Data Science Platform Market Research, 2030
Data science framework comprises the software center in which all aspects of data science work take place, including the incorporation and exploration of data from different sources, coding, and models of construction. It also leverages the data, deploys models into development, and through model-powered applications or reports, it serves outcomes. It helps data scientists to uncover actionable insights from data within a single environment, prepare a strategy, and communicate the collected ideas within an organization. Data science includes several work names, ranging from analytics officer, actuary, to research scientist, through numerous industries and organizations. All four phases of the data science production line are assisted by the Data Science platform: data planning, model creation, DevOps, and business delivery. It is focused on open access to data, consistent metadata, good corporate governance, automated machine learning and model building, operationalized model management, and tools that measure and improve its impact on business.
Market Highlights
Global Data Science Platform Market is expected to project a notable CAGR of 29.4% in 2030.
Global Data Science Platform Market to surpass USD 805.7 million by 2030 from USD 36.57 million in 2018 at a CAGR of 29.4% throughout the forecast period. The growing demand for the public cloud, the adoption of artificial intelligence, the exponential growth of applications for the Internet of Things (IoT) and machine learning, the revolution and increase in demand for big data, etc., are the factors that are expected to drive the industry demand for data science platforms. In addition, the relative importance of data collection in most local economies and the need to gain actionable data insights are expected to fuel demand for services and solutions for the data science platforms market. These platforms attract the attention of organizations that aim to increase business performance and decrease human interference. The implementation of such data-driven solutions thus supports the development of the demand for data science platforms.
Global Data Science PlatformMarket: Segments
Sales Business FunctionSegment to grow with the highest CAGR of XX.X% during 2019-30
Global Data Science Platform Market is segmented by Business Function into Logistics, Marketing, Sales, Customer Support, Human Resource and Others. The greater market share in 2018 was accounted for by the Sales segment and is expected to maintain the dominance throughout the forecast period owing to the ability of to organizations prepare data, build models and operationalize analytics. Digitalization and automation are gradually moving towards enterprises, which are growing big data and contributing to complicated business processes. Organizations need innovative technology that helps to gain real-time insights into a large pool of data to cope with these complexities. The data science platform helps them streamline business processes and attract new customers.
Retail and Consumer Goods segment to grow with the highest CAGR of XX.X% during 2019-30
The Global Data Science platform market is segmented by End-User into BFSI, Healthcare and Life Sciences, IT and Telecom, Retail and Consumer Goods, Media and Entertainment, Transportation and Logistics, and Others. The Healthcare and Life science segment is estimated to dominate the market in terms of revenue in 2018 owing to an increase in the need for enhanced data analytical solutions due to the rise of 3D printing, the Internet of things (IoT), and artificial intelligence. The data science platform offers several communities in medical research that can widely exchange, incorporate and interpret historical, patient-level data from phase III clinical trials in academia and industry. Such a rich data collection is part of data science and undoubtedly will help the pharmaceutical research and development segment.
Global Data Science Platform Market: Market Dynamics
Drivers
Growing inclination of enterprises toward data-intensive business strategies
The increasing focus of companies on ease-of-use methods to drive business and the need to obtain in-depth insights from voluminous data to gain a competitive edge are key growth drivers for the industry. Companies are increasingly inclined towards data-intensive business strategies and increasing adoption of advanced technology to generate many opportunities for data science platform vendors. The market for data science platforms is primarily driven by the rapid growth of big data technology, growing demand for technologies to increase operational performance, and increasing acceptance of big data analytics to gain insights into customer purchasing behavior and buying trends.
Rising adoption of advanced technologies
Data science is opening up huge opportunities to learn unnoticed trends of customer buying. These trends allow businesses to understand key insights to help their company run effectively, target potential customers, and deliver better services. In addition, business analytics tools are being embraced by businesses that can deliver effective results from a broad collection of data, which in turn is fueling the growth of the market for data science platforms. Funding and enormous investments by the public and private sectors in the production of big data and related technologies are expected to fuel the growth of the data science platform market.
Restraint
Lack of privacy and security
Lack of technological reliability, stringent government rules and regulations, data protection and privacy concerns and enormous investment requirements are key factors hindering the growth of the data science platform industry. Users of this technology will need to upgrade their platform on a regular basis to make it effective with advanced data resources and technologies, which is a key challenge for market growth. In the data science platform industry, data explosion, lack of domain knowledge and lack of analytical capabilities are few challenges.
Global Data Science Platform Market is segmented based on regional analysis into five major regions. These include North America, Latin America, Europe, APAC and MENA.
Global Data Science Platform Market in Asia Pacific held the largest market share of XX.X% in the year 2018due to large enterprises, technical experts, and growing demand for data science platform in this region. Whereas in the APAC region a huge amount of data is produced by the growing demand for cloud, IoT, and edge solutions, growing the need for advanced data processing technologies. This need for data processing is boosting demand in the APAC region for the data science platform. In addition, major tech companies' investments are also expected to fuel business growth across the region.
Competitive Landscape:
Global Data Science Platform market, which is highly competitive, consists of several major players such as Microsoft Corporation, Google Inc., IBM Corporation holds a substantial market share in the Global Data Science Platform market. Other players analyzed in this report are Alphabet Inc. (Google) (US), Altair Engineering, Inc. (US), Alteryx, Inc. (US), MathWorks (Australia), SAS Institute Inc. (US), RapidMiner, Inc. (US), Cloudera, Inc. (US), Anaconda, Inc. (US), Wolfram (US), Dataiku (US), Civis Analytics (US), H2O.ai. (US), Domino Data Lab, Inc. (US), RStudio, Inc. (US), Rapid Insight (US), DataRobot, Inc. (US), Rexer Analytics (US), SAP (Germany), and Databricks (US).
Recently, various developments have been taking place in the market. For instance, In July 2019, Microsoft released Microsoft Machine Learning Server 9.4. This platform provides Python function libraries and R for ML and data science. It also contains updates for R and Python engines with additional Spark 2.4 and CDH 6.1 support.
Global Data Science PlatformMarket is further segmented by region into:
- North America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – United States and Canada
- Latin America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – Mexico, Argentina, Brazil and Rest of Latin America
- Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – United Kingdom, France, Germany, Italy, Spain, Belgium, Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia, Turkey and Rest of Europe
- APAC Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – India, China, South Korea, Japan, Malaysia, Indonesia, New Zealand, Australia and Rest of APAC
- MENA Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – North Africa, Israel, GCC, South Africa and Rest of MENA
Global Data Science Platform Market: Key Players
- Microsoft Corporation
- Company Overview
- Business Strategy
- Key Product Offerings
- Financial Performance
- Key Performance Indicators
- Risk Analysis
- Recent Development
- Regional Presence
- SWOT Analysis
- IBM Corporation
- SAS Institute, Inc.
- SAP SE
- RapidMiner, Inc.
- Dataiku SAS
- Alteryx, Inc
- Fair Issac Corporation (FICO)
- MathWorks, Inc
- Teradata, Inc.
Global Data Science Platform Market report also contains analysis on:
Global Data Science PlatformMarket Segments:
By Business Function:
- Logistics, Marketing
- Sales
- Customer Support
- Human Resource
- Others
By Deployment Type:
- On-Premise
- On-Demand
By End-User:
- BFSI
- Health and Life Sciences
- IT and Telecom
- Retail and Consumer Goods
- Media and Entertainment
- Transportation and Logistics
- Others
- Data Science PlatformMarketDynamics
- Data Science PlatformMarketSize
- Supply & Demand
- Current Trends/Issues/Challenges
- Competition & Companies Involved in the Market
- Value Chain of the Market
- Market Drivers and Restraints
Frequently Asked Questions (FAQ):
The report provides a global overview of the data science platform market, including segmentation by component (platforms vs services), deployment model (cloud vs onâpremise), endâuser industry (such as BFSI, retail, healthcare, telecom), regional breakdowns, market size, growth drivers, challenges and forecasts.
Major growth drivers include the explosive growth in data generation (from IoT, cloud, edge), increasing demand for advanced analytics and AI/ML workflows, enterprises consolidating dataâengineering + modelâops + businessâintelligence on single stacks, and regulatory/compliance pressures driving adoption of mature platforms
Challenges include the high cost and complexity of deploying endâtoâend data science platforms, talent shortages in data science and MLOps, integration issues with legacy data systems, and variability in regulatory/dataâgovernance regimes across regions that can slow deployment of large platforms.
The report segments the market by component, such as the core platform software and associated services (consulting, integration, support). It also breaks down by deployment model including cloudâbased versus onâpremise (or hybrid) implementations, reflecting enterprise preferences and maturity
Industries such as Banking, Financial Services & Insurance (BFSI) lead the market because of the heavy use of dataâscience platforms for fraud detection, risk modelling, customer analytics. Regions covered include North America, Europe, AsiaâPacific, Latin America and Middle East & Africa. North America remains dominant in value terms, while AsiaâPacific is often cited as the fastestâgrowing region due to rising analytics adoption.
This report is useful for enterprise software vendors, cloud and analytics platform providers, system integrators, dataâplatform service firms, Câlevel decisionâmakers in enterprises (CIO/CTO), investors exploring platformâsoftware opportunities, and strategic planners. It offers insights into segmentation, growth trends, regional opportunity and competitive dynamics
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