of intelligent traffic management solutions is expected to accelerate, creating new opportunities for market players.

From a regional perspective, North America currently dominates the global traffic manager market, accounting for the largest share in 2024. This leadership is attributed to the region's advanced IT infrastructure, high penetration of cloud services, and the presence of major technology vendors. However, Asia Pacific is anticipated to witness the fastest growth during the forecast period, driven by rapid digitalization, expanding internet user base, and increasing investments in network infrastructure across emerging economies such as China and India. Europe and Latin America are also experiencing steady growth, supported by regulatory initiatives and the rising adoption of digital services in sectors such as healthcare, BFSI, and retail. The Middle East & Africa region, while still nascent, is gradually catching up as governments and enterprises invest in modernizing their network capabilities.