The market for Life Sciences Data Mining and Visualization Software is projected to reach a value of [MM] million by 2033, exhibiting a CAGR of [XX]% during the forecast period from 2025 to 2033. The surge in demand for software that can handle vast and complex life sciences data, including genomics, proteomics, and clinical trial data, is fueling the growth of this market. The increasing adoption of cloud-based solutions and the growing need for data-driven insights to improve drug discovery and development processes are further contributing to market expansion. Among the key players in the Life Sciences Data Mining and Visualization Software market are Accenture, Cognizant, Dundas Data Visualization Inc., IBM Corporation, InetSoft Technology Corporation, Information Builders, IQVIA, Microsoft Corporation, MicroStrategy Inc., Oracle Corporation, Pentaho Corporation, SAP SE, SAS Institute Inc., Tableau Software, Take Solutions Limited, TIBCO Software Inc., Wipro Limited, Guangzhou Smartbi Software Co., Ltd., and Fan Ruan Software Co., Ltd. These companies offer a range of software solutions designed to meet the specific data mining and visualization needs of the life sciences industry.

The Lifesciences Data Mining and Visualization market is experiencing robust growth, driven by the increasing volume of biological data generated through genomics, proteomics, and clinical trials. The need for efficient analysis and interpretation of this complex data to accelerate drug discovery, personalize medicine, and improve patient outcomes is fueling market expansion. A Compound Annual Growth Rate (CAGR) of approximately 15% is projected for the period 2025-2033, indicating significant market potential. The pharmaceutical and biotech sectors are major contributors, with a strong demand for advanced analytical tools to manage large datasets and extract actionable insights. Contract Research Organizations (CROs) are also actively adopting these solutions to improve efficiency and reduce costs in their research and development processes. The market is segmented by deployment type (on-premise, on-demand, both) and application (academia, biotech, government, pharmaceuticals, CROs, others). On-demand solutions are witnessing greater adoption due to their scalability and cost-effectiveness, particularly among smaller organizations. Geographic growth is expected across regions, with North America and Europe maintaining a significant market share due to the presence of established players and extensive research infrastructure. However, Asia Pacific is poised for rapid expansion driven by increasing government investments in healthcare and growing adoption of advanced technologies. Competitive landscape includes established players like Tableau, SAP, IBM, and SAS, along with several specialized data visualization providers. The market's future growth is dependent on factors such as advancements in data analytics techniques, increasing data volumes, and the growing focus on data security and regulatory compliance within the life sciences industry. The market's future hinges on several factors. The continuous evolution of data analytics techniques, including artificial intelligence and machine learning, will create more sophisticated tools for life sciences data analysis. The exponential growth of biological data, driven by next-generation sequencing and other high-throughput technologies, will sustain demand for efficient data mining and visualization solutions. Additionally, regulations regarding data privacy and security will influence the development and adoption of these tools, with robust security features becoming paramount. The increasing emphasis on personalized medicine and precision therapies will further bolster the market, as researchers require advanced analytics to understand individual patient responses and tailor treatments accordingly. Finally, the integration of data mining and visualization tools with other life science software and platforms will drive greater adoption and efficiency within the industry.

The advanced and predictive analytics market is experiencing robust growth, driven by the increasing adoption of data-driven decision-making across various sectors. The market's expansion is fueled by several key factors, including the exponential growth of data volume and velocity, the decreasing cost of data storage and processing, and the rising demand for real-time insights. Businesses across industries are leveraging advanced analytics techniques like machine learning, deep learning, and artificial intelligence to improve operational efficiency, enhance customer experience, optimize resource allocation, and mitigate risks. The banking and financial services, insurance, and healthcare sectors are particularly significant adopters, using predictive models for fraud detection, risk assessment, customer segmentation, and personalized medicine. However, challenges such as data security concerns, the need for skilled data scientists, and the complexity of implementing and integrating advanced analytics solutions continue to present hurdles for wider adoption. The market segmentation reveals a significant contribution from the banking and financial services sector, followed closely by insurance and healthcare. Geographical distribution shows strong growth in North America and Europe, driven by early adoption and mature technological infrastructure. However, the Asia-Pacific region is expected to witness significant growth in the coming years due to increasing digitalization and government initiatives promoting data analytics. The competitive landscape is characterized by both established technology giants like IBM, Microsoft, and SAP, and specialized analytics companies like SAS and FICO, leading to innovation and diverse solutions. Future growth will be shaped by advancements in cloud computing, big data technologies, and the development of more sophisticated and explainable AI algorithms. The continued focus on data privacy and regulatory compliance will also play a crucial role in shaping the market's trajectory.

Context SAP is one of the largest companies in the world, providing enterprise software for e.g. resource planning. This dataset consists of their official press releases since the beginning of the 2000s, which are currently available at https://news.sap.com/press-room/.

Content Each item consists of a headline, describing the respective title of the press release. The data has been labeled in a weakly supervision manner into the following categories:

Partnership: when the press release is mostly about a joint work or collaboration of SAP and another company, e.g. "SAP and IBM Collaborate to Serve Transportation and Logistics Industry" Award: when SAP or one of its subsidiaries has been awarded, e.g. "SAP Recognized as a Leader in Gartner Magic Quadrant for Manufacturing Execution Systems and Ranked #1 in ARC Advisory Group MES Market Research Study" Financials: SAP Announces Preliminary Fourth Quarter and Full Year 2016 Results People: press releases dedicated to e.g. hiring of Chief X Officers, such as "Jonathan Becher Named Chief Digital Officer and Leads SAP Digital; Maggie Chan Jones Will Join SAP as Chief Marketing Officer" Solution: releases about e.g. new solutions or tools and frameworks, such as "SAP App Center Simplifies Acquiring and Managing Partner Solutions" Merger / Investment: when SAP has bought or invested into a company, e.g. "SAP Completes Acquisition of Concur" Story: when SAP released stories such as case studies or success stories, e.g. "SAP Broadens Its Developer Community Engagement With Code for America Sponsorship" Acknowledgements This data is collected from publicly available SAP resources.

Inspiration Why don't you try out to classify each headline into a specific label? This could help analysts a lot to stay up-to-date for the most important press releases. Or analyze topics within certain clusters.

License

CC0

Original Data Source: SAP Press Releases

The global Data Analytics Software market is experiencing robust growth, driven by the increasing adoption of cloud-based solutions, the expanding volume of big data, and the rising demand for data-driven decision-making across various industries. The market, valued at approximately $150 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% during the forecast period of 2025-2033. This significant expansion is fueled by several key factors. Businesses are increasingly recognizing the strategic importance of data analytics in optimizing operations, enhancing customer experiences, and gaining a competitive edge. The shift towards cloud-based solutions offers scalability, cost-effectiveness, and accessibility, making data analytics accessible to a broader range of businesses, from SMEs to large enterprises. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are integrating seamlessly into data analytics platforms, providing more sophisticated insights and predictive capabilities. The market's growth is further segmented by deployment model (on-premise vs. cloud-based) and user type (SMEs vs. large enterprises), reflecting the diverse needs and adoption rates across various business segments. While the market presents substantial opportunities, certain challenges persist. Data security and privacy concerns remain paramount, requiring robust security measures and compliance with evolving regulations. The complexity of implementing and managing data analytics solutions can also pose a barrier to entry for some organizations, requiring skilled professionals and substantial investments in infrastructure and training. Despite these challenges, the long-term outlook for the Data Analytics Software market remains highly positive, driven by continuous technological innovation, growing data volumes, and the increasing strategic importance of data-driven decision-making across industries. The market's evolution will continue to be shaped by the ongoing integration of AI and ML, the expansion of cloud-based offerings, and the increasing demand for advanced analytics capabilities. This dynamic landscape will present both challenges and opportunities for existing players and new entrants alike.

The Metals and Mining Industry Software market is experiencing robust growth, driven by the increasing need for operational efficiency, enhanced safety protocols, and sustainable practices within the sector. The market's expansion is fueled by the adoption of cloud-based solutions offering scalability and cost-effectiveness compared to on-premise systems. Large enterprises are leading the adoption, leveraging advanced analytics and AI-powered solutions to optimize resource management, predict maintenance needs, and improve production yields. However, the market faces challenges such as high initial investment costs for sophisticated software and the need for robust cybersecurity measures to protect sensitive operational data. Furthermore, integration with legacy systems can present a significant hurdle for some companies. The market is segmented by deployment type (on-premise and cloud-based) and user type (large enterprises and SMEs). We project a compound annual growth rate (CAGR) of 12% for the period 2025-2033, indicating a significant market expansion. This growth is expected to be driven primarily by increased automation, data-driven decision-making, and the growing adoption of digital transformation initiatives across the metals and mining industry globally. The geographical distribution of the market reveals significant regional variations. North America and Europe currently hold the largest market shares, driven by early adoption of advanced technologies and established digital infrastructure. However, the Asia-Pacific region is poised for significant growth, fueled by increasing industrialization and investment in mining operations in countries like China and India. The competitive landscape is characterized by a mix of established players like IBM, SAP, and Microsoft, alongside specialized niche providers focusing on specific software solutions for the mining industry. This competitive environment is driving innovation and enhancing the overall value proposition for end-users. Future growth will likely be shaped by the development of integrated platforms offering a comprehensive suite of software solutions and the growing emphasis on sustainability and environmental compliance within the industry.

The advanced analytics market, valued at $47.38 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 21.46% from 2025 to 2033. This surge is driven by several key factors. The increasing availability of large datasets, fueled by the proliferation of IoT devices and digitalization across various sectors, provides rich fodder for advanced analytical techniques. Furthermore, the rising demand for data-driven decision-making across industries like BFSI (Banking, Financial Services, and Insurance), retail, healthcare, and IT & Telecommunications is a significant catalyst. Businesses are leveraging advanced analytics for improved risk management, customer segmentation, predictive maintenance, fraud detection, and personalized services, leading to increased operational efficiency and competitive advantage. The adoption of cloud-based analytics platforms also contributes to market expansion, offering scalability, cost-effectiveness, and accessibility to a wider range of users. Specific analytical techniques like predictive analytics are witnessing particularly strong growth, owing to their ability to forecast future outcomes and inform proactive strategies. While the market enjoys significant growth potential, certain challenges remain. Data security and privacy concerns continue to be a major hurdle, requiring robust data governance frameworks and compliance with regulations like GDPR. The need for skilled professionals capable of implementing and interpreting advanced analytics also presents a limitation. However, the ongoing investments in education and training programs aimed at bridging this skills gap are likely to mitigate this constraint over the forecast period. The market's segmentation, encompassing statistical, text, risk, and predictive analytics across diverse end-user industries, presents numerous opportunities for specialized solutions and targeted market penetration by established players like IBM, SAS, Oracle, and emerging technology providers. Competition is expected to remain intense, with continuous innovation and mergers and acquisitions shaping the market landscape. Recent developments include: November 2022: IBM has announced new software, IBM Business Analytics Enterprise, designed for businesses to dismantle data and analytics silos so they can act quickly on data-driven insights and navigate unforeseen disruptions. The software provides intelligence planning, budgeting, reporting, forecasting, and dashboard capabilities that give users a comprehensive view of data sources across their entire organization., October 2022: SAS has announced a collaboration with the Monetary Authority of Singapore (MAS)-led Veritas consortium to integrate and operationalize the Veritas toolkit with the SAS Viya platform, intending to improve trustworthy artificial intelligence (AI) adoption in the financial services sector. The integration allows for assessing fairness in analytical models by utilizing SAS Viya's out-of-the-box natural language generation and workflow capabilities.. Key drivers for this market are: Growing Need to Prevent Fraudulent Activities, Increasing Demand to Counter Big Data Challenges; Growing Digitization Trends and Increased Digital Data Production; Technological Developments of Advanced Analytics Solutions. Potential restraints include: Growing Need to Prevent Fraudulent Activities, Increasing Demand to Counter Big Data Challenges; Growing Digitization Trends and Increased Digital Data Production; Technological Developments of Advanced Analytics Solutions. Notable trends are: Growing Digitization Trends and Increased Digital Data Production to Drive the Market Growth.

This dataset contains 1359 reports obtained with Prospector, an open-source repository mining tool developed by SAP Security Research and the AssureMOSS consortium.

The vulnerabilities covered by this dataset correspond to the union of the vulnerability from project KB and those from the SAP-internal vulnerability dataset built by SAP Security Research while developing and operating Eclipse Steady.

The global mining digitalization market, valued at $5,789.1 million in 2025, is projected to experience robust growth, driven by increasing demand for enhanced efficiency, safety, and sustainability in mining operations. A compound annual growth rate (CAGR) of 4.0% from 2025 to 2033 indicates a steady expansion, fueled by several key factors. The adoption of intelligent hardware, including autonomous vehicles, drones, and sensors, is revolutionizing mining processes, leading to improved resource allocation and reduced operational costs. Simultaneously, sophisticated software systems and advanced analytics are enabling predictive maintenance, optimizing production planning, and enhancing overall mine management. The IT, energy, and industrial sectors are significant adopters, with increasing integration across the mining value chain. While initial investment costs can be a restraint, the long-term benefits of increased productivity, reduced risks, and improved environmental performance are driving widespread adoption. Key players like Caterpillar, Sandvik AB, and SAP are actively investing in research and development, further accelerating market growth. Regional variations exist, with North America and Europe currently holding significant market shares due to advanced technological infrastructure and robust regulatory frameworks. However, rapid growth is anticipated in the Asia-Pacific region, driven by large-scale mining projects and increasing government initiatives to improve mining sector efficiency. The segmentation of the market into intelligent hardware, software systems, and applications across various sectors (IT, energy, industrial, and others) reflects the diverse technological advancements shaping the industry. The competitive landscape is characterized by both established mining equipment manufacturers and technology providers, leading to strategic partnerships and collaborations to offer comprehensive digitalization solutions. Future growth will be further influenced by advancements in artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), enabling more autonomous and data-driven mining operations. The continued focus on improving safety protocols and environmental sustainability will also play a critical role in shaping future market dynamics. We project a continued increase in market size, driven by these factors, though the exact figures will vary based on economic conditions and technological innovation.

This dataset contains 259 vulnerability statements found with Prospector, an open-source repository mining tool developed by SAP Security Research and the AssureMOSS consortium.

The vulnerabilities covered by this dataset are a subset of a larger vulnerability dataset built by SAP Security Research while developing and operating Eclipse Steady.

This dataset contains 307 vulnerability statements found with Prospector, an open-source repository mining tool developed by SAP Security Research and the AssureMOSS consortium.

The vulnerabilities covered by this dataset are a subset of those that appear in the "depth" dataset at https://patch-tracer.github.io/

The global smart mining market, valued at $34.16 billion in 2025, is poised for steady growth, exhibiting a compound annual growth rate (CAGR) of 0.21% from 2025 to 2033. This relatively low CAGR suggests a market maturing beyond its initial explosive growth phase, indicating a shift towards sustained, incremental advancements rather than rapid expansion. Key drivers include the increasing need for enhanced safety and productivity in mining operations, coupled with the growing adoption of data analytics for optimizing resource extraction and reducing operational costs. The integration of smart technologies, such as IoT sensors, AI-powered predictive maintenance systems, and advanced automation solutions, are significantly improving efficiency and minimizing environmental impact. The market is segmented by solution (smart control systems, asset management, safety & security, data analytics software, monitoring systems, and other solutions), service type (system integration, consulting, engineering & maintenance), and mining type (underground and surface mining). The diverse range of solutions caters to the specific needs of various mining operations, driving market diversification. While the market's growth is projected to be moderate, the continuous technological advancements and increasing demand for operational efficiency in the mining sector are expected to contribute to consistent market expansion throughout the forecast period. Despite the relatively low CAGR, several factors contribute to sustained market growth. The increasing pressure on mining companies to improve safety records and reduce operational downtime fuels the adoption of smart mining technologies. The ability of these technologies to improve resource allocation, reduce waste, and enhance overall productivity presents a compelling value proposition for mining operators. The geographical distribution of the market is likely to reflect established mining hubs, with North America, Europe, and Asia-Pacific commanding significant market shares. However, developing economies with burgeoning mining sectors in regions like Latin America and Africa present promising opportunities for future market expansion. Competition among established technology providers like Cisco, Rockwell Automation, and SAP, along with specialized mining technology companies, will continue to drive innovation and affordability, ensuring the long-term viability of the smart mining market. Recent developments include: June 2022 - Metso Outotec collaborated with Dynamox on using Dynamox's condition monitoring platform in mining and aggregating processes. Metso Outotec is offering the solution to the company's installed equipment base. Dynamox is an addition to Metso Outotec's partner ecosystem and helps develop and provide easy-to-use and sustainable digital solutions to customers. The company is further upgrading in mining using AI and analytics solutions., May 2022 - Epiroc's new Boomer S10 S gives a major leap in the productivity of mine development and cost-efficiency. The Boomer S10 S provides near-surgical precision in drilling and major cost savings throughout the cycle. Boomer S10 S offers up to 25 % more development than traditional one-boom jumbo when applying the high-performance development method, which works during the entire drill cycle in the mining operations.. Key drivers for this market are: Rising Adoption of Wireless Monitoring and Centralized Solutions among Several Large Mining Installations, Technological Advancements and Convergence of Various Digital Transformation Practices. Potential restraints include: Rising Adoption of Wireless Monitoring and Centralized Solutions among Several Large Mining Installations, Technological Advancements and Convergence of Various Digital Transformation Practices. Notable trends are: Data Management and Analytics Software is Expected to Show Highest Growth.

Market Overview The global Text Mining market is estimated to expand at a robust CAGR of XX% over the forecast period of 2025-2033, reaching a value of million in 2033. The growing volume of unstructured text data across industries, such as customer feedback, social media posts, and business documents, is driving the demand for text mining solutions. Businesses are increasingly seeking to extract meaningful insights from this data to improve decision-making, optimize operations, and enhance customer experiences. Key Market Trends and Market Segments Key market drivers include the rise of data science and analytics, the need for competitive advantage, and the increasing adoption of cloud-based text mining solutions. Trends include the integration of artificial intelligence (AI) and machine learning (ML) capabilities for advanced sentiment analysis and predictive modeling. The cloud-based segment is expected to dominate the market due to its cost-effectiveness, scalability, and ease of deployment. By application, data analysis and forecasting dominates the market, with customer relationship management (CRM) emerging as a significant growth segment. Major companies in the market include IBM, Microsoft, SAS Institute, and SAP SE. Regionally, North America currently holds the largest market share, followed by Europe and Asia Pacific. Text Mining Market Report This comprehensive report analyzes the dynamic text mining market, providing insights into its current trends, growth drivers, challenges, and opportunities. The market is anticipated to reach $100 million by 2028, exhibiting a CAGR of 15.2% during the forecast period (2022-2028).

Business intelligence and analytics software publishers' revenue is expected to swell at a compound annual rate of 1.9% over the five years through 2024-25 to reach £884.9 million. Strong growth has been fuelled by rising business software investment, IT and telecommunications adoption, advances in computing technology and the digitalisation of business processes. This has driven the advent of big data, providing new data sets which can interface with business analytics software. Many software products, including customer relationship management and enterprise resource planning systems, have become basic tools for managing large companies. The largest publishers have pursued acquisition activity to take control of cloud companies and data analytics businesses. These industry giants are generally selective with acquisitions, embracing the switch to software as a service and adopting the low-cost cloud model. The industry has demonstrated resilience amid turbulent times, continuing on a growth path in recent years. This is primarily a result of the rapid digitisation spurred by the pandemic. As remote work became the new norm and businesses faced the necessity of managing expansive data sets efficiently, they turned to analytics software. Despite fiscal stresses, companies continued investing in software subscriptions, recognising the indispensable use of applications in a remote work environment. As such, subscriptions and sales of cloud-based software witnessed noticeable growth. Revenue is forecast to climb by 1.9% in 2024-25, with profit also expected to edge up as demand remains strong. Over the five years through 2029-30, revenue is expected to climb at a compound annual rate of 2.9% to reach £1 billion. Heightened adoption of industry-specific software among small and medium-size enterprises (SMEs) is projected to fuel growth. The ongoing transition towards business intelligence apps hosted on external servers and accessible via secure internet connections – known as software as a service (SaaS) – will open up new possibilities. While workforce complications and restrictions on the freedom of movement present potential challenges, the industry's future still looks strong, characterised by a continued focus on research and development and aggressive acquisition strategies from the biggest publishers.

The market for Opinion Mining Software is expanding at a remarkable pace, driven by the surge in social media usage, e-commerce, and customer feedback. Projected to reach a value of several million USD by 2033, this market exhibits a promising CAGR of XX%. Key factors fueling its growth include the rising demand for customer sentiment analysis, improved customer service, and the need for data-driven decision-making. Significant market segments include application (large enterprises, SMEs) and type (on-premises, cloud-based). Leading players in the industry include IBM, Clarabridge, OpenText, SAP, SAS, Basis Technology, and Microsoft. The geographical landscape shows strong growth prospects in North America, Europe, and Asia Pacific, with China, India, and the United States emerging as key markets. However, restraints such as data privacy concerns and the availability of skilled professionals may present challenges to market growth.

The global digital mining solutions market is experiencing robust growth, driven by the increasing need for enhanced efficiency, safety, and sustainability in mining operations. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of automation and data analytics technologies across mining operations is streamlining processes, reducing operational costs, and improving overall productivity. Secondly, stringent government regulations focused on environmental protection and worker safety are compelling mining companies to invest in advanced digital solutions. Finally, the growing demand for critical minerals like lithium and cobalt, essential for electric vehicles and renewable energy technologies, is further driving investment in sophisticated mining technologies to optimize extraction and processing. The increasing connectivity and adoption of cloud-based solutions are also significantly contributing to market growth. The market is segmented by application (underground and surface mining) and solution type (logistics, data & operations management, safety & security, connectivity, analytics, remote management, and asset management software). While all segments are experiencing growth, the data & operations management and analytics solutions segments are expected to witness the most significant expansion due to the increasing value of real-time data analysis for optimized decision-making. Geographically, North America and Asia-Pacific are currently leading the market due to the high concentration of mining activities and early adoption of digital technologies in these regions. However, regions such as Europe and South America are expected to experience substantial growth in the coming years due to increasing investments in modernization and technological advancements within their mining sectors. Key players like Cisco Systems, AVEVA Group, and Hexagon are actively shaping the market through strategic partnerships, technological advancements, and acquisitions. The competitive landscape is characterized by both established technology providers and specialized mining solution companies, leading to continuous innovation and market evolution.

This folder contains the datasets created for the paper "Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation", submitted to the BPM Conference 2025.It contains the "data_courpus.pkl" created from the SAP-SAM Model Collection.Also, it contains the used training set, test set, as well as the collective dataset as filtered according to the paper.Reference and legal info:The corpus and the benchmark datasets are generated using the SAP-SAM dataset:Kampik, T., Warmuth, C., Sola, D., Schäfer, B., Axworthy, L., Ivarsson, E., Ouda, K., & Eickhoff, D. (2022). SAP Signavio Academic Models (0.5.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7012043The SAP-SAM dataset is published with a specific license (see "Rights"), which, therefore, also applies to the data published in this record.

This dataset contains 1316 reports obtained with Prospector, an open-source repository mining tool developed by SAP Security Research and the AssureMOSS consortium.

The vulnerabilities covered by this dataset correspond to a subset of the vulnerabilities from the Tracer "depth" dataset, obtained from https://patch-tracer.github.io