| Status : Published | Published On : Jan, 2021 | Report Code : VRICT5029 | Industry : ICT & Media | Available Format :
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Page : 142 |
Global Data Science Platform Market – Analysis and Forecast (2023-2030)
Industry Insights by Deployment Type (On-Premise, On-Demand), by Business Function (Marketing, Logistics, Customer Support, Human Resource, Sales, Others), by Industry Vertical (IT & Telecom, Healthcare & Life Sciences, Retail & Consumer Goods, Transportation & Logistics, Media & Entertainment, Banking, Financial Services, and Insurance (BFSI), Others)
Industry Overview
The global data science platform market is projected to reach USD 292.9 billion by 2030, registering a CAGR of 41.1% during the forecast period. increasing awareness regarding the benefits of these technologies among different enterprises or organizations and ease of use methods, propelling the growth of the market.
Market Segmentation
Insight by Deployment Type
Based on deployment type, the global data science platform market is categorized into on-premise and on demand, wherein on-premise category accounted for larger share in 2020.
Insight by Business Function
On the basis of industry vertical, the global data science platform market can be segmented into IT and telecom, healthcare and life sciences, retail and consumer goods, transportation and logistics, media and entertainment, BFSI, and others. Of all, the BFSI sector is expected to continue holding the largest share during the forecast period. BFSI sector utilizes these platforms for marketing analytics, collection analytics, risk assessment and reduction, fraud analytics, operation analytics, regulatory compliance, credit policy adherence and collection analytics. All these use cases are key to the efficient operations of BFSI sector, therefore, leading to the largest adoption of the products and services offered by the data science platform industry in BFSI sector.
Insight by Industry Verticals
On the basis of industry vertical, the global data science platform market can be segmented into IT and telecom, healthcare and life sciences, retail and consumer goods, transportation and logistics, media and entertainment, BFSI, and others. Of all, the BFSI sector is expected to continue holding the largest share during the forecast period. BFSI sector utilizes these platforms for marketing analytics, collection analytics, risk assessment and reduction, fraud analytics, operation analytics, regulatory compliance, credit policy adherence and collection analytics. All these use cases are key to the efficient operations of BFSI sector, therefore, leading to the largest adoption of the products and services offered by the data science platform industry in BFSI sector.
Data Science Platform Market Report Coverage
|
Report Metric |
Details |
|
Historical Period |
2018–2022 |
|
Base Year Considered |
2022 |
|
Forecast Period |
By 2030 |
|
Market Size in 2022 |
$X.XX Billion |
|
Revenue Forecast in 2030 |
$26.8 Billion |
|
Growth Rate |
CAGR 4.2% |
|
Segments Covered in the Report |
By Product Type, By Wound Type, By Application, and By End-User |
|
Report Scope |
Market Trends, Drivers, and Restraints; Revenue Estimation and Forecast; Segmentation Analysis; Impact of COVID-19; Companies’ Strategic Developments; Market Share Analysis of Key Players; Company Profiling |
|
Regions Covered in the Report |
North America, Europe, Asia-Pacific, Middle East, and Rest of the World |
Industry Dynamics
Growth Drivers
The global data science platform market has been driven by several key factors, predominantly advancements in big data technologies, increasing awareness regarding the benefits of these technologies among different enterprises or organizations, and ease of use methods to drive businesses. Also, the increased demand from the BFSI sector for the platform owing to the need for simplifying complexities of operations in the banking and finance sector significantly drives the global market. Increasing numbers of fraud in the banking sector related to accounting, credit cards, insurance, and others lead to the significant growth of the market.
Increasing data volume: The proliferation of data from various sources, such as social media, IoT devices, and sensors, has led to an exponential growth in data volume. Data science platforms provide the tools and capabilities to manage and analyze large datasets, enabling organizations to extract valuable insights and make data-driven decisions.
Increasing focus on data-driven decision-making: Organizations across industries are recognizing the value of data-driven decision-making. Data science platforms empower decision-makers by providing insights derived from data analysis, enabling them to make informed choices, optimize operations, and identify new business opportunities.
Growing need for actionable insights: Organizations are recognizing the importance of leveraging data to gain actionable insights and gain a competitive advantage. Data science platforms offer advanced analytics and machine learning capabilities that enable businesses to uncover hidden patterns, trends, and correlations in their data, leading to better decision-making and improved operational efficiency.
Advancements in artificial intelligence and machine learning: The rapid advancements in artificial intelligence (AI) and machine learning (ML) technologies have driven the growth of the data science platform market. These platforms incorporate AI and ML capabilities, allowing data scientists and analysts to develop sophisticated models and algorithms for tasks like natural language processing, image recognition, and anomaly detection.
Integration with big data technologies: Data science platforms often integrate with big data technologies such as Apache Hadoop and Spark, allowing organizations to process and analyze vast amounts of structured and unstructured data. This integration enables data scientists to work with diverse data sources and perform advanced analytics on large-scale datasets.
Growing adoption of cloud-based platforms: Cloud-based data science platforms have gained significant traction due to their flexibility, scalability, and cost-effectiveness. These platforms eliminate the need for on-premises infrastructure and provide easy access to compute resources and data storage, making them more accessible to organizations of all sizes.
Challenges
Key factors hindering the growth of the data science platform market are lack of reliability on the technology, stringent government rules and regulations, data security and privacy issues and huge investment requirement. Also, the users of this technology require to regularly update their platform to make it reliable with advanced data tools and technologies, which is a key challenge for the growth of the industry.
Geographic Overview
North America has been one of the largest consumers of data science platform during the forecast period. The supportive government initiatives developed banking and financial sector and high awareness regarding the benefits of the technology lead to the largest share of the region, globally. U.S. is the larger market in the North American market, due to the larger presence of banking and finance organizations and developed IT infrastructure across different industry verticals.
Global Data Science Platform Market, By Region
Asia-Pacific is observed to witness the fastest growth in the data science platform market during the forecast period. As the region offers immense opportunities for banking and finance sectors and large customer base. Also, the developing infrastructures for IT and telecom, healthcare and life sciences, and transportation and logistics require the need for efficient analysis of large volume data, thus fueling the growth of the industry in the region.
Competitive Insight
Market players in the global data science platform industry are integrating AI to advance its technology platform, thus gaining a competitive advantage over other players. In March 2018, IBM Corporation unveiled a new data science and machine learning platform and an elite consulting team to help enterprises accelerate their AI roadmaps. The new Cloud Private for Data of IBM is an integrated data science, data engineering, and app-building platform.
Some of the key players operating in the global data science platform market are Alphabet, Inc., Wolfram, Microsoft Corporation, IBM Corporation, RapidMiner Inc., Domino Data Lab, Sense Inc., DataRobot Inc., Alteryx, Inc., and Dataiku.
The Data Science Platform Market report offers a comprehensive market segmentation analysis along with an estimation for the forecast period 2023–2030.
Segments Covered in the Report
- By Deployment Type
- On-Premise
- On-Demand
- By Business Function Type
- Marketing
- Logistics
- Customer Support
- Human Resource
- Sales
- Others
- By Industry Vertical
- IT and Telecom
- Healthcare and Life Sciences
- Retail and Consumer Goods
- Transportation and Logistics
- Media and Entertainment
- BFSI
- Others
Region Covered in the Report
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Russia
- Rest of Europe
- Asia-Pacific (APAC)
- China
- Japan
- India
- South Korea
- Rest of Asia-Pacific
- Rest of the World (RoW)
- Brazil
- Saudi Arabia
- South Africa
- U.A.E.
- Other Countries
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Data Science Platform Market