The online revenue of hub.com.pk amounted to US$1m in 2024. Discover eCommerce insights, including sales development, shopping cart size, and many more.

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The Office of the Assessor compiles property sales data to perform an annual property sales study to adjust calculated costs of property values based on local market conditions. This dataset includes property sales data obtained for annual sales studies from 2018 to the present. While only Valid Arm's Length transactions that occurred in the two years prior to when a given sales study is finalized are included in each study, this dataset includes all sales transactions obtained to perform the sales studies, whether or not the sales transactions met inclusion criteria for a study. More information about the Sales Study is available from the Office of the Assessor.Values in categorical fields such as 'Sales Instrument' are recorded based on State of Michigan CAMA standards at the time the value was recorded. Some variation in field value codes occurs over time as a related CAMA standard is updated. CAMA standards are available from the State of Michigan Department of Treasury State Tax Commission.Click here for the Analytics Hub visualization of Property Sales.

Table of usage statistics (number of views) for datasets within the Halifax Open Data Catalogue.The data was collected to show the usage of data within the Open Data Catalogue. Metadata

The Office of the Assessor compiles property sales data to perform an annual property sales study to adjust calculated costs of property values based on local market conditions. This dataset includes property sales data obtained for annual sales studies from 2018 to the present. While only Valid Arm's Length transactions that occurred in the two years prior to when a given sales study is finalized are included in each study, this dataset includes all sales transactions obtained to perform the sales studies, whether or not the sales transactions met inclusion criteria for a study. More information about the Sales Study is available from the Office of the Assessor.Values in categorical fields such as 'Sales Instrument' are recorded based on State of Michigan CAMA standards at the time the value was recorded. Some variation in field value codes occurs over time as a related CAMA standard is updated. CAMA standards are available from the State of Michigan Department of Treasury State Tax Commission.Click here for the Analytics Hub visualization of Property Sales.

The In-Memory Analytics market is experiencing robust growth, projected to reach $2.98 billion in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 18.38% from 2025 to 2033. This expansion is driven by the increasing need for real-time data processing and analysis across diverse sectors. Businesses are increasingly adopting in-memory analytics solutions to gain actionable insights from massive datasets, enabling faster decision-making and improved operational efficiency. The cloud deployment model is witnessing significant adoption due to its scalability, cost-effectiveness, and accessibility. Key end-user industries fueling market growth include BFSI (Banking, Financial Services, and Insurance), retail, IT and telecommunications, and the manufacturing sector, where real-time insights are crucial for risk management, fraud detection, customer relationship management, supply chain optimization, and predictive maintenance. The competitive landscape is characterized by a mix of established players like SAP, IBM, and Oracle, and emerging innovative companies offering specialized solutions. While data security and integration complexities pose certain challenges, the overall market outlook remains positive, fueled by ongoing technological advancements and growing data volumes. The market's continued growth trajectory is expected to be propelled by several factors. The increasing adoption of big data technologies and the Internet of Things (IoT) generate exponential data volumes, necessitating efficient and rapid analytical capabilities. Advancements in in-memory database technologies, coupled with declining hardware costs, are making in-memory analytics more accessible and cost-effective for a broader range of organizations. Furthermore, the rising demand for advanced analytics capabilities, such as predictive modeling and machine learning, integrated within in-memory platforms will significantly impact market expansion. Regional growth will likely be driven by increasing digitalization across Asia Pacific and Latin America, while North America and Europe maintain significant market shares due to early adoption and robust technological infrastructure. Recent developments include: November 2022: IBM announced a new software Business Analytics Enterprise to help organizations break down analytics and data silos to make informed decisions. In addition to IBM planning analytics with Watson and IBM Cognos analytics with Watson, this suite included a new IBM analytics content hub that simplified how users discover and consume analytics and planning tools across multiple platforms in a single, custom dashboard view., October 2022: Oracle announced a new product suite across its full data and analytics capabilities to help customers make faster and better decisions. Oracle Fusion Analytics across Customer Exchanges (CX) delivers new capabilities to accelerate insights, enhance predictions, and improve integrations across Oracle Fusion Cloud Applications (FaaS), Oracle Autonomous Database (ADB), and MySQL HeatWave.. Key drivers for this market are: Digital Transformation of End-users Leading to Adoption of Real-Time Analytics, Growing Data Volume Demanding Swift Analytical Methods; Advancements in Computational Technology. Potential restraints include: Digital Transformation of End-users Leading to Adoption of Real-Time Analytics, Growing Data Volume Demanding Swift Analytical Methods; Advancements in Computational Technology. Notable trends are: Manufacturing Sector to Drive the Market Growth.

The Detroit Land Bank Authority's (DLBA) Own It Now (OIN) program offers vacant homes for sale with a minimum offer price of $1,000. Homes are available on the DLBA website for sale 24 hours a day, 7 days a week and may be offered on at any time. Homes are sold as is and buyers are required to rehab the houses and ensure that they are occupied. The dataset provides information on the properties that have been successfully sold by the DLBA through the OIN program.The Detroit Land Bank Authority (DLBA) works directly with individual buyers, as well as Community Partner organizations and developers to achieve their mission to return the city's blighted and vacant properties to productive use. They utilize a variety of sales programs to make homeownership and land purchases accessible to Detroiters. One of these programs is Own it Now (OIN).Each row in the dataset represents an OIN home and includes data about the sale status, closing date for sold homes, sale price, and location information such as: address; parcel ID; and neighborhood.For more information about the DLBA's sales programs please visit their website.Click here for the Analytics Hub visualization of this dataset.

Comprehensive financial and analytical metrics for Efi Hub, including key performance indicators, market data, and ecosystem analytics.

Market Overview: The global content analytics market is projected to reach a value of 6.25 million by 2033, exhibiting a CAGR of 11.01% during the forecast period. The increasing volume of unstructured data from various sources, such as social media, text, and videos, is a major driver of this growth. Organizations are leveraging content analytics to gain insights into customer preferences, market trends, and operational efficiencies. Cloud-based deployment and the adoption of advanced technologies like natural language processing (NLP) and machine learning (ML) are key trends in the market. Market Segments and Key Players: The content analytics market is segmented based on deployment type (on-premise, cloud), application (text analytics, video analytics, social media analytics, speech analytics), and end-user industry (BFSI, healthcare, retail, manufacturing). Key players in the market include SAS Institute Inc., Adobe Systems Inc., TIBCO Software Inc., IBM Corporation, and Nice Systems Ltd. Strategic initiatives such as partnerships, acquisitions, and new product launches are driving competition in the market. Additionally, emerging economies in Asia Pacific and Latin America are expected to offer significant growth opportunities for content analytics providers. 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: Lack of Skilled Personnel and Awareness. Notable trends are: Video Analytics to have a significant growth rate.

This dataset is a compilation of PlumX metrics with the top 100 most-downloaded papers from Sci-Hub between Sept 2015-Feb 2016.Analysis of this dataset can be found here: http://plumanalytics.com/sci-hub-academic-cat-bag-post/.If you'd like to explore the altmetrics about this data, it can be found here: https://plu.mx/scihub100.The data used to compile the top 100 is the Sci-Hub dataset available on Dryad: Elbakyan A, Bohannon J (2016) Data from: Who's downloading pirated papers? Everyone. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.q447c

Dataset that contains vessel position information transmitted by vessels of different types and collected via the Automatic Identification System (AIS). The AIS dataset comes along with spatially and temporally correlated data about the vessels and the area of interest, including weather information

The Vehicle Data Hub (VDH) market is experiencing robust growth, driven by the increasing adoption of connected car technologies and the burgeoning need for real-time data analytics across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033, reaching approximately $50 billion by 2033. This expansion is fueled by several key factors. Firstly, the proliferation of connected vehicles equipped with advanced sensors and telematics generates vast quantities of data, creating a demand for efficient data aggregation, processing, and distribution platforms. Secondly, the insurance industry leverages VDH data for risk assessment and fraud detection, leading to improved pricing models and enhanced customer experiences. Similarly, infrastructure planning and traffic management benefit from real-time traffic insights, optimizing urban mobility and reducing congestion. Furthermore, the advertising industry uses VDH data for targeted advertising campaigns, enhancing efficiency and ROI. While data privacy concerns and the complexity of data standardization represent potential restraints, ongoing technological advancements and increasing regulatory clarity are mitigating these challenges. The segmentation within the VDH market highlights significant opportunities. Application-wise, Insurance and Traffic Management are currently dominant segments, yet growth potential is high across all segments, particularly in areas like Infrastructure Planning and City Planning as smart city initiatives accelerate globally. The types of data – Parking Data, Traffic Data, and Navigation Data – represent distinct value propositions, each catering to specific industry needs. Key players like Otonomo, Wejo, Verisk, INRIX, and others are actively investing in innovative solutions to capture and monetize this data, fostering competition and market innovation. Geographically, North America and Europe are currently leading the market, reflecting the higher penetration of connected cars in these regions. However, rapid technological advancements in Asia-Pacific and other developing regions are poised to drive substantial future growth. The market's future hinges on advancements in data analytics, AI, and the increasing integration of VDH with other intelligent transportation systems.

This dataset displays the number of page views each day in 2018 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.

Comprehensive financial and analytical metrics for Cosmos Hub, including key performance indicators, market data, and ecosystem analytics.

The Social Media Analytics Tools Software market is experiencing robust growth, driven by the increasing reliance of businesses, both large enterprises and SMEs, on social media for marketing and customer engagement. The market's expansion is fueled by the need for sophisticated tools to track performance, analyze audience behavior, and optimize social media strategies. The shift towards cloud-based solutions reflects a broader industry trend toward accessibility, scalability, and cost-effectiveness. While on-premise solutions still hold a segment of the market, cloud-based platforms are rapidly gaining traction due to their flexibility and ease of integration with existing marketing technology stacks. Competition is fierce, with established players like HubSpot and Salesforce alongside emerging specialists focusing on niche functionalities like social listening or influencer marketing. This competitive landscape fosters innovation and drives the development of more advanced analytics capabilities, including predictive analytics, sentiment analysis, and AI-powered insights. The market is geographically diverse, with North America currently dominating due to early adoption and high technology spending. However, Asia-Pacific is projected to witness significant growth in the coming years, driven by increasing internet penetration and the burgeoning digital economy in regions like India and China. Overall, the market presents a compelling opportunity for businesses seeking to leverage data-driven insights to enhance their social media ROI. Continued innovation in areas such as AI-powered insights and integration with other marketing platforms will further fuel market expansion. The forecast period (2025-2033) anticipates consistent market growth, albeit with potential fluctuations influenced by factors like global economic conditions and technological advancements. While restraints such as data privacy concerns and the complexity of integrating various social media platforms exist, the overwhelming demand for performance measurement and strategic decision-making in social media marketing will continue to drive market expansion. The segmentation by application (large enterprises vs. SMEs) and type (cloud-based vs. on-premise) highlights the diverse needs within the market, providing opportunities for specialized solutions to cater to specific user requirements. Successful vendors will likely focus on delivering highly integrated platforms offering comprehensive analytics capabilities and seamless integration with other marketing tools to consolidate the social media management workflow.

Issues from the Improve Detroit application. Detroiters use Improve Detroit to submit non-emergency service requests to the City and to check the status of non-emergency requests such as potholes, graffiti and damaged street signs. Issues are submitted through the Improve Detroit mobile app or the website. Improve Detroit uses the SeeClickFix CRM system from CivicPlus.Each row in the dataset represents a recorded issue, and includes information such as the type of issue reported, a brief description, issue status, and when an issue was opened, acknowledged, and closed. Links to a SeeClickFix webpage with an issue summary are also included. City of Detroit departments that use Improve Detroit are: DWSD, DPD, GSD, BSEED, DPW, PLA, PDD, Demolition, CRIO and DDOT. DoIT acts as system administrators.Click here for the Analytics Hub visualization of Improve Detroit Issues.NOTE: This dataset may not be downloadable through the Open Data Portal. The complete dataset, updated daily, is available to download in csv format.

This dataset contains sale information for properties sold by the Detroit Land Bank Authority (DLBA) through the Community Partner and Economic Development sales programs. The Community Partner program enables programs organizations purchase houses and/or vacant land at discounted prices for home rehab projects, urban gardening, green space projects or any use that enhances the quality of life in neighborhoods. The Economic Development program partners with locally based real estate companies to market properties that support infill development, are guided by City of Detroit planning studies, or adjacent to City-owned parcels that may be co-marketed for specialized development.Each row in the dataset represents a DLBA-acquired home that has been sold to a community partner or economic development program and includes data about the closing date, sale price, and location information such as address, parcel ID, and neighborhood.For more information about the DLBA's Community Partnership program click here. For more information about the DLBA's Projects program click here.Click here for the Analytics Hub visualization of this dataset.

Dataset contains the total number of page views for the dates 1/1/2014 through 12/31/2016. Data obtained through Google Analytics.

Website analytics for content and data on GeoHub.ca. First 5000 records from Google Analytics. Current data range: 01/01/2018 - 06/26/2018

This dataset displays the number of page views each day in 2017 for mississauga.ca. This data is compiled by Google Analytics and is updated annually.