According to the report published by Allied Market Research The Why to Invest in Sports Analytics Market Which Size Reach USD 6 376 Billion by 2026 The report provides an extensive analysis of changing market dynamics major segments value chain ...

Why to Invest in Sports Analytics Market Which Size Reach USD 6.376 Billion by 2026

In this week&#x27;s real-time analytics news: LinkedIn announced LakeChime, a new data trigger service to streamline data management in data lakes.

Real-time Analytics News for the Week Ending May 4 - RTInsights

Verisk Analytics (NASDAQ:VRSK – Get Free Report) and Potash America (OTCMKTS:PTAM – Get Free Report) are both business services companies, but which is the better investment? We will compare the two companies based on the strength of their profitability, institutional ownership, analyst ...

Reviewing Potash America (OTCMKTS:PTAM) & Verisk Analytics (NASDAQ:VRSK) - Defense World

Ailytics

ailytics

The data analytics landscape is changing very quickly. For many businesses, the ability to gather, analyze, and interpret data effectively helps them to understand their customers, improve internal processes, and remain competitive. There are five trends that we think will shape up how businesses analyze and use data in the future. Let’s take a look at each of them and understand what they are. 1. Data Sources – Synthetic Data Any kind of data analytics needs source data, and in today’s world this can come from nearly anywhere. Traditional data sources like customer databases, sales records, and website analytics are now joined by newer sources, such as social media feeds, IoT devices (e.g. drones), and third-party databases. But amongst all these newer sources, there is one in particular that we think is going to shape the future - Synthetic data. This is where Artificial Intelligence (‘AI’) is being used to create a simulation of data based on real-world information. While we are in the early stages of using synthetic data, it is becoming an increasingly important tool in areas where it is hard to source original data. 2. Data Infrastructure - Interoperability With a growing number of data feeds and sources, it has been a constant challenge for many businesses to implement the right infrastructure. This includes both the software and hardware required to capture, store and process data across an organization. On the hardware front, one trend that has emerged over the past 10 years is cloud computing. This refers to the storage and processing of data in third-party data centres. Amazon was a first mover in this space with introduction of AWS. Nower days, the industry has matured with increased competition from other tech giants like Microsoft. Another trend within cloud computing has been to set up data lakes and warehouses. However, the trend that we are focused on is around software that can connect data from different sources in a standardized way - This is referred to as data interoperability. Having interoperability between different systems, such as data from the Customer Relationship Management system and the Enterprise Resource Planning system is critical for the flow of information. While many businesses struggle with interoperability, those that achieve it will have a real advantage by being able to leverage their data to gain deeper insights. 3. AI and Machine Learning (‘ML’) – Natural Language Processing (‘NLP’) AI and ML shook the world in late 2022 with the release of ChatGPT 3.5, which was an information chatbot free for the public to use. Since then, AI and ML have become the most powerful tools in data analytics. This was initially focused on using structured data within companies to gain new insights and forecast with increased accuracy. The use of AI has moved at a very quick pace and now there are all sorts of new tools that can help organizations leverage their structured data better. However, the trend that we really think is worth keeping an eye on is NLP, which is using AI to analyze and provide insights from unstructured data. This includes extracting insights from data sources like video, images and audio, which has traditionally been a very time consuming exercise, until now. 4. Data Visualization - Storytelling Data visualization historically refers to using graphics to present data. For most of us, these are the charts and graphs used in presentations and reports. However, we think that it’s becoming more about transforming data into a story that can be easily acted on. As the number of data sources increase, using data visualization as a tool to actually tell the story is becoming more important. Especially when it comes to informing people within an organization and having the right decisions made on time. Storytelling is a growing trend that simply combines data visualizations with the narrative. It makes it easier to explain the findings from complex data to a non-technical audience, and drive informed decision-making across all levels of the organization. 5. Talent – New Roles The demand for data savvy talent is growing as analytics becomes more central to business strategy. From data scientists to analysts, organizations need skilled professionals who can make sense of the data and communicate it effectively. While there’s a push to make data skills more accessible across roles, there is also the creation of new data-related roles, such as “analytics translators”. This particular role is focused on bridging the gap between technical and non-technical teams. These professionals help communicate insights effectively, ensuring that business leaders can act on data insights without needing a strong technical background. This is one example of some of the new roles that are being created, in parallel with increasing demand for traditional data roles, such as data scientists and engineers. Conclusion The world of data analytics and insights is moving quickly. It is being driven by new sources of data, robust infrastructure, advanced AI and ML capabilities, improved visualization tools, and growing demand for data-savvy talent. While data analytics is typically focused on internal data, benchmarking is another tool that can uncover competitive trends and insights using external data. Organizations who stay on top of these emerging trends are well-positioned to continue winning into the future. The data analytics landscape is changing very quickly. For many businesses, the ability to gather, analyze, and interpret data effectively helps them to understand their customers, improve internal processes, and remain competitive. There are five trends that we think will shape up how businesses analyze and use data in the future. Let’s take a look at each of them and understand what they are. 1. Data Sources – Synthetic Data Any kind of data analytics needs source data, and in today’s world this can come from nearly anywhere. Traditional data sources like customer databases, sales records, and website analytics are now joined by newer sources, such as social media feeds, IoT devices (e.g. drones ), and third-party databases. But amongst all these newer sources, there is one in particular that we think is going to shape the future - Synthetic data. This is where Artificial Intelligence (‘AI’) is being used to create a simulation of data based on real-world information. While we are in the early stages of using synthetic data, it is becoming an increasingly important tool in areas where it is hard to source original data. drones drones 2. Data Infrastructure - Interoperability With a growing number of data feeds and sources, it has been a constant challenge for many businesses to implement the right infrastructure. This includes both the software and hardware required to capture, store and process data across an organization. On the hardware front, one trend that has emerged over the past 10 years is cloud computing. This refers to the storage and processing of data in third-party data centres. Amazon was a first mover in this space with introduction of AWS. Nower days, the industry has matured with increased competition from other tech giants like Microsoft. Another trend within cloud computing has been to set up data lakes and warehouses . However, the trend that we are focused on is around software that can connect data from different sources in a standardized way - This is referred to as data interoperability. Having interoperability between different systems, such as data from the Customer Relationship Management system and the Enterprise Resource Planning system is critical for the flow of information. While many businesses struggle with interoperability, those that achieve it will have a real advantage by being able to leverage their data to gain deeper insights. data lakes and warehouses data lakes and warehouses 3. AI and Machine Learning (‘ML’) – Natural Language Processing (‘NLP’) AI and ML shook the world in late 2022 with the release of ChatGPT 3.5, which was an information chatbot free for the public to use. Since then, AI and ML have become the most powerful tools in data analytics. This was initially focused on using structured data within companies to gain new insights and forecast with increased accuracy. The use of AI has moved at a very quick pace and now there are all sorts of new tools that can help organizations leverage their structured data better. However, the trend that we really think is worth keeping an eye on is NLP , which is using AI to analyze and provide insights from unstructured data. This includes extracting insights from data sources like video, images and audio, which has traditionally been a very time consuming exercise, until now. NLP NLP 4. Data Visualization - Storytelling Data visualization historically refers to using graphics to present data. For most of us, these are the charts and graphs used in presentations and reports. However, we think that it’s becoming more about transforming data into a story that can be easily acted on. As the number of data sources increase, using data visualization as a tool to actually tell the story is becoming more important. Especially when it comes to informing people within an organization and having the right decisions made on time. Storytelling is a growing trend that simply combines data visualizations with the narrative. It makes it easier to explain the findings from complex data to a non-technical audience, and drive informed decision-making across all levels of the organization. Data visualization Data visualization 5. Talent – New Roles The demand for data savvy talent is growing as analytics becomes more central to business strategy. From data scientists to analysts, organizations need skilled professionals who can make sense of the data and communicate it effectively. While there’s a push to make data skills more accessible across roles, there is also the creation of new data-related roles, such as “ analytics translators ”. This particular role is focused on bridging the gap between technical and non-technical teams. These professionals help communicate insights effectively, ensuring that business leaders can act on data insights without needing a strong technical background. This is one example of some of the new roles that are being created, in parallel with increasing demand for traditional data roles, such as data scientists and engineers. analytics translators Conclusion The world of data analytics and insights is moving quickly. It is being driven by new sources of data, robust infrastructure, advanced AI and ML capabilities, improved visualization tools, and growing demand for data-savvy talent . While data analytics is typically focused on internal data, benchmarking is another tool that can uncover competitive trends and insights using external data. Organizations who stay on top of these emerging trends are well-positioned to continue winning into the future. growing demand for data-savvy talent benchmarking

5 Trends Shaping the Future of Data Analytics and Insights

5 প্রবণতা ডেটা বিশ্লেষণ এবং অন্তর্দৃষ্টির ভবিষ্যত গঠন করে

5 tendències que configuren el futur de l'anàlisi de dades i les estadístiques

5 tendencias que están dando forma al futuro del análisis y la información de datos

5 Tandans ki fòme avni done Analytics ak Insights

データ分析と洞察の未来を形作る 5 つのトレンド

5 Деректерді талдау мен түсініктердің болашағын қалыптастыратын тенденциялар

5 និន្នាការបង្កើតអនាគតនៃការវិភាគទិន្នន័យ និងការយល់ដឹង

5 Isbeddellada Qaabeeya Mustaqbalka Falanqaynta Xogta iyo Aragtida

Mitindo 5 Inaunda Mustakabali wa Uchanganuzi wa Data na Maarifa

5 Тамоюлҳои ташаккули ояндаи таҳлили додаҳо ва фаҳмишҳо

5 Trend na Humuhubog sa Kinabukasan ng Data Analytics at Insights

Iindlela ezi-5 zokubumba ikamva loHlaziyo lweDatha kunye nokuqonda

Event Time Processing with Flink and Beam - Power of Real time Analytics

Leveraging Python's Pattern Matching and Comprehensions for Data Analytics

Getting Started with Data Analytics in Python Using PyArrow

AUSTIN, TX, USA, October 10th, 2024/CyberNewsWire/--IDLink, SpyCloud’s new automated digital identity correlation capability, is now core to its industry-leading Investigations solution used by CTI teams, security operations, fraud and risk prevention analysts, and law enforcement globally. SpyCloud, the leader in Identity Threat Protection, announced that its SaaS Investigations solution has been enhanced with identity analytics that illuminate the scope of digital identities and accelerate successful outcomes of complex investigations from days or hours to minutes. SpyCloud Investigations is a powerful cybercrime and identity threat investigation solution used by analysts and investigators to discover and act on threats by navigating the world’s largest repository of recaptured breach, malware, and phishing data. It powers rapid analysis of identity exposures across organizations, VIPs and supply chains, pattern of life analysis, threat actor attribution, insider risk analysis, financial crimes research, and more. SpyCloud Investigations now includes IDLink, the company’s advanced analytics technology that automatically delivers expanded digital identity results from a simple search query. Where a traditional threat intelligence or investigations tool may provide a small number of records directly correlated to the search input, IDLink expands the pool of results to include identity data correlated across shared usernames, emails, passwords, and PII – with flexible options around pivoting depth, confidence levels, and visualization. Based on more than a decade’s worth of techniques and expertise developed by renowned investigators at SpyCloud, including former intelligence agency personnel, IDLink uniquely provides a more comprehensive picture of identity compromise to give analysts more avenues for investigation while reducing errors and missed data points. Organizations with fewer in-house CTI, security operations, or fraud/e-crime prevention resources now have an easy-to-use solution to expand their investigative capabilities without adding additional expertise or headcount. “SpyCloud Investigations is the ultimate force multiplier for security teams,” said Jason Lancaster, SpyCloud’s senior vice president of investigations. “SpyCloud’s team of investigators have decades of experience investigating cybercrimes day and night, across all manner of use cases, with public and private sector partners. We’ve spent the last year infusing this knowledge into our solution so analysts at all skill levels can reap the benefits.” With IDLink advanced analytics now foundational to its industry-leading solution, SpyCloud Investigations offers users the ability to visualize holistic identities of exposed employees, consumers, vendors, and cybercriminal actors themselves to more quickly and comprehensively identify and act on risks – helping them achieve: Up-leveled Analyst Output: Investigative workflows automate the process of identifying hidden identity exposures, up-leveling analysts and investigators of all skill levels, increasing team productivity, discovery, and resolution. Hidden Connections: IDLink automatically connects the dots and rapidly pieces together a holistic view of a digital identity, in minutes instead of hours of advanced analysis previously. Attribution: Automated analytics deliver linked exposed identity assets and records, reducing dead ends in investigations and delivering critical details about criminal actors and threats. This announcement comes at a time when adversaries are increasingly using stolen identity data to bypass security measures and exploit exposed access. This is evidenced by large-scale infostealer malware campaigns and headline-grabbing breaches, such as the National Public Data breach, which leaked 2.7 billion identity records – including hundreds of millions of Americans' Social Security numbers. “There is a vast amount of personal information in criminals’ hands,” said Jason. “SpyCloud Investigations gets that same data into the right hands, faster, to protect businesses and their users. By illuminating connections, opening up new threads to investigate, and offering unlimited queries to SpyCloud’s enriched database of breached, phished, and malware-exfiltrated data, analysts can visualize threats and act decisively, enhancing organizational resilience against cybercrime and identity threats.” For more information about SpyCloud Investigations or to schedule a complimentary demo to explore your data, users can contact us here. About SpyCloud SpyCloud transforms recaptured darknet data to disrupt cybercrime. Its automated identity threat protection solutions leverage advanced analytics to proactively prevent ransomware and account takeover, safeguard employee and consumer accounts, and accelerate cybercrime investigations. SpyCloud's data from breaches, malware-infected devices, and successful phishes also powers many popular dark web monitoring and identity theft protection offerings. Customers include more than half of the Fortune 10, along with hundreds of global enterprises, mid-sized companies, and government agencies worldwide. Headquartered in Austin, TX, SpyCloud is home to more than 200 cybersecurity experts whose mission is to protect businesses and consumers from the stolen identity data criminals are using to target them now. To learn more and see insights on your company’s exposed data, users can visit spycloud.com. Contact Emily Brown REQ on behalf of SpyCloud ebrown@req.co This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here . AUSTIN, TX, USA, October 10th, 2024/CyberNewsWire/--IDLink, SpyCloud’s new automated digital identity correlation capability, is now core to its industry-leading Investigations solution used by CTI teams, security operations, fraud and risk prevention analysts, and law enforcement globally. SpyCloud, the leader in Identity Threat Protection, announced that its SaaS Investigations solution has been enhanced with identity analytics that illuminate the scope of digital identities and accelerate successful outcomes of complex investigations from days or hours to minutes. SpyCloud Investigations is a powerful cybercrime and identity threat investigation solution used by analysts and investigators to discover and act on threats by navigating the world’s largest repository of recaptured breach, malware, and phishing data. It powers rapid analysis of identity exposures across organizations, VIPs and supply chains, pattern of life analysis, threat actor attribution, insider risk analysis, financial crimes research, and more. SpyCloud Investigations now includes IDLink, the company’s advanced analytics technology that automatically delivers expanded digital identity results from a simple search query. Where a traditional threat intelligence or investigations tool may provide a small number of records directly correlated to the search input, IDLink expands the pool of results to include identity data correlated across shared usernames, emails, passwords, and PII – with flexible options around pivoting depth, confidence levels, and visualization. Based on more than a decade’s worth of techniques and expertise developed by renowned investigators at SpyCloud, including former intelligence agency personnel, IDLink uniquely provides a more comprehensive picture of identity compromise to give analysts more avenues for investigation while reducing errors and missed data points. Organizations with fewer in-house CTI, security operations, or fraud/e-crime prevention resources now have an easy-to-use solution to expand their investigative capabilities without adding additional expertise or headcount. “SpyCloud Investigations is the ultimate force multiplier for security teams,” said Jason Lancaster, SpyCloud’s senior vice president of investigations. “SpyCloud Investigations is the ultimate force multiplier for security teams,” said Jason Lancaster, SpyCloud’s senior vice president of investigations. “SpyCloud’s team of investigators have decades of experience investigating cybercrimes day and night, across all manner of use cases, with public and private sector partners. We’ve spent the last year infusing this knowledge into our solution so analysts at all skill levels can reap the benefits.” “SpyCloud’s team of investigators have decades of experience investigating cybercrimes day and night, across all manner of use cases, with public and private sector partners. We’ve spent the last year infusing this knowledge into our solution so analysts at all skill levels can reap the benefits.” With IDLink advanced analytics now foundational to its industry-leading solution, SpyCloud Investigations offers users the ability to visualize holistic identities of exposed employees, consumers, vendors, and cybercriminal actors themselves to more quickly and comprehensively identify and act on risks – helping them achieve: Up-leveled Analyst Output: Investigative workflows automate the process of identifying hidden identity exposures, up-leveling analysts and investigators of all skill levels, increasing team productivity, discovery, and resolution. Hidden Connections: IDLink automatically connects the dots and rapidly pieces together a holistic view of a digital identity, in minutes instead of hours of advanced analysis previously. Attribution: Automated analytics deliver linked exposed identity assets and records, reducing dead ends in investigations and delivering critical details about criminal actors and threats. This announcement comes at a time when adversaries are increasingly using stolen identity data to bypass security measures and exploit exposed access. This is evidenced by large-scale infostealer malware campaigns and headline-grabbing breaches, such as the National Public Data breach, which leaked 2.7 billion identity records – including hundreds of millions of Americans' Social Security numbers. “There is a vast amount of personal information in criminals’ hands,” said Jason. “There is a vast amount of personal information in criminals’ hands,” said Jason. “SpyCloud Investigations gets that same data into the right hands, faster, to protect businesses and their users. By illuminating connections, opening up new threads to investigate, and offering unlimited queries to SpyCloud’s enriched database of breached, phished, and malware-exfiltrated data, analysts can visualize threats and act decisively, enhancing organizational resilience against cybercrime and identity threats.” “SpyCloud Investigations gets that same data into the right hands, faster, to protect businesses and their users. By illuminating connections, opening up new threads to investigate, and offering unlimited queries to SpyCloud’s enriched database of breached, phished, and malware-exfiltrated data, analysts can visualize threats and act decisively, enhancing organizational resilience against cybercrime and identity threats.” For more information about SpyCloud Investigations or to schedule a complimentary demo to explore your data, users can contact us here. About SpyCloud SpyCloud transforms recaptured darknet data to disrupt cybercrime. Its automated identity threat protection solutions leverage advanced analytics to proactively prevent ransomware and account takeover, safeguard employee and consumer accounts, and accelerate cybercrime investigations. SpyCloud's data from breaches, malware-infected devices, and successful phishes also powers many popular dark web monitoring and identity theft protection offerings. Customers include more than half of the Fortune 10, along with hundreds of global enterprises, mid-sized companies, and government agencies worldwide. Headquartered in Austin, TX, SpyCloud is home to more than 200 cybersecurity experts whose mission is to protect businesses and consumers from the stolen identity data criminals are using to target them now. To learn more and see insights on your company’s exposed data, users can visit spycloud.com . spycloud.com spycloud.com Contact Emily Brown REQ on behalf of SpyCloud ebrown@req.co This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Cybernewswire under HackerNoon’s Business Blogging Program. Learn more about the program here here here .

SpyCloud Embeds Identity Analytics In Cybercrime Investigations Solution

SpyCloud تدمج تحليلات الهوية في حل تحقيقات الجرائم الإلكترونية

SpyCloud integra análisis de identidad en una solución de investigación de delitos cibernéticos

A SpyCloud beágyazza az identitáselemzést a kiberbűnözés-vizsgálati megoldásba

SpyCloud-ը ներդրում է ինքնության վերլուծությունը կիբերհանցագործությունների հետաքննության լուծումում

SpyCloud がサイバー犯罪捜査ソリューションにアイデンティティ分析を組み込む

SpyCloud iegulst identitātes analīzi kibernoziegumu izmeklēšanas risinājumā

SpyCloud dia mampiditra ny famakafakana ny maha-izy azy ao amin'ny Vahaolana fanadihadiana momba ny heloka bevava an-tserasera

SpyCloud integreert identiteitsanalyse in cybercrime-onderzoeksoplossing

SpyCloud osadza analizę tożsamości w rozwiązaniu dochodzeniowym w sprawie cyberprzestępczości

SpyCloud ฝังการวิเคราะห์ข้อมูลประจำตัวในโซลูชันการสืบสวนอาชญากรรมทางไซเบอร์

SpyCloud nhúng phân tích danh tính vào giải pháp điều tra tội phạm mạng

SpyCloud 将身份分析嵌入网络犯罪调查解决方案中

Talk Data to Me: The Art of Analytics Translation

Sports analytics has long relied on basic statistics such as points per game, field goal percentage, and rebounds to assess player performance. While these metrics provide some insight, they fall short of capturing the nuances of a player's skill and decision-making abilities. Coaches and analysts often struggle with evaluating the quality of a player's shots, which is crucial for devising effective game strategies. In that realm, Ricky Zhang has made strides. A data scientist at Amazon with a background in economics, mathematics, and computer science from Emory University, Zhang has developed a project that is set to redefine how we understand player performance on the basketball court. His 'Shot Quality' project, using advanced machine learning techniques, specifically beta-binomial regression, addresses the limitations of traditional basketball metrics. The Problem: Stale Metrics and Missed Opportunities Basketball analytics, for ages, leaned on basic stats to gauge player performance. These metrics, though handy, miss the finer points of a player’s skills and decisions. Coaches and analysts often hit walls when judging shot quality—a key factor for crafting game strategies. Ricky Zhang saw these gaps and aimed higher. With his machine learning and AI chops, he was inspired to craft a model that nails down the true quality of basketball shots. A New Era in Basketball Analytics Inspired by a baseball batting averages analytics report, Zhang started creating a model that could accurately assess the quality of shots taken by basketball players. The 'Shot Quality' project was born out of this vision. Zhang’s project utilizes beta-binomial regression, a statistical method that accounts for the variability in players' shooting performance and the trust placed in them by their coaches. The 'Shot Quality' project zeroes in on the context and conditions of player shots. By crunching heaps of data—player positioning, defensive pressure, game situations—Zhang's model predicts shot success likelihood. This fresh method paints a clearer picture of a player's shooting prowess than old-school metrics. One of the biggest challenges in sports analytics is the mountain of data and its tricky interpretation. Zhang's machine learning chops let him efficiently sift through this data, pulling out valuable insights. His model tackles data noise and variability, giving coaches and analysts straightforward, actionable information. The 'Shot Quality' project's impact? Massive. Coaches can now make smarter calls on player rotations, shot choices, and defensive matchups. Knowing which players excel in specific scenarios lets teams play to their strengths and exploit opponents' weaknesses. Ricky Zhang: A Thought Leader in Sports Analytics Zhang's work redefines industry standards. His innovative machine learning approach places him as a thought leader. Beyond technical skills, he's committed to mentoring upcoming data scientists and sharing his insights. The heart of his leadership is all about resilience and adaptability, evident in how he tackled personal hurdles. When Twitch let him go due to company-wide cutbacks, he swiftly pivoted, using his network and skills to land a new gig at Amazon. This journey bolstered his resilience and dedication to nonstop learning—key ingredients in his recipe for success. Zhang's influence in sports analytics is poised to grow. He envisions further refining the 'Shot Quality' model and expanding its applications to other sports. His goal is to integrate real-time data and advanced AI techniques to provide even more accurate and actionable insights. Recent leaps in sports analytics are shining a light on how critical data-driven decisions have become in athletics. Player-tracking tech and high-res video analysis are shaking up the game, capturing every little player's move and interaction on the court, creating a treasure trove of data for the geeks to dive into. The brains at MIT Sloan Sports Analytics Conference are making noise about how machine learning and AI are flipping sports strategies on their heads. Turns out, models that mix player tracking with game context data can boost the accuracy of performance predictions and strategic calls. Take neural networks, for instance—these bad boys are getting good at predicting player performance and spotting injury risks, giving teams new ways to keep their stars healthy and sharp. Then there’s wearable tech, adding another layer to the data game. Real-time physiological and biomechanical stats are now at coaches’ fingertips, helping keep tabs on player fatigue, recovery, and overall health. This means smarter coaching decisions and players who are primed for peak performance. Zhang's 'Shot Quality' project aligns with these trends, showcasing how advanced statistical models can be applied to sports analytics. By leveraging beta-binomial regression, Zhang's model accounts for the inherent variability in player performance, providing a more nuanced understanding of shooting efficiency. This approach not only enhances the accuracy of performance metrics but also offers deeper insights into player decision-making and game dynamics. The Road Ahead for Ricky Zhang and Shot Quality Project Ricky Zhang’s 'Shot Quality' project represents a significant leap forward in sports analytics. By applying advanced machine learning techniques to basketball performance, he is transforming how we understand and evaluate players. As Zhang continues to innovate and lead in this field, the future of sports analytics looks incredibly promising. For those inspired by Zhang’s journey, there are countless opportunities to explore the intersections of data science and sports. Whether you're an aspiring data scientist or a seasoned professional, Zhang's work serves as a powerful reminder of the impact that innovative thinking and perseverance can have on an industry. If you’re interested in learning more about Ricky Zhang’s work or exploring the future of sports analytics, connect with him on LinkedIn. Stay tuned for more groundbreaking projects that will continue to reshape the world of sports. Sports analytics has long relied on basic statistics such as points per game, field goal percentage, and rebounds to assess player performance. While these metrics provide some insight, they fall short of capturing the nuances of a player's skill and decision-making abilities. Coaches and analysts often struggle with evaluating the quality of a player's shots, which is crucial for devising effective game strategies. In that realm, Ricky Zhang has made strides. Ricky Zhang Ricky Zhang A data scientist at Amazon with a background in economics, mathematics, and computer science from Emory University, Zhang has developed a project that is set to redefine how we understand player performance on the basketball court. His 'Shot Quality' project, using advanced machine learning techniques, specifically beta-binomial regression, addresses the limitations of traditional basketball metrics. The Problem: Stale Metrics and Missed Opportunities Basketball analytics, for ages, leaned on basic stats to gauge player performance. These metrics, though handy, miss the finer points of a player’s skills and decisions. Coaches and analysts often hit walls when judging shot quality—a key factor for crafting game strategies. Ricky Zhang saw these gaps and aimed higher. With his machine learning and AI chops, he was inspired to craft a model that nails down the true quality of basketball shots. A New Era in Basketball Analytics Inspired by a baseball batting averages analytics report , Zhang started creating a model that could accurately assess the quality of shots taken by basketball players. The 'Shot Quality' project was born out of this vision. Zhang’s project utilizes beta-binomial regression, a statistical method that accounts for the variability in players' shooting performance and the trust placed in them by their coaches. baseball batting averages analytics report baseball batting averages analytics report The 'Shot Quality' project zeroes in on the context and conditions of player shots. By crunching heaps of data—player positioning, defensive pressure, game situations—Zhang's model predicts shot success likelihood. This fresh method paints a clearer picture of a player's shooting prowess than old-school metrics. One of the biggest challenges in sports analytics is the mountain of data and its tricky interpretation. Zhang's machine learning chops let him efficiently sift through this data, pulling out valuable insights. His model tackles data noise and variability, giving coaches and analysts straightforward, actionable information. The 'Shot Quality' project's impact? Massive. Coaches can now make smarter calls on player rotations, shot choices, and defensive matchups. Knowing which players excel in specific scenarios lets teams play to their strengths and exploit opponents' weaknesses. Ricky Zhang: A Thought Leader in Sports Analytics Zhang's work redefines industry standards. His innovative machine learning approach places him as a thought leader. Beyond technical skills, he's committed to mentoring upcoming data scientists and sharing his insights. The heart of his leadership is all about resilience and adaptability, evident in how he tackled personal hurdles. When Twitch let him go due to company-wide cutbacks, he swiftly pivoted, using his network and skills to land a new gig at Amazon. This journey bolstered his resilience and dedication to nonstop learning—key ingredients in his recipe for success. Zhang's influence in sports analytics is poised to grow. He envisions further refining the 'Shot Quality' model and expanding its applications to other sports. His goal is to integrate real-time data and advanced AI techniques to provide even more accurate and actionable insights. Recent leaps in sports analytics are shining a light on how critical data-driven decisions have become in athletics. Player-tracking tech and high-res video analysis are shaking up the game, capturing every little player's move and interaction on the court, creating a treasure trove of data for the geeks to dive into. The brains at MIT Sloan Sports Analytics Conference are making noise about how machine learning and AI are flipping sports strategies on their heads. Turns out, models that mix player tracking with game context data can boost the accuracy of performance predictions and strategic calls. Take neural networks, for instance—these bad boys are getting good at predicting player performance and spotting injury risks, giving teams new ways to keep their stars healthy and sharp. Then there’s wearable tech, adding another layer to the data game. Real-time physiological and biomechanical stats are now at coaches’ fingertips, helping keep tabs on player fatigue, recovery, and overall health. This means smarter coaching decisions and players who are primed for peak performance. Zhang's 'Shot Quality' project aligns with these trends, showcasing how advanced statistical models can be applied to sports analytics. By leveraging beta-binomial regression, Zhang's model accounts for the inherent variability in player performance, providing a more nuanced understanding of shooting efficiency. This approach not only enhances the accuracy of performance metrics but also offers deeper insights into player decision-making and game dynamics. The Road Ahead for Ricky Zhang and Shot Quality Project Ricky Zhang’s 'Shot Quality' project represents a significant leap forward in sports analytics. By applying advanced machine learning techniques to basketball performance, he is transforming how we understand and evaluate players. As Zhang continues to innovate and lead in this field, the future of sports analytics looks incredibly promising. For those inspired by Zhang’s journey, there are countless opportunities to explore the intersections of data science and sports. Whether you're an aspiring data scientist or a seasoned professional, Zhang's work serves as a powerful reminder of the impact that innovative thinking and perseverance can have on an industry. If you’re interested in learning more about Ricky Zhang’s work or exploring the future of sports analytics, connect with him on LinkedIn . Stay tuned for more groundbreaking projects that will continue to reshape the world of sports. LinkedIn LinkedIn

The Future of Sports Analytics: Ricky Zhang's Groundbreaking 'Shot Quality' Project

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In 2023, I wrote about essential developers’ conferences to attend, highlighting their significance and benefits. The year 2024 has witnessed further developments in digital technology, with artificial intelligence (AI) and big data leading the charge and dominating the headlines. This year, there will be AI and big data conferences in different parts of the world for AI experts, researchers, and enthusiasts to attend either in real life or online. In most cases, organizing these events requires a lot of preparations, from hotel reservations for attendees to transportation and the provision of refreshments, etc. Nevertheless, there are usually options for online attendance. What Is an AI And Big Data Conference? An AI and big data conference is a gathering of AI experts, researchers, students and enthusiasts focused on exploring the latest developments in the fields of AI and big data. It is also a place to discuss the opportunities and the various challenges facing the AI and big data industry. Seasoned speakers are usually invited to deliver keynote speeches on various topics ranging from AI and big data applications and data privacy to issues bordering on AI ethics. Panel discussions are held to facilitate a mutual exchange between the audience and the panelists. There are also tech exhibitions showcasing the latest technologies and solutions. Why You Should Attend an AI And Big Data Conference There are peculiar reasons to attend an AI and big data conference in 2024, and these include staying abreast of the latest developments in the industry, networking or meeting like-minded people, learning new skills, and exploring career opportunities. Upcoming AI And Big Data Conferences to Attend in 2024 Whether you are an AI expert, a passionate researcher, or an enthusiast, AI, and big data conferences are great platforms for learning, networking, and staying updated on the latest trends in the industry. This list presents you with an overview of some of the upcoming conferences on AI and big data. The conferences covered include are World Summit AI, AI Summit New York, Oxycon, Analytics Summit, and Big Data Conference Europe, all of which are highly anticipated events in 2024. Oxycon Date: September 25, 2024
Location: Online
Cost: Free
Focus Areas: Fueling Businesses with Public Web Data, Mastering AI & Advanced Web Scraping Techniques, Optimizing Web Data Extraction Operations
Speakers and Agenda: Yet to be revealed Celebrating its 5th anniversary, OxyCon is an online event focusing on web data acquisition for businesses. This year, the speakers will discuss utilizing web data for boosting businesses and optimizing data operations. Mastering AI in web scraping will be another widely explored topic. What makes OxyCon stand out from other conferences is that it’s completely free – you just need to register so you get the link to access it. It is also held online (some conferences are still paid even for watching online), so you can attend it from the comfort of your home or office. The speaker list and agenda are not revealed as of July 2024. However, judging from the past, OxyCon’s speakers are usually top web scraping professionals from Oxylabs and some guests from other successful organizations. Whether you’re a developer or a business owner, you can really get some insider knowledge about data acquisition processes. World Summit AI Date: October 9-10, 2024
Location: Amsterdam, Netherlands
Cost: From €819
Focus Areas: Generative AI, Scaling Startups with AI, AI in Finance and Other Industries Held in Amsterdam, the World Summit AI is one of the largest AI conferences globally. The event’s schedule is busy, full of interesting presentations, panel discussions, and workshops. Some of the presenters include Trishul Chilimbi, VP and distinguished scientist, stores foundational AI at Amazon, Nitzan Mekel-Bobrov, Chief AI Officer at eBay, etc. Big Data Conference Europe Date: November 19-22, 2024
Location: Hybrid - Vilnius, Lithuania, and Online
Cost: From €730
Focus Areas: Predictive and Data Analytics, Kubernetes, Cloud Computing, Serverless Computing This hybrid event, held in Vilnius and available online, is in its 8th year. The Big Data Conference Europe includes hands-on workshops and a wide range of sessions on crucial AI topics such as ChatGPT, deep learning, and predictive analytics. It's an excellent opportunity for both in-person and virtual attendees to enhance their knowledge and skills. Some of the more interesting speakers include Gaurav Tiwari, Engineering Manager at Spotify, Karim Wadie, Tech Consultant at Google, and Ricardo Sueiras, AWS Cloud Practitioner at Amazon Web Services. The Analytics Summit Date: October 8-9, 2024


Location(Hybrid and Online): Hamburg, Germany


Cost: €249


Focus Areas: Data, Analytics, Marketing Technologies, Conversion Optimization, Cloud, Advanced Analytics, AI The Analytics Summit is the largest Google Analytics conference in Europe. Co-developed with Google, this event has expanded to cover a wide array of topics, from marketing technologies to advanced analytics and AI. It features multiple conferences, one-on-one meetings with experts, and hands-on seminars, making it a valuable experience for anyone passionate about data and technology. In this year’s Analytics Summit, there will be a lot of experienced and interesting professionals presenting. The speaker list features Cemre Şahin, Digital Data and Growth Marketing Manager at PepsiCo, Franziska Eickhoff, Chief of Data and Analytics at L’Oréal, and many more. AI Summit New York Date: December 6-7, 2024
Location: New York, NY, USA (Likely Hybrid Format)
Cost: Not stated on their website
Focus Areas: Artificial Intelligence, Business Applications, Technology The AI Summit New York is a key event for those looking to explore AI's business applications. With a likely hybrid format, it caters to both in-person and online attendees. The summit covers a broad spectrum of AI topics and offers a platform for networking with industry leaders. Although this year’s speakers and agenda have not yet been revealed (end of July 2024), the list includes associates from Meta, Google, EY, Cloudflare, Pfizer, and others: a prestigious yet versatile list of companies. Conclusion The importance of attending an AI and big data conference can't be overemphasized. To catch up with the latest developments in this burgeoning tech industry, attending conferences, whether online or in real life, has proven to be a very valuable and rewarding experience for attendees. In 2023, I wrote about essential developers’ conferences to attend , highlighting their significance and benefits. The year 2024 has witnessed further developments in digital technology, with artificial intelligence (AI) and big data leading the charge and dominating the headlines. essential developers’ conferences to attend This year, there will be AI and big data conferences in different parts of the world for AI experts, researchers, and enthusiasts to attend either in real life or online. In most cases, organizing these events requires a lot of preparations, from hotel reservations for attendees to transportation and the provision of refreshments, etc. Nevertheless, there are usually options for online attendance. What Is an AI And Big Data Conference? An AI and big data conference is a gathering of AI experts, researchers, students and enthusiasts focused on exploring the latest developments in the fields of AI and big data. It is also a place to discuss the opportunities and the various challenges facing the AI and big data industry. Seasoned speakers are usually invited to deliver keynote speeches on various topics ranging from AI and big data applications and data privacy to issues bordering on AI ethics. Panel discussions are held to facilitate a mutual exchange between the audience and the panelists. There are also tech exhibitions showcasing the latest technologies and solutions. Why You Should Attend an AI And Big Data Conference There are peculiar reasons to attend an AI and big data conference in 2024, and these include staying abreast of the latest developments in the industry, networking or meeting like-minded people, learning new skills, and exploring career opportunities. Upcoming AI And Big Data Conferences to Attend in 2024 Whether you are an AI expert, a passionate researcher, or an enthusiast, AI, and big data conferences are great platforms for learning, networking, and staying updated on the latest trends in the industry. This list presents you with an overview of some of the upcoming conferences on AI and big data. The conferences covered include are World Summit AI, AI Summit New York, Oxycon, Analytics Summit, and Big Data Conference Europe, all of which are highly anticipated events in 2024. Oxycon Date: September 25, 2024 Location: Online Cost: Free Focus Areas: Fueling Businesses with Public Web Data, Mastering AI & Advanced Web Scraping Techniques, Optimizing Web Data Extraction Operations Speakers and Agenda: Yet to be revealed Date: September 25, 2024 Location: Online Cost: Free Focus Areas: Fueling Businesses with Public Web Data, Mastering AI & Advanced Web Scraping Techniques, Optimizing Web Data Extraction Operations Speakers and Agenda: Yet to be revealed Celebrating its 5th anniversary, OxyCon is an online event focusing on web data acquisition for businesses. This year, the speakers will discuss utilizing web data for boosting businesses and optimizing data operations. Mastering AI in web scraping will be another widely explored topic. What makes OxyCon stand out from other conferences is that it’s completely free – you just need to register so you get the link to access it. It is also held online (some conferences are still paid even for watching online), so you can attend it from the comfort of your home or office. The speaker list and agenda are not revealed as of July 2024. However, judging from the past, OxyCon’s speakers are usually top web scraping professionals from Oxylabs and some guests from other successful organizations. Whether you’re a developer or a business owner, you can really get some insider knowledge about data acquisition processes. World Summit AI Date: October 9-10, 2024 Location: Amsterdam, Netherlands Cost: From €819 Focus Areas: Generative AI, Scaling Startups with AI, AI in Finance and Other Industries Date: October 9-10, 2024 Location: Amsterdam, Netherlands Cost: From €819 Focus Areas: Generative AI, Scaling Startups with AI, AI in Finance and Other Industries Held in Amsterdam, the World Summit AI is one of the largest AI conferences globally. The event’s schedule is busy, full of interesting presentations, panel discussions, and workshops. Some of the presenters include Trishul Chilimbi, VP and distinguished scientist, stores foundational AI at Amazon, Nitzan Mekel-Bobrov, Chief AI Officer at eBay, etc. Big Data Conference Europe Date: November 19-22, 2024 Location: Hybrid - Vilnius, Lithuania, and Online Cost: From €730 Focus Areas: Predictive and Data Analytics, Kubernetes, Cloud Computing, Serverless Computing Date: November 19-22, 2024 Location: Hybrid - Vilnius, Lithuania, and Online Cost: From €730 Focus Areas: Predictive and Data Analytics, Kubernetes, Cloud Computing, Serverless Computing This hybrid event, held in Vilnius and available online, is in its 8th year. The Big Data Conference Europe includes hands-on workshops and a wide range of sessions on crucial AI topics such as ChatGPT, deep learning, and predictive analytics. It's an excellent opportunity for both in-person and virtual attendees to enhance their knowledge and skills. Some of the more interesting speakers include Gaurav Tiwari, Engineering Manager at Spotify, Karim Wadie, Tech Consultant at Google, and Ricardo Sueiras, AWS Cloud Practitioner at Amazon Web Services. The Analytics Summit Date: October 8-9, 2024 Location(Hybrid and Online): Hamburg, Germany Cost: €249 Focus Areas: Data, Analytics, Marketing Technologies, Conversion Optimization, Cloud, Advanced Analytics, AI Date: October 8-9, 2024 Date: October 8-9, 2024 Location(Hybrid and Online): Hamburg, Germany Location(Hybrid and Online): Hamburg, Germany Cost: €249 Cost: €249 Focus Areas: Data, Analytics, Marketing Technologies, Conversion Optimization, Cloud, Advanced Analytics, AI Focus Areas: Data, Analytics, Marketing Technologies, Conversion Optimization, Cloud, Advanced Analytics, AI The Analytics Summit is the largest Google Analytics conference in Europe. Co-developed with Google, this event has expanded to cover a wide array of topics, from marketing technologies to advanced analytics and AI. It features multiple conferences, one-on-one meetings with experts, and hands-on seminars, making it a valuable experience for anyone passionate about data and technology. In this year’s Analytics Summit, there will be a lot of experienced and interesting professionals presenting. The speaker list features Cemre Şahin, Digital Data and Growth Marketing Manager at PepsiCo, Franziska Eickhoff, Chief of Data and Analytics at L’Oréal, and many more. AI Summit New York Date: December 6-7, 2024 Location: New York, NY, USA (Likely Hybrid Format) Cost: Not stated on their website Focus Areas: Artificial Intelligence, Business Applications, Technology Date: December 6-7, 2024 Location: New York, NY, USA (Likely Hybrid Format) Cost: Not stated on their website Focus Areas: Artificial Intelligence, Business Applications, Technology The AI Summit New York is a key event for those looking to explore AI's business applications. With a likely hybrid format, it caters to both in-person and online attendees. The summit covers a broad spectrum of AI topics and offers a platform for networking with industry leaders. Although this year’s speakers and agenda have not yet been revealed (end of July 2024), the list includes associates from Meta, Google, EY, Cloudflare, Pfizer, and others: a prestigious yet versatile list of companies. Conclusion The importance of attending an AI and big data conference can't be overemphasized. To catch up with the latest developments in this burgeoning tech industry, attending conferences, whether online or in real life, has proven to be a very valuable and rewarding experience for attendees.

Essential 2024 AI & Big Data Conferences: Oxycon, World AI Summit, AI Summit NY, Analytics Summit  

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