Data Science Platform Market Key Players Analysis, Gross Revenue, CAGR of 29.00% by 2030, Size, Application, Gross Margin

A recent study report released by Data Bridge Market research titled "Data Science Platform Market"  (covering USA, Europe, China, Japan, India, South East Asia, and Etc) highlights opportunities, risk analysis, and leveraged with strategic and tactical decision-making support. Global Data Science Platform market report endows with a better solution for refining the business strategies to thrive in this competitive marketplace. This market report deals with the market research of the Data Science Platform industry by considering several parameters that are affecting business growth. By maintaining quality and transparency strictly, research studies are carried out which offer an outstanding market research report niche. The Data Science Platform market research report is wide-ranging and object-oriented, which is framed after the combination of admirable industry experience, talent solutions, industry insight, and the most modern tools and technology. All this helps to enhance the company's growth by subsidizing the risk and improving its performance.

Data Bridge Market Research analyses that the data science platform market which was USD 122.94  billion in 2022, would rocket up to USD 942.76  billion by 2030, and is expected to undergo a CAGR of 29.00% during the forecast period. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

List of the leading companies operating in the Data Science Platform Market includes:

IBM (U.S.)
DataRobot Inc., (U.S.)
apheris AI GmbH (Germany)
The Digital Talent Ecosystem (U.S.)
Databand (Israel)
dotData (U.S.)
Explorium Inc., (U.S.)
Noogata (Israel)
Tecton Inc., (U.S.)
Spell Designs Pty Ltd (U.S.)
Arrikto Inc., (U.S.)
Iterative (U.S.)
Google Inc (U.S.)
Microsoft (U.S.)
SAS Institute Inc., (U.S.)
Amazon Web Services, Inc. (U.S.)
The MathWorks, Inc. (U.S.)
Cloudera Inc., (U.S.)
Teradata (U.S.)
TIBCO Software Inc. (U.S.)
ALTERYX, INC. (U.S.)
RapidMiner (U.S.), Databricks (U.S.)
Snowflake Inc., (U.S.)
ai (U.S.)
Altair Inc., (U.S.)
Anaconda Inc., (U.S.)
SAP SE (U.S.)
Domino Data Lab Inc., (U.S.)
Dataiku (U.S.)

Data science platform Market Dynamics

This section deals with understanding the market drivers, advantages, opportunities, restraints and challenges. All of this is discussed in detail as below:

Drivers

Burgeoning growth of Big Data

The amount of data that enterprises collect is constantly rising due to the growth of social media, IoT, and multimedia, which have generated an overwhelming flow of data in both structured and unstructured forms. For instance, just the past two years have seen the creation of about 90% of the world's data. The growth rate of machine-based and human-generated data is generally 10 times greater than that of traditional corporate data. The growth rate of machine data is exponential and 50 times quicker. The majority of data is consumer driven and oriented. Today's "always-on" consumers produce the majority of data produced worldwide. The enormous growth in data presents chances for businesses to learn new things, which has led to a rise in the demand for fresh approaches. This in turn significantly influences the market for data science platforms.

Numerous Benefits offered by Data Science Platform

Data science platforms are currently being used more and more due to the various benefits offered by these platforms. The software offers open source tools significant flexibility and scalability of computing resources. Additionally, it is simple to align with different data architectures. In addition, the platform supports version control, enabling the data science team to collaborate on projects without losing recently completed work. Consequently, such advantages significantly aid market expansion over the forecast period.

Furthermore, the factors such as surge in reliance on machine learning coupled with the surge in inclination of enterprises toward data-intensive business strategies will accelerate the overall market expansion during the forecast period. Additionally surge in adoption of cloud-based solutions and services is anticipated to drive the growth rate of the data science platform market. The increase in the demand for analytical tools will further positively impact the market's growth rate during the forecast period.

Opportunities

Rising Investment And Advancements In Technologies

The rising investment in research and development is estimated to generate lucrative opportunities for the market, which will further expand the data science platform market's growth rate in the future. Moreover, the advancements in technologies such as artificial intelligence (AI), machine learning (ML), and internet of things (IoT) further offer numerous growth opportunities within the market.

Restraints/Challenges

Uncertainty over the Business Issues

Businesses should research the issues they intend to use the data science platform for. Prior to having a good understanding of the business problem to be solved, choosing the mechanical technique of finding datasets and executing data analysis turns out to be less productive. Businesses using the data science platform to make wise decisions is extremely unhelpful. Even with a defined aim in mind, efforts are ineffective if firms' expectations from the installation of the data science platform are not in line with the objectives. This factor is projected to create various growth hindrances over the forecast period.

Lack of Technical Expertise

Nowadays, businesses use sophisticated analytics methods including streaming analytics, machine learning, and predictive analytics. These methods are difficult and call for in-depth analytical expertise. Technical expertise as well as analytical and critical thinking abilities are necessary to develop an ML model. Many end users lack the personnel with the necessary abilities and information. Most of an organization's effort is spent collecting and correcting data generated from numerous sources. Not every employee that handles data must be knowledgeable in data science. To create a culture of data-driven decision-making, business expertise and the accompanying training are also necessary. Therefore, the dearth of trained staff or technical expertise is therefore estimated to be significant challenge for the data science platform market over the forecast period.

This data science platform market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the data science platform market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

To Gain More Insights into the Market Analysis, Browse Summary of the Data Science Platform Report@ https://www.databridgemarketresearch.com/reports/global-data-science-platform-market

Global Data Science Platform Segmentations:

Component Type

Platform
Services

Function Division

Marketing
Sales
Logistics
Finance and Accounting
Customer Support
Business Operations
Others

Deployment Model

On-Premises
Cloud based

Organization Size

Small and Medium-sized Enterprises (SMEs)
Large Enterprises

End User Application

Banking, Financial Services, and Insurance (BFSI)
Telecom and IT
Retail and E-commerce
Healthcare and Life sciences
Manufacturing
Energy and Utilities
Media and Entertainment
Transportation and Logistics
Government
Others

Table of Content: Global Data Science Platform Market

1 Introduction

2 Market Segmentation

3 Executive Summary

4 Premium Insights

5 Market Overview

6 Global Data Science Platform Market, By Deployment Type

7 Global Data Science Platform Market, By Enterprise Size

8 Global Data Science Platform Market, By Sales Channel

9 Global Data Science Platform Market, By Application

10 Global Data Science Platform Market, By Region

11 Global Data Science Platform Market, Company Landscape

12 Swot Analysis

13 Company Profile

14 Questionnaire

15 Related Reports

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This release was published on openPR.