Dataset

This dataset was created by PriyankaJ7

Contents

The global big data and business analytics (BDA) market was valued at ***** billion U.S. dollars in 2018 and is forecast to grow to ***** billion U.S. dollars by 2021. In 2021, more than half of BDA spending will go towards services. IT services is projected to make up around ** billion U.S. dollars, and business services will account for the remainder. Big data High volume, high velocity and high variety: one or more of these characteristics is used to define big data, the kind of data sets that are too large or too complex for traditional data processing applications. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. For example, connected IoT devices are projected to generate **** ZBs of data in 2025. Business analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate business insights. The size of the business intelligence and analytics software application market is forecast to reach around **** billion U.S. dollars in 2022. Growth in this market is driven by a focus on digital transformation, a demand for data visualization dashboards, and an increased adoption of cloud.

Crime isn't a topic most people want to use mental energy to think about. We want to avoid harm, protect our loved ones, and hold on to what we claim is ours. So how do we remain vigilant without digging too deep into the filth that is crime? Data, of course. The focus of our study is to explore possible trends between crime and communities in the city of Calgary. Our purpose is visualize Calgary criminal behaviour in order to help increase awareness for both citizens and law enforcement. Through the use of our visuals, individuals can make more informed decisions to improve the overall safety of their lives. Some of the main concerns of the study include: how crime rates increase with population, which areas in Calgary have the most crime, and if crime adheres to time-sensative patterns.

This comprehensive dataset amalgamates detailed match statistics and player performance data from the Premier League 2021-2002, 2022-2023 and 2023-2024 season. It includes two distinct yet complementary datasets: one focuses on match-by-match team statistics including expected goals (xG), attendance, and in-game metrics; the other delves into individual player performances, providing insights into goals, assists, playing positions, and more. These datasets are ideal for a thorough analysis of the league, offering perspectives from both team strategies and player contributions. Ideal for sports analysts, data scientists, and football enthusiasts, this collection serves as a valuable resource for predictive modeling, tactical analysis, and player evaluation

Comprehensive YouTube channel statistics for Google Analytics, featuring 507,000 subscribers and 23,444,129 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Technology category. Track 337 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Real-time browser market share, OS distribution, and device capability statistics collected anonymously from web developers worldwide

In 2021, the global social media analytics market was valued at roughly ***** billion U.S. dollars. It was expected to grow to *** billion in 2022 and surpass ** billion dollars in 2028. Social media analytics tools are used, among others, to manage customer experience, as well as marketing management, and to gain competitive intelligence.

As of 2019, forecasts suggest that the predictive analytics market will reach over *********** U.S. dollars in total revenue. By 2022 the market is expected to reach nearly ** billion dollars in annual revenue as an increasingly large number of businesses make use of predictive analytics techniques for everything from fraud detection to medical diagnosis. Predictive analytics The field of predictive analytics involves the use of various statistical methods and models within businesses to make predictions about a wide range of future outcomes. Predictive analytical analysis is already one of the most widely adopted intelligent automation technologies in the world, with over ** percent of major enterprises deploying smart analytics that include predictive analytics. As business interactions around the world become increasingly digitalized, massive amounts of data are created which can be evaluated through predictive analytics tools in order to give users a better understanding of market dynamics and underlying trends. Considering this, it is no surprise that predictive models rank as the one of the top big data technology trends around the world.

The Data Analytics market is rapidly evolving, standing as a cornerstone for modern decision-making across various industries. With a current market size estimated to exceed billions of dollars, it has grown substantially over the past decade, driven by the explosion of big data and the increasing need for organizat

The booming App Data Statistics Tool market is projected to reach $9.66 billion by 2033, growing at a CAGR of 18%. This report analyzes market size, trends, key players (like App Annie, Firebase, Mixpanel), segmentation (social, gaming, e-commerce apps), and regional growth. Discover insights to optimize your app strategy.

Context

Football generates a vast amount of data, and every move can be scrutinized. This dataset represents raw data from https://www.premierleague.com/. It was collected on October 10th 2021.

Content

The dataset has files grouped by position of the player, as each position represents a difference quantification of data, for a total of 866 players. There are four main positions: - Goalkeeper (gk) - Defender (def) - Midfielder (mid) - Forward (fwd)

Each file is in a csv format, but has a different set of columns. They are self explanatory in their titles, and are not extensively explained. If required, it can be asked of the uploader.

Additionally, there is a file with the links to the data, and the whole set of names.

Acknowledgements

This dataset is the sole property of the Premier League and is for research only.

Inspiration

This dataset can be clustered and analyzed against other datasets, while trying to understand real time performance of the players themselves. There can be other questions also - such as the distribution of experience and youth.

The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in 2018. With a share of 45 percent, the software segment would become the large big data market segment by 2027. What is Big data? Big data is a term that refers to the kind of data sets that are too large or too complex for traditional data processing applications. It is defined as having one or some of the following characteristics: high volume, high velocity or high variety. Fast-growing mobile data traffic, cloud computing traffic, as well as the rapid development of technologies such as artificial intelligence (AI) and the Internet of Things (IoT) all contribute to the increasing volume and complexity of data sets. Big data analytics Advanced analytics tools, such as predictive analytics and data mining, help to extract value from the data and generate new business insights. The global big data and business analytics market was valued at 169 billion U.S. dollars in 2018 and is expected to grow to 274 billion U.S. dollars in 2022. As of November 2018, 45 percent of professionals in the market research industry reportedly used big data analytics as a research method.

Journal of business analytics Impact Factor 2024-2025 - ResearchHelpDesk - Business analytics research focuses on developing new insights and a holistic understanding of an organisation’s business environment to help make timely and accurate decisions, and to survive, innovate and grow. Thus, business analytics draws on the full spectrum of descriptive/diagnostic, predictive and prescriptive analytics in order to make better (i.e., data-driven and evidence-based) decisions to create business value in the broadest sense. The mission of the Journal of Business Analytics Journal (JBA) is to serve the emerging and rapidly growing community of business analytics academics and practitioners. We aim to publish articles that use real-world data and cases to tackle problem situations in a creative and innovative manner. We solicit articles that address an interesting research problem, collect and/or repurpose multiple types of data sets, and develop and evaluate analytics methods and methodologies to help organisations apply business analytics in new and novel ways. Reports of research using qualitative or quantitative approaches are welcomed, as are interdisciplinary and mixed methods approaches. Topics may include: Applications of AI and machine learning methods in business analytics Network science and social network applications for business Social media analytics Statistics and econometrics in business analytics Use of novel data science techniques in business analytics Robotics and autonomous vehicles Methods and methodologies for business analytics development and deployment Organisational factors in business analytics Responsible use of business analytics and AI Ethical and social implications of business analytics and AI Bias and explainability in analytics and AI Our editorial philosophy is to publish papers that contribute to theory and practice. Journal of Business Analytics is indexed in: AIS eLibrary Australian Business Deans Council (ABDC) Journal Quality List British Library CLOCKSS Crossref Ei Compendex (Engineering Village) Google Scholar Microsoft Academic Portico SCImago Scopus Ulrich's Periodicals Directory

Between 2023 and 2027, the majority of companies surveyed worldwide expect big data to have a more positive than negative impact on the global job market and employment, with ** percent of the companies reporting the technology will create jobs and * percent expecting the technology to displace jobs. Meanwhile, artificial intelligence (AI) is expected to result in more significant labor market disruptions, with ** percent of organizations expecting the technology to displace jobs and ** percent expecting AI to create jobs.

The global sports analytics service software market is experiencing robust growth, driven by the increasing adoption of data-driven strategies by sports teams, leagues, and broadcasters. The market's expansion is fueled by several key factors: the rising popularity of sports globally, the need for enhanced performance analysis, the proliferation of wearable technology generating vast amounts of data, and the increasing sophistication of analytical tools. The market is segmented by operating system (Android, iOS, Windows, and others) and application (basketball, football, and others), reflecting the diverse needs of different sports and technological preferences. North America currently holds a significant market share, owing to the established sports infrastructure and the early adoption of advanced analytics in professional leagues. However, regions like Asia-Pacific are showing promising growth potential due to the expanding sports industry and increasing investment in sports technology. The competitive landscape is characterized by a mix of established players and emerging technology companies, each offering unique solutions tailored to specific sports and analytical needs. Challenges include the high cost of implementation, data security concerns, and the need for skilled personnel to interpret and utilize the complex data generated by these systems. Despite these hurdles, the long-term outlook for the sports analytics service software market remains positive, with a projected CAGR indicating sustained growth over the forecast period. The forecast period (2025-2033) anticipates continuous growth, primarily driven by technological advancements and the increasing integration of analytics into sports decision-making at all levels. Advancements in artificial intelligence (AI) and machine learning (ML) are expected to further enhance the capabilities of these software solutions, providing more accurate predictions and actionable insights. The market's evolution will also be shaped by the ongoing development of new data sources and the increasing focus on personalized athlete development strategies. Furthermore, the growing interest in esports and the corresponding demand for performance analysis in virtual sports are also likely to contribute significantly to market growth. Competition will intensify, leading to innovation in software features, pricing strategies, and strategic partnerships to capture larger market shares. The global reach of major sports leagues will influence the expansion into new geographical markets, particularly in developing economies where the sports industry is rapidly expanding.

Detailed analytics for Facebook including content performance, engagement rates, and optimal posting times for November 2025

The Self-serve Data Analytics Solutions market is revolutionizing the way organizations harness their data, enabling users across various industries to access, analyze, and visualize data independently without requiring extensive IT involvement. This democratization of data empowers businesses to make informed decis

The global business analytics market size is predicted to grow from USD 55.33 billion in 2024 to USD 123.95 billion by 2034, reflecting a CAGR of over 8.4% from 2025 through 2034. Prominent industry players include Oracle, IBM, SAP SE, Tibco SoftwareMicrosoft.

The global sports analytics market, valued at $2.87 billion in 2025, is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 30.04% from 2025 to 2033. This explosive growth is fueled by several key factors. The increasing adoption of data-driven decision-making by sports teams and organizations is a primary driver. Teams are leveraging advanced analytics to improve player performance, optimize strategies, enhance scouting processes, and personalize fan experiences. Technological advancements, particularly in areas like AI, machine learning, and big data processing, are further accelerating market expansion. The rising availability of affordable and sophisticated analytics tools is making these technologies accessible to a wider range of teams and leagues, regardless of size or budget. Furthermore, the growing popularity of fantasy sports and esports is generating significant demand for detailed sports data and analytical insights, contributing to market growth. The market's segmentation reveals a diverse landscape of players. Established technology giants like IBM, SAP, and Oracle provide comprehensive data analytics solutions, while specialized firms like Opta Sports and Stats LLC cater to the specific needs of the sports industry. The emergence of innovative startups further underscores the dynamic nature of this sector. Geographic expansion also plays a crucial role, with North America and Europe currently dominating the market. However, growing interest in sports analytics in Asia-Pacific and other emerging regions presents significant opportunities for future growth. While challenges such as data security concerns and the need for skilled analytics professionals exist, the overall market outlook remains exceptionally positive, driven by the continued convergence of sports and technology. Recent developments include: October 2023, Texas A&M Athletics Sports Science announced that it has entered into an arrangement with Gemini Sports Analytics to offer the Aggies' staff Gemini’s AI software platform built-for sports that is projected to empower the Aggies to access prognostic analytics in addition to metrics to aid support student-athletes. The Gemini application authorizes stakeholders by offering predictive data analytics to the end users, cumulative interdisciplinary professionals' efficiency, and permitting high-level decision-makers to make game-changing choices faster., February 2023: Gemini Sports Analytics is an AI and Automated Machine learning tool, and SIS (Sports Info Solutions) announced a partnership to pre-integrate SIS data into the Gemini app. Along with the data integration, the two companies would leverage their complementary offerings and develop solutions for their current and future clients. Gemini's mission is to make it faster and easier for sports organizations across the globe to use predictive analytics in their decision-making processes around recruitment, player development, personnel, health and performance, and other management choices.. Key drivers for this market are: Rising Adoption of Big Data Analytics, AI and ML Technologies, Increase in Investments in the Newer Technologies. Potential restraints include: Rising Adoption of Big Data Analytics, AI and ML Technologies, Increase in Investments in the Newer Technologies. Notable trends are: Football Sport is Expected to Hold Significant Market Share.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for master in business administration business statistics data analytics in the U.S.