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I AgreeAnalysis of Life Sciences Data Mining and Visualization Market Covering 30+ Countries Including Analysis of US, Canada, UK, Germany, France, Nordics, GCC countries, Japan, Korea and many more
The global life sciences data mining and visualization market is set to surpass a valuation of US$ 8.3 billion in 2023 and further expand at a CAGR of 9.1% to reach US$ 19.9 billion by the end of 2033.
Revenue generation from life sciences data mining and visualization accounted for 7% of overall data analytics market in 2022.
Report Attributes |
Details |
Life Sciences Data Mining and Visualization Market Size (2022A) |
US$ 7.5 Billion |
Estimated Market Value (2023E) |
US$ 8.3 Billion |
Forecasted Market Value (2033F) |
US$ 19.9 Billion |
Global Market Growth Rate (2023-2033) |
9.1% CAGR |
North America Market Share (2023) |
~ 28.3% |
North America Market Value (US$ Mn), 2023 |
US$ 2.3 Billion |
Europe Market Share (%), 2023 |
~26.4% |
Europe Market Value (US$ Mn), 2023 |
US$ 2.2 Billion |
China Market Share (%), 2023 |
~11.4% |
China Market Value (US$ Mn), 2023 |
US$ 948 Million |
Top 3 country Market Share (%) |
~40.7% |
Key Companies Profiled |
|
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As per the research by Fact.MR, from 2018 to 2022, the market value of life sciences data mining and visualization market increased at a rate of 8.9% CAGR, with U.S., China and U.K commanding high shares in the global market.
Life sciences data mining and visualization refers to the process of extracting valuable insights and information from large and complex datasets in the life sciences. This can include data from areas such as genetics, genomics, proteomics, metabolomics, and clinical studies. The goal of data mining in the life sciences is to identify patterns, relationships, and trends that can provide new insights into the underlying biology of a disease or the effectiveness of a particular treatment.
Data visualization is an important part of the data mining process, as it allows researchers to easily explore and understand the data and the insights that are generated from it. This can include techniques such as scatter plots, heat maps, and network diagrams to help researchers explore the data and identify patterns and trends.
Industries have benefited greatly from data mining applications. For instance, insurers can now identify fraud and abuse, life sciences firms can improve customer relationship management, doctors can now find the best practices and treatments, and patients can now access more affordable and effective healthcare.
The process of turning difficult data into valuable information is facilitated with the aid of data mining's technique and technology. Fact.MR estimates that the growth of the global life sciences data mining and visualization market will be 2.4 times by 2033, creating an absolute dollar opportunity of US$ 12.3 Bn over the forecast period.
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The shift towards precision medicine, which aims to tailor treatments to the specific genetic and molecular characteristics of individual patients, has led to an increase in the amount of data being collected and analyzed in the life sciences. This has created a demand for data mining and visualization techniques that can help identify patterns and relationships in the data that can inform personalized treatment plans.
Using data mining algorithms, such as machine learning, researchers can predict patient outcomes such as drug response, risk of disease progression, or survival probability. Data mining and visualization can play an important role in precision medicine by helping researchers to identify patterns and relationships in large, complex datasets for more effective treatments and improved outcomes of patients.
As a result, the demand for data mining and visualization in life sciences is estimated to witness considerable growth in successive years for precision medicine.
With the growing amount of personal information being collected and analyzed in life sciences, there is a rising need to ensure that data is handled securely and that privacy is protected. Data mining and visualization can play an important role in this by allowing life science researchers to explore the data in a way that does not compromise the privacy of individuals.
Data mining and visualization tools can be used to anonymize data by removing or masking personal identifiers such as names, addresses, and social security numbers. This can help to protect the privacy of individuals while still allowing researchers to analyze and explore the data.
Data mining and visualization tools can also be used to encrypt data, making it unreadable to unauthorized users. This can benefit to protect sensitive data from being accessed or stolen by unauthorized parties, opening ample opportunities for the market.
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Poor compliance is one of the challenges that companies and organizations face while using data mining and visualization tools in the life sciences. Compliance refers to the adherence to laws, regulations, and standards related to the collection, storage, and use of data. Non-compliance can result in fines, legal action, and damage to an organization's reputation.
To comply with the regulations and standards, organizations must have strong data management and security practices in place, and must ensure that their data mining and visualization activities are aligned with their overall compliance and data governance strategies.
This includes regularly reviewing and updating policies and procedures, training employees on data protection and privacy, and conducting regular assessments of data management and security practices. Modern data warehouses come with role-based access control and have strict oversight on access, ensuring compliance with privacy regulations, which may pose a threat to market growth.
The United States is home to a large and diversified life sciences industry, which includes pharmaceutical, biotechnology, and medical device companies. These industries generate large amounts of data, which creates a need for data mining and visualization tools.
The U.S government has implemented policies to support the life sciences industry and encourage innovation, including promotion of data sharing and collaboration initiatives. According to Fact. MR's estimate, the US market is anticipated to generate US$ 2 billion by 2023.
The U.S has a strong infrastructure for the storage and analysis of big data, which includes robust IT infrastructure, large amounts of computational resources, and well-established data management practices. This makes it a favorable country for life sciences data mining and visualization companies. The US is predicted to hold a market share of 24.5% at global level in 2023 and is expected to grow at a CAGR of 6.7% owing to aforementioned factors.
China's life sciences industry has been growing rapidly in recent years, driven by increased government funding, investments from private companies, and growth in the number of biotech and pharmaceutical companies. This has led to an increase in the amount of data being generated, creating a need for data mining and visualization tools.
China has made significant advances in technology, particularly in the areas of genomics, AI and big data. In addition, the Chinese government has been making significant investments in data-driven research and development, particularly in the field of life sciences.
With the increase of healthcare expenditure in China, leading to the growth of healthcare sector, China is predicted to grow at a CAGR of 7.7%. In 2023, China is anticipated to have a value of US$ 948 Mn, holding a market share of 11.4% at global level.
The pharmaceutical sector generates a large amount of data, including data from preclinical and clinical studies, genomics data, electronic health records, and other sources. This data is being generated at an unprecedented rate, and pharmaceutical companies require data mining and visualization tools to identify and analyze various data points.
The pharmaceutical sector is increasingly focused on developing personalized medicine, which is tailored to the specific characteristics of a patient. Data mining and visualization tools can help researchers to understand the underlying biology of a disease and identify potential drug targets.
Overall, the pharmaceutical sector is expected to be an opportunistic market for the life sciences data mining and visualization market as it requires a large amount of data to be analyzed, providing insights for drug discovery, development, and improving efficiency in the sector. The pharmaceuticals end use industry will have a valuation of around US$ 1.6 Bn in 2023 and hold a share of 19.3% of the overall market.
Cloud-based data mining and visualization in the life sciences field has rising demand as it allows researchers to easily access and analyze large amounts of data that were previously difficult or impossible to work with. Cloud-based solutions offer a number of advantages in this regard, including scalability, flexibility, and cost-efficiency. Additionally, many cloud-based platforms provide powerful data visualization tools that allow researchers to quickly and easily gain insights from their data.
Cloud-based solutions typically have lower upfront costs and can be more cost-effective in the long term, as researchers do not need to invest in expensive hardware or software. On-cloud life sciences data mining and visualization is likely to hold a market valuation of US$ 5.5 Bn in 2023 and hold a market share of 66.3%.
Prominent players of life sciences data mining and visualization globally 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. and Wipro Limited. Companies are developing interactive, user-friendly visualization tools that enable researchers, clinicians, and drug developers to explore and understand large and complex datasets.
The key focus of vendors is to provide high-quality and value-added services that enable customers to gain insights from large and complex datasets, and to make better-informed decisions in the drug development and precision medicine space.
Fact.MR has provided detailed information about the service offering of key vendors of life sciences data mining and visualization positioned across regions, revenue growth, deployment scale, and speculative technological expansion, in the recently published report.
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The market is likely to reach a valuation of US$ 19.9 Bn by the end of forecast period.
The on-cloud deployment of life sciences data mining and visualization is likely to reach a valuation of around US$ 5.5 Bn in 2023.
North America holds the leading market share by around 28.3% in 2023 and is presumed to remain in same growth curve by the end of 2033.
Yearly subscription license structure will have the highest market share of 35.1% in 2023.
Europe region is likely to offer great growth prospect with a market valuation of US$ 2.2 Bn in 2023.
China is expected to hold a market share of around 11.4% in 2023 at global level and is expected to grow in same rate by a CAGR of 7.7%.
Data mining under component segment is expected to reach a market valuation of US$ 2.6 Bn by 2023.