Biological data analysis is the key to new discoveries in disease biology and drug discovery. The rapid proliferation of high-throughput ‘omics’ data has necessitated a need for tools and platforms that allow the researchers to combine and analyse different types of biological data and obtain biologically relevant knowledge. We had previously developed TargetMine, an integrative data analysis platform for target prioritisation and broad-based biological knowledge discovery. Here, we describe the newly modelled biological data types and the enhanced visual and analytical features of TargetMine. These enhancements have included: an enhanced coverage of gene–gene relations, small molecule metabolite to pathway mappings, an improved literature survey feature, and in silico prediction of gene functional associations such as protein–protein interactions and global gene co-expression. We have also described two usage examples on trans-omics data analysis and extraction of gene-disease associations using MeSH term descriptors. These examples have demonstrated how the newer enhancements in TargetMine have contributed to a more expansive coverage of the biological data space and can help interpret genotype–phenotype relations. TargetMine with its auxiliary toolkit is available at https://targetmine.mizuguchilab.org. The TargetMine source code is available at https://github.com/chenyian-nibio/targetmine-gradle.

Question Paper Solutions of chapter Web Mining of Data Warehousing and Data Mining, 3rd Semester , Master of Computer Applications (2 Years)

The Enterprise Data Warehouse (EDW) market is experiencing robust growth, projected to reach a market size of $3455.2 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.6% from 2025 to 2033. This expansion is driven by the increasing need for organizations to consolidate data from disparate sources for improved business intelligence, enhanced decision-making, and streamlined operational efficiency. The rising adoption of cloud-based EDW solutions, fueled by scalability, cost-effectiveness, and accessibility, is a significant factor contributing to this growth. Furthermore, the expanding use of advanced analytics techniques, such as data mining and predictive modeling, within EDWs is further boosting market demand across diverse sectors including healthcare, finance, and retail. The market is segmented by deployment type (web-based and server-based) and application (information processing, data mining, and analytical processing), reflecting the diverse functionalities and deployment models available. Key players, including industry giants like Amazon Web Services, Microsoft, and Google, alongside specialized vendors like Teradata and Snowflake, are aggressively innovating to meet the evolving needs of enterprises. The competitive landscape is characterized by both established players and emerging technology providers. The ongoing trend towards data democratization, where access to data and analytics is broadened within organizations, is fostering demand for user-friendly EDW interfaces and tools. While regulatory compliance and data security remain key restraints, the overall market outlook for EDWs remains positive, with substantial growth potential driven by the continuous rise in data volumes, the growing need for real-time analytics, and increasing investments in digital transformation initiatives across industries globally. The North American market currently holds a significant share due to early adoption and technological advancements, but the Asia-Pacific region is projected to witness rapid growth in the coming years due to increased digitalization and technological infrastructure development.

The Enterprise Data Warehouse (EDW) market is experiencing robust growth, driven by the increasing need for businesses to consolidate and analyze large volumes of data for improved decision-making. The market, valued at $5075.2 million in 2025, is projected to exhibit significant expansion over the forecast period (2025-2033). While a precise CAGR is unavailable, considering the strong market drivers such as the rising adoption of cloud-based solutions, the growing demand for advanced analytics, and the increasing focus on data-driven strategies across various industries, a conservative estimate of the Compound Annual Growth Rate (CAGR) would fall within the range of 10-15% for the forecast period. This growth is fueled by the transition to cloud-based EDW solutions, offering scalability, cost-effectiveness, and enhanced accessibility compared to on-premise systems. Furthermore, the rising adoption of advanced analytics techniques like machine learning and artificial intelligence is further driving the demand for robust EDW solutions capable of handling and processing massive datasets effectively. The market segmentation reveals a strong preference for web-based solutions and a significant demand across applications like information processing, data mining, and analytical processing. Leading players like Amazon Web Services (AWS), Microsoft, and Snowflake are at the forefront of innovation, constantly introducing new features and capabilities to enhance the functionalities and user experience of their EDW offerings. The geographical distribution of the market shows substantial growth across North America and Europe, driven by higher technology adoption rates and increased investments in digital transformation initiatives. However, Asia-Pacific is anticipated to emerge as a rapidly growing region in the coming years, fueled by rising digitalization and the expanding adoption of EDW solutions among large enterprises and government organizations. The key restraints to market growth include the high initial investment costs associated with implementing EDW systems, the need for specialized skills and expertise for effective management and utilization, and concerns about data security and privacy. However, these challenges are progressively being addressed through the emergence of cost-effective cloud-based solutions and the development of user-friendly interface solutions. The market is expected to witness further consolidation as leading vendors continue to expand their product portfolios and service offerings to cater to the ever-evolving needs of the enterprises.

Question Paper Solutions of chapter Module III of Data Warehousing and Data Mining, 7th Semester , Computer Science and Engineering

The Report Covers Global Active Data Warehousing Market Companies and it is segmented by Type of Deployment (On-premise, Cloud, and Hybrid), Size of Enterprise (Small and Medium-sized Enterprises, Large Enterprises), Industry Vertical (BFSI, Manufacturing, Healthcare, Retail), and Geography (North America, Europe, Asia-Pacific, and the Rest of the World). The market size and forecast are provided in terms of values (USD billion) for all the above segments.

Snapshot img

Data Warehousing Market Size 2025-2029

The data warehousing market size is forecast to increase by USD 32.3 billion, at a CAGR of 14% between 2024 and 2029.

The market is experiencing significant growth, driven by the shift from traditional on-premises solutions to cloud-based Software-as-a-Service (SaaS) offerings. Advanced storage technologies, such as columnar databases and in-memory storage, are also fueling market expansion. However, data privacy and security risks continue to pose challenges, necessitating strong security measures. Companies must prioritize data protection and compliance with regulations like GDPR and HIPAA to mitigate risks and maintain customer trust. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) technologies is transforming technology, enabling advanced analytics and insights. Overall, these trends and challenges are shaping the future of the market, offering opportunities for innovation and growth.

What will be the Size of the Market During the Forecast Period?

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The market encompasses the provision of storage systems and related services for managing and analyzing data from various operational and analytical processes. These data and component repositories facilitate statistical analysis, data mining, import export analysis, and other forms of advanced data processing. Virtual and meta data inventory solutions enable real-time views of data from multiple sources, including unstructured, semi-structured, and structured data. Middleware and ETL (Extract, Transform, Load) solutions facilitate data integration from diverse data sources.
Emerging economies and legacy applications continue to drive market growth, as businesses seek to leverage data for competitive advantage. AI and ML technologies are increasingly integrated into systems to enhance data analysis capabilities. The IT & telecom and healthcare industries are significant end-users, with growing demand for solutions in sectors such as finance, retail, and manufacturing.

How is this Industry segmented and which is the largest segment?

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

Deployment

  On-premises
  Hybrid
  Cloud-based


Type

  Structured and semi-structured data
  Unstructured data


End-user

  BFSI
  Healthcare
  Retail and e-commerce
  Others


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan
    South Korea


  Middle East and Africa



  South America

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

The on-premises market caters to organizations that prefer installing and managing solutions on their own servers. This model's appeal is due to factors like data security, control, and end-to-end quality control. On-premises solutions offer workflow streamlining, reporting, and faster response times. The data's security is a significant concern, and the complete ownership and management by the buyer organization ensure its protection.

Key drivers for this segment include the need for data governance, compliance, and the ability to integrate various data sources seamlessly. Additionally, industries such as finance, healthcare, and manufacturing, where data security is paramount, often opt for on-premises solutions. These systems enable advanced analytics, business intelligence, and real-time data processing, providing valuable insights for strategic decision-making.

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The on-premises segment was valued at USD 11.33 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 50% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The market continues to thrive due to the region's early adoption of advanced technologies in industries such as manufacturing, retail, and banking, financial services, and insurance (BFSI). The presence and penetration of leading companies In these sectors fuel market growth. With several advanced economies in North America, the requirement for data warehousing, including data processing, outsourcing, and Internet services and infrastructure, is significant.

Additionally, the integration of cloud-based services, automation solutions, and AI with operational and supply chain processes

Question Paper Solutions of Data Warehousing and Data Mining (MCAN-E305B),3rd Semester,Master of Computer Applications (2 Years),Maulana Abul Kalam Azad University of Technology

Question Paper Solutions of chapter Module IV of Data Warehousing and Data Mining, 7th Semester , Computer Science and Engineering

Snapshot img

Enterprise Data Warehouse Market Size 2024-2028

The enterprise data warehouse market size is forecast to increase by USD 39.24 billion, at a CAGR of 30.08% between 2023 and 2028. The market is experiencing significant growth due to the data explosion across various industries. With the increasing volume, velocity, and variety of data, businesses are investing heavily in EDW solutions and data warehousing to gain insights and make informed decisions. A key growth driver is the spotlight on innovative solution launches, designed with cutting-edge features and functionalities to keep pace with the ever-evolving demands of modern businesses.

However, concerns related to data security continue to pose a challenge in the market. With the increasing amount of sensitive data being stored in EDWs, ensuring its security has become a top priority for organizations. Despite these challenges, the market is expected to grow at a strong pace, driven by the need for efficient data management and analysis.

What will be the Size of the Enterprise Data Warehouse Market During the Forecast Period?

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An enterprise data warehouse (EDW) is a centralized, large-scale database designed to collect, store, and manage an organization's valuable business information from multiple sources. The EDW acts as the 'brain' of an organization, processing and integrating data from various physical recordings, flat files, and real-time data sources. Data engineering plays a crucial role in the EDW, responsible for data ingestion, cleaning, and digital transformation. Business units across the organization rely on Business Intelligence (BI) tools like Tableau, PowerBI, Qlik, and data visualization tools to extract insights from the EDW. The EDW is a collection of databases, including Teradata, Netezza, Exadata, Amazon Redshift, and Google BigQuery, which serve as the backbone for data-driven decision-making.

Moreover, the cloud has significantly impacted the EDW market, enabling cost-effective and scalable solutions for businesses of all sizes. BI tools and data visualization tools enable departments to access and analyze data, improving operational efficiency and driving innovation. The EDW market continues to grow, with organizations recognizing the importance of a centralized, integrated data platform for managing their valuable assets.

Enterprise Data Warehouse Market Segmentation

The enterprise data warehouse market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD Billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

Product Type

  Information and analytical processing
  Data mining


Deployment

  Cloud based
  On-premises


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    India


  Middle East and Africa



  South America

By Product Type

The information and analytical processing segment is estimated to witness significant growth during the forecast period. The market is witnessing significant growth due to the increasing data requirements of various industries such as IT, BFSI, education, healthcare, and retail. The primary function of an EDW system is to extract, transform, and load data from source systems into a central repository for data integration and analysis. This process enables businesses to gain timely insights and make informed decisions based on historical data and real-time analytics. EDW systems are designed to be scalable to cater to the data processing needs of the largest organizations. The use of Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes in data warehousing has become a popular trend to address processing bottlenecks and ensure Service Level Agreements (SLAs) are met.

Furthermore, business users increasingly rely on these systems for business intelligence and data analytics. Big Data technologies like Hadoop MapReduce and Apache Spark are being integrated with ETL tools to enable the processing of large volumes of data. Precisely, as a pioneer in data integration, offers solutions that cater to the needs of various business teams and departments. Data visualization tools like Tableau, PowerBI, Qlik, Teradata, Netezza, Exadata, Amazon Redshift, Google BigQuery, Snowflake, and Data virtualization are being used to gain insights from the data in the EDW. The history of transactions and multiple users accessing the data make the need for data warehousing more critical than ever.

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The information and analytical processing segment was valued at USD 3.65 billion in 2018 and showed a gradual increase during the forecast period.

Regional Insights

APAC is estimated to contribute 32% to the growt

Global Data Warehouse as a Service (DWaaS) Market valued at USD 5.03 Billion in 2023 and is predicted to USD 30.37 Billion by 2032, with a CAGR of 22.1%.

Question Paper Solutions of Data Warehousing and Data Mining (Old),7th Semester,Computer Science and Engineering,Maulana Abul Kalam Azad University of Technology

The Data Warehousing Market is projected to grow at 16.6% CAGR, reaching $69.64 Billion by 2029. Where is the industry heading next? Get the sample report now!

Global Data Warehousing Market size worth at USD 11.03 Billion in 2023 and projected to USD 41.31 Billion by 2032, with a CAGR of 15.8% between 2024-2032.

The data warehouse as a service market size was over USD 5.05 billion in 2024 and is expected to exceed USD 52.8 billion by the end of 2037, growing at over 22.8% CAGR during the forecast period i.e., between 2025-2037. North America industry is poised to generate revenue of about USD 20 Billion by 2037, backed by growing adoption of cloud technology including public cloud as well as private cloud.

The Data Warehouse As A Service Market is projected to grow at 21.1% CAGR, reaching $18.38 Billion by 2029. Where is the industry heading next? Get the sample report now!

The open-source big data tools market is experiencing robust growth, driven by the increasing need for scalable, cost-effective data management and analysis solutions across diverse sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising volume and velocity of data generated across industries, from banking and finance to manufacturing and government, necessitate powerful and adaptable tools. Secondly, the cost-effectiveness and flexibility of open-source solutions compared to proprietary alternatives are major drawcards, especially for smaller organizations and startups. The ease of customization and community support further enhance their appeal. Growth is also being propelled by technological advancements such as the development of more sophisticated data analytics tools, improved cloud integration, and increased adoption of containerization technologies like Docker and Kubernetes for deployment and management. The market's segmentation across application (banking, manufacturing, etc.) and tool type (data collection, storage, analysis) reflects the diverse range of uses and specialized tools available. Key restraints to market growth include the complexity associated with implementing and managing open-source solutions, requiring skilled personnel and ongoing maintenance. Security concerns and the need for robust data governance frameworks also pose challenges. However, the growing maturity of the open-source ecosystem, coupled with the emergence of managed services providers offering support and expertise, is mitigating these limitations. The continued advancements in artificial intelligence (AI) and machine learning (ML) are further integrating with open-source big data tools, creating synergistic opportunities for growth in predictive analytics and advanced data processing. This integration, alongside the ever-increasing volume of data needing analysis, will undoubtedly drive continued market expansion over the forecast period.

The market is projected to be valued at $X million in 2024, driven by factors such as increasing consumer awareness and the rising prevalence of industry-specific trends. The market is expected to grow at a CAGR of Y%, reaching approximately $Z million by 2034.

Question Paper Solutions of year 2022 of Data Warehousing and Data Mining, 3rd Semester , Master of Computer Applications (2 Years)