Organizations use several methods to minimize their market offer and acquire an edge in the strong Data Science Platform industry. A focus process involves separation, where companies want to stand apart by delivering unique features and high-level capabilities in their data science platforms. It might include robust AI computations, intuitive UIs, or a constant mix of data instruments. Companies strive to attract clients searching for certain features and establish themselves as high-quality data science providers through separation to build client loyalty.
Cost authority is another important Data Science Platform market mechanism. By improving operational efficiency, using economies of scale, and conducting productive expense board practices, organizations try to make smart decisions. This strategy attracts budget-conscious customers and boosts market share. By offering powerful data science platforms at low prices, cost-conscious companies hope to become the top choice for companies seeking affordable but powerful data science solutions.
Market division is crucial to Data Science Platform companies' market share positioning strategies. Companies customize their platforms to meet the needs of different businesses. This involves developing marketing and sales strategies and providing specific solutions. Market division allows companies to specialize in specialized areas, expanding their customer base and market share.
Key partnerships are becoming more common in the Data Science Platform sector. Organizations understand the benefits of partnering with innovation, data, or industry experts to improve platform contributions. Cooperative efforts let companies expand their platforms, enter new markets, and profit from correlation. Organizations increase market share by expanding clientele and increasing cooperation.
industry share positioning in the Data Science Platform industry requires strong branding and marketing. Laying forth a picture's strengths builds credibility and recognition. Companies sell their uniqueness, reliability, and resilience. A strong brand presence attracts new customers and strengthens existing ones, helping to grow market share.
Continuous development underpins the Data Science Platform industry. Organizations invest in innovation to better their platforms. This might contain trend-setting advances like normal language processing, automated model sending, or better collaborative effort highlights. Creative solutions meet customer needs and position companies as industry leaders, attracting associations that focus on cutting-edge and future-ready data science platforms.
Report Attribute/Metric | Details |
---|---|
Market Opportunities | Rising adoption of advanced technology. |
Market Dynamics | Astonishing Growth of big data. Rising adoption of cloud-based solutions. |
Data Science Platform Market Deployment was valued at USD 100.9 billion in 2022. The Data Science Platform market industry is projected to grow from USD 120.27 Billion in 2023 to USD 345.0 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 19.20% during the forecast period (2023 - 2030). Technological advancements are happening rapidly with increasing investments in R&D. As businesses grow, so does the need for technologies that increase productivity and efficiency. These are the key market drivers enhancing market growth.
Figure 1: Data Science Platform Market Size, 2022-2030 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Data Science Platform Market Trends
Data science platforms are currently being used increasingly due to the various benefits these platforms offer. The software provides open-source tools with remarkable flexibility and scalability of computing resources. Also, it's easy to be consistent with different data schemas. Additionally, the platform supports version control, enabling data science teams to collaborate on projects without losing recently completed work. Hence, these advantages significantly contribute to market expansion during the forecast period.
Furthermore, factors such as surging reliance on machine learning and the surging propensity of enterprises for data-intensive business strategies will accelerate the overall market expansion over the forecast period. Furthermore, the surging adoption of cloud-based solutions and services is expected to drive the Growth of the data science platform market. Increased demand for analytical tools will further positively impact the market growth rate during the forecast period.
Increasing R&D investment is estimated to bring lucrative opportunities to the market, which will further expand the growth rate of the data science platform market in the future. Moreover, advancements in technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) further provide numerous growth opportunities for the market. These are essential factors driving the Data Science Platform market revenue growth.
Based on Business Function, the Data Science Platform market segmentation includes marketing, sales, logistics, and human resources. The sales classified segment held the majority share in 2022, contributing most of the Data Science Platform market revenue due to the various advantages offered, such as the use of data science, marketing, and sales departments can gain a deeper understanding of buyer personas and spend marketing budgets accordingly, generating more return on investment (ROI). Apart from this, factors such as reduced financial risk due to precise expense calculation, more predictable revenue generation, and enhanced customer experience contribute to the platform's adoption in this segment.
Deployment has bifurcated the Data Science Platform market data into on-demand and on-premises. On-Premise has a considerable share of the market. Cloud computing refers to storing, managing, and processing data via networks of remote servers, which are typically accessed via the Internet. Enterprises mostly in heavily regulated industry verticals, such as BFS, healthcare and life sciences, and manufacturing, Opt for the on-premises deployment model of a Data Science Platform. Furthermore, large enterprises with sufficient IT resources are expected to opt for the on-premises deployment model. On-premises is the most reliable deployment mode, which an enterprise can rely on for a high level of control and security. Enterprises need to purchase a license or a copy to deploy cloud-based solutions.
Figure 2: Data Science Platform Market by Verticals, 2022 & 2030 (USD billion)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
Based on Verticals, the Data Science Platform industry has been segmented into BFSI, healthcare, retail, IT, and transportation. The healthcare segment is expected to grow over the forecast period. One of the major applications of the platform is medical imaging. The strong focus on advancing healthcare services has contributed to the rapid adoption of technology in the field.
By Region, the study provides market insights into North America, Europe, Asia-Pacific, and the Rest of the World. The North American Data Science Platform market, which accounted for USD 37.1 billion in 2022, is expected to exhibit a significant CAGR growth during the study period. This is due to the increasing focus of key market players in the Region on further developing these platforms. For example, in February 2020, technology company Oracle announced the launch of a cloud-based data science platform. New platform capabilities include audibility, reproducibility, team security policies, model catalogs, and shared projects.
Further, the significant countries studied in the market report are The U.S., Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 3: DATA SCIENCE PLATFORM MARKET SHARE BY REGION 2022 (%)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
Europe's Data Science Platform market accounts for the second-largest market share. With the rise of data-driven digital transformation, more and more companies in the Region are adopting the technology to drive Growth. The market in Asia Pacific is expected to register the highest CAGR during the forecast period. Increasing lifetime value, cost of acquisition, and customer retention drive this Growth. Further, the German Data Science Platform market held the largest market share, and the U.K. Data Science Platform market was the fastest-growing market in the European Region.
The Asia-Pacific Data Science Platform Market is expected to grow at the fastest CAGR from 2022 to 2030. The Growth of the industry in the Region is primarily driven by factors such as rising spending on big data technologies in economies such as India and China, surging mobile data traffic resulting in rapidly increasing volume and complexity, and emerging markets—application of IoT and artificial intelligence in business operations. Moreover, the China Data Science Platform market held the largest market share, and the Indian Data Science Platform market was the fastest-growing market in the Asia-Pacific region.
Major market players are spending a lot on R&D to increase their Verticals lines, which will help the Data Science Platform market grow even more. Market participants are also taking various strategic initiatives to grow their worldwide footprint, with key market developments such as new Verticals launches, contractual agreements, mergers and acquisitions, increased investments, and collaboration with other organizations. Data Science Platform industry competitors must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.
Manufacturing locally to reduce operating costs is one of the primary business strategies manufacturers adopt in the Data Science Platform industry to benefit clients and expand the market sector. The Data Science Platform industry has provided medicine with some of the most significant benefits in recent years. In the Data Science Platform markets, major players such as Microsoft Corporation (U.S.), IBM Corporation (U.S.), Google Inc. (U.S.), Wolfram (U.S.), and others are working on expanding the market demand by investing in research and development activities.
Google LLC is an American multinational technology company focused on online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, artificial intelligence, and consumer electronics. Due to its market dominance in artificial intelligence, data collection, and technological superiority, it has been called "the world's most powerful company" and one of its most valuable brands. In May 2021, Google changed the goals of Google Vertex AI, Google Cloud's new managed ML platform, to simplify the Deployment and maintenance of AI models for developers. The fact that Google chose to launch Vertex today shows how important the company thinks this new service will be for developers of all kinds. It's an unusual announcement at Google I/O, which usually focuses on mobile and web developers and doesn't usually include much Google Cloud news.
Also, International Business Machines Corporation (IBM), nicknamed Big Blue, is an American multinational technology corporation headquartered in Armonk, New York, with operations in over 175 countries. It focuses on computer hardware, middleware, and software and provides hosting and consulting services in areas ranging from mainframe computing to nanotechnology. IBM is the world's largest industrial research institution, with 19 research institutions in more than a dozen countries, and has held the record for the most annual U.S. patents by an enterprise for 29 consecutive years from 1993 to 2021.
Microsoft Corporation (U.S.)
Sense Inc. (U.S.)
IBM Corporation (U.S.)
Wolfram (U.S.)
Google Inc. (U.S.)
DataRobot Inc. (U.S.)
RapidMiner Inc. (U.S.)
Domino Data Lab (U.S.)
Dataiku (France)
Alteryx Inc. (U.S.)
Continuum Analytics Inc. (U.S.)., among others
September 2021: Optimizely, a provider of digital experience platform solutions, announces the launch of Data Core Services to enhance the Digital Experience Platform (DXP) with deeper analytics and unified data insights across its product suite. With Data Core Services, companies better understand their customers and their overall digital business performance.
Marketing
Sales
Logistics
Human Resources
On-Demand
On-Premises
BFSI
Healthcare
Retail
It
Transportation
North America
US
Canada
Europe
Germany
France
UK
Italy
Spain
Rest of Europe
Asia-Pacific
China
Japan
India
Australia
South Korea
Australia
Rest of Asia-Pacific
Rest of the World
Middle East
Africa
Latin America
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