サンプル依頼リスト カート
  • English
  • Korean
  • Traditional Chinese
  • Simplified Chinese
デフォルト表紙
市場調査レポート
商品コード
1378922

データサイエンスプラットフォーム市場レポート：コンポーネント、用途、業界別、地域別、2023-2028年

Data Science Platform Market Report by Component, Application, Vertical, and Region 2023-2028
出版日: | 発行: IMARC | ページ情報: 英文 145 Pages | 納期: 2～3営業日

● お客様のご希望に応じて、既存データの加工や未掲載情報（例：国別セグメント）の追加などの対応が可能です。　 詳細はお問い合わせください。

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=156.76円
データサイエンスプラットフォーム市場レポート：コンポーネント、用途、業界別、地域別、2023-2028年
出版日: 2023年11月02日
発行: IMARC
ページ情報: 英文 145 Pages
納期: 2～3営業日
  • 全表示
  • 概要
  • 図表
  • 目次
概要

概要

世界のデータサイエンスプラットフォーム市場規模は2022年に89億米ドルに達しました。今後、IMARC Groupは、同市場が2022年から2028年の間に32.7%の成長率（CAGR）を示し、2028年までに485億米ドルに達すると予測しています。ヘルスケア業界におけるデータサイエンスプラットフォームの利用の高まり、様々な企業組織におけるクラウドベースのプログラムに対する需要の高まり、データサイエンスプラットフォームにおける先端技術の統合の高まりは、市場を牽引する主要な要因のいくつかを表しています。

データサイエンスプラットフォームは、データサイエンス・プロセスの様々な側面に必要なツール、技術、リソースを提供する包括的なソフトウェアおよびハードウェアのインフラストラクチャです。データサイエンスは、データの収集、クリーニング、分析、解釈を含む学際的な分野で、価値ある洞察を引き出し、データ主導の意思決定を行う。これらのプラットフォームには、データ抽出、変換、ローディング（ETL）のためのツールや、データベース、データウェアハウス、API、その他のデータソースへのコネクタが含まれます。また、予測モデルや記述モデルを構築するための機械学習アルゴリズムやモデリングツールも幅広く提供されています。

現在、膨大な量の構造化データおよび非構造化データを効率的に分析、監督、統合する能力により、ヘルスケア分野でのデータサイエンスプラットフォームの採用が増加しており、これが主に市場成長の原動力となっています。さらに、多様な世界事業体においてクラウドベースのソリューションへの選好が高まっていることも、良好な市場環境を促進しています。さらに、費用対効果が高く、効率的で、強化された意思決定ツールに対する需要が世界規模で高まっています。この需要の急増は、企業の分析と生産性を高めるデータサイエンスプラットフォームの利用拡大と相まって、市場の成長を促進しています。さらに、人工知能（AI）、モノのインターネット（IoT）、機械学習（ML）のデータサイエンスプラットフォームへの統合は、業界利害関係者に有利な成長機会をもたらしています。さらに、ビジネス向けの予測モデルの構築、管理、最適化のためのまとまった統合アプローチを提供するデータサイエンスプラットフォームに対する意欲の高まりが、市場に好影響を及ぼしています。さらに、ビッグデータ技術の進化に後押しされたデータサイエンスプラットフォームに対する需要の高まりが、市場の拡大に寄与しています。さらに、銀行サービスの利用拡大によるBFSI分野でのデータサイエンスプラットフォームに対するニーズの高まりが、市場の成長をさらに強めています。

本レポートで扱う主な質問

  • 世界のデータサイエンスプラットフォーム市場の規模は？
  • 2023年から2028年にかけてのデータサイエンスプラットフォームの世界市場成長率予測は？
  • データサイエンスプラットフォームの世界市場を牽引する主要因は何か
  • COVID-19がデータサイエンスプラットフォームの世界市場に与えた影響は？
  • データサイエンスプラットフォームの世界市場におけるコンポーネント別の区分は？
  • データサイエンスプラットフォームの世界市場の用途別区分は？
  • データサイエンスプラットフォームの世界市場の業界別区分は？
  • データサイエンスプラットフォームの世界市場における主要地域は？
  • データサイエンスプラットフォームの世界市場における主要プレイヤー/企業は？

データサイエンスプラットフォーム市場の動向と促進要因：

  • ヘルスケア業界におけるデータサイエンスプラットフォーム活用の高まり
  • ヘルスケアでは、構造化されたデータ（患者記録）だけでなく、医療画像や臨床記録などの非構造化データも含め、膨大な量のデータが生成されます。データサイエンスプラットフォームは、ヘルスケアプロバイダーがこの豊富な情報を効果的に分析、管理、吸収することを可能にします。例えば、データ分析を利用して、患者集団の動向やパターン、潜在的な健康リスクを特定することができます。さらに、これらのプラットフォームはヘルスケア専門家に予測分析を活用する力を与えます。疾病の発生を予測し、より注意が必要と思われるハイリスク患者を特定し、さらには患者の転帰を予測することができます。この予測能力により、患者のケアと資源配分が強化されます。さらに、製薬やバイオテクノロジーの分野では、データサイエンスプラットフォームが創薬や薬剤開発に役立っています。研究者は遺伝子データ、臨床試験結果、薬物相互作用を分析し、新たな治療法の市場投入プロセスを加速することができます。
  • さまざまな企業で高まるクラウドベースのプログラム需要
  • クラウドベースのプラットフォームは、大規模なデータセットや計算需要を処理するスケーラビリティを提供します。企業は必要に応じてリソースを増減できるため、データサイエンス・プロジェクトを柔軟に管理できます。また、これらのソリューションでは、ハードウェアやインフラへの先行投資が少なくて済むことが多いです。この費用対効果は、あらゆる規模の組織、特に新興企業や中小企業にとって魅力的です。さらに、クラウドベースのプラットフォームはリモートアクセスを可能にし、地理的に分散したチーム間のコラボレーションを促進します。今日の世界化したビジネス環境では、このアクセシビリティは極めて重要です。さらに、クラウド・プロバイダーがソフトウェアのアップデートやインフラのメンテナンスを行うため、社内のITチームの負担が軽減され、企業は常に最新の機能やセキュリティ・パッチにアクセスできます。
  • データサイエンスプラットフォームにおける先端技術の統合の高まり
  • AIとMLアルゴリズムは、データサイエンスプラットフォームに不可欠な要素になりつつあります。これらは自動化、予測モデリング、自然言語処理、異常検知を可能にします。これらの高度な機能は、複雑なデータセットから価値ある洞察を引き出すために不可欠です。さらに、様々な業界におけるIoTデバイスの普及に伴い、データサイエンスプラットフォームは、これらのデバイスから生成される大量のデータの流入を処理するために適応しつつあります。データサイエンスプラットフォームは、センサー、デバイス、機械からのデータを分析し、リアルタイムの洞察を提供し、意思決定を改善することができます。また、先進的なテクノロジーにより、データサイエンスプラットフォームはより洗練されたデータ可視化技術を提供できるようになっています。これにより、利害関係者に洞察を効果的に伝える能力が強化されます。

本レポートで扱う主な質問

  • 世界のデータサイエンスプラットフォーム市場の規模は？
  • 2023年～2028年のデータサイエンスプラットフォームの世界市場成長率は？
  • データサイエンスプラットフォームの世界市場を牽引する主要因は何か
  • COVID-19がデータサイエンスプラットフォームの世界市場に与えた影響は？
  • データサイエンスプラットフォームの世界市場におけるコンポーネント別の区分は？
  • データサイエンスプラットフォームの世界市場の用途別区分は？
  • データサイエンスプラットフォームの世界市場の業界別区分は？
  • データサイエンスプラットフォームの世界市場における主要地域は？
  • データサイエンスプラットフォームの世界市場における主要プレイヤー/企業は？

目次

第1章 序文

第2章 調査範囲と調査手法

  • 調査目的
  • 利害関係者
  • データソース
    • 一次情報
    • 二次情報
  • 市場推定
    • ボトムアップアプローチ
    • トップダウンアプローチ
  • 調査手法

第3章 エグゼクティブサマリー

第4章 イントロダクション

  • 概要
  • 主要業界動向

第5章 世界のデータサイエンスプラットフォーム市場

  • 市場概要
  • 市場実績
  • COVID-19の影響
  • 市場予測

第6章 市場内訳：コンポーネント別

  • ソフトウェア
    • 市場動向
    • 市場予測
  • サービス
    • 市場動向
    • 市場予測

第7章 市場内訳：用途別

  • マーケティング・販売
    • 市場動向
    • 市場予測
  • ロジスティクス
    • 市場動向
    • 市場予測
  • 財務・会計
    • 市場動向
    • 市場予測
  • カスタマーサポート
    • 市場動向
    • 市場予測
  • その他
    • 市場動向
    • 市場予測

第8章 市場内訳：業界別

  • IT・通信
    • 市場動向
    • 市場予測
  • ヘルスケア
    • 市場動向
    • 市場予測
  • BFSI
    • 市場動向
    • 市場予測
  • 製造業
    • 市場動向
    • 市場予測
  • 小売とeコマース
    • 市場動向
    • 市場予測
  • その他
    • 市場動向
    • 市場予測

第9章 市場内訳：地域別

  • 北米
    • 米国
      • 市場動向
      • 市場予測
    • カナダ
      • 市場動向
      • 市場予測
  • アジア太平洋
    • 中国
      • 市場動向
      • 市場予測
    • 日本
      • 市場動向
      • 市場予測
    • インド
      • 市場動向
      • 市場予測
    • 韓国
      • 市場動向
      • 市場予測
    • オーストラリア
      • 市場動向
      • 市場予測
    • インドネシア
      • 市場動向
      • 市場予測
    • その他
      • 市場動向
      • 市場予測
  • 欧州
    • ドイツ
      • 市場動向
      • 市場予測
    • フランス
      • 市場動向
      • 市場予測
    • 英国
      • 市場動向
      • 市場予測
    • イタリア
      • 市場動向
      • 市場予測
    • スペイン
      • 市場動向
      • 市場予測
    • ロシア
      • 市場動向
      • 市場予測
    • その他
      • 市場動向
      • 市場予測
  • ラテンアメリカ
    • ブラジル
      • 市場動向
      • 市場予測
    • メキシコ
      • 市場動向
      • 市場予測
    • その他
      • 市場動向
      • 市場予測
  • 中東・アフリカ地域
    • 市場動向
    • 市場内訳：国別
    • 市場予測

第10章 SWOT分析

  • 概要
  • 強み
  • 弱み
  • 機会
  • 脅威

第11章 バリューチェーン分析

第12章 ポーターのファイブフォース分析

  • 概要
  • 買い手の交渉力
  • 供給企業の交渉力
  • 競合の程度
  • 新規参入業者の脅威
  • 代替品の脅威

第13章 価格分析

第14章 競合情勢

  • 市場構造
  • 主要企業
  • 主要企業のプロファイル
    • Alteryx Inc.
    • Cloudera Inc.
    • Dataiku Inc.
    • Google LLC（Alphabet Inc.）
    • H2O.ai Inc.
    • International Business Machines Corporation
    • Microsoft Corporation
    • RapidMiner Inc.
    • SAP SE
    • SAS Institute Inc.
    • The MathWorks Inc.
    • TIBCO Software Inc.
図表

List of Figures

  • Figure 1: Global: Data Science Platform Market: Major Drivers and Challenges
  • Figure 2: Global: Data Science Platform Market: Sales Value (in Billion US$), 2017-2022
  • Figure 3: Global: Data Science Platform Market Forecast: Sales Value (in Billion US$), 2023-2028
  • Figure 4: Global: Data Science Platform Market: Breakup by Component (in %), 2022
  • Figure 5: Global: Data Science Platform Market: Breakup by Application (in %), 2022
  • Figure 6: Global: Data Science Platform Market: Breakup by Vertical (in %), 2022
  • Figure 7: Global: Data Science Platform Market: Breakup by Region (in %), 2022
  • Figure 8: Global: Data Science Platform (Software) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 9: Global: Data Science Platform (Software) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 10: Global: Data Science Platform (Services) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 11: Global: Data Science Platform (Services) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 12: Global: Data Science Platform (Marketing and Sales) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 13: Global: Data Science Platform (Marketing and Sales) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 14: Global: Data Science Platform (Logistics) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 15: Global: Data Science Platform (Logistics) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 16: Global: Data Science Platform (Finance and Accounting) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 17: Global: Data Science Platform (Finance and Accounting) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 18: Global: Data Science Platform (Customer Support) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 19: Global: Data Science Platform (Customer Support) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 20: Global: Data Science Platform (Other Applications) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 21: Global: Data Science Platform (Other Applications) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 22: Global: Data Science Platform (IT and Telecommunication) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 23: Global: Data Science Platform (IT and Telecommunication) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 24: Global: Data Science Platform (Healthcare) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 25: Global: Data Science Platform (Healthcare) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 26: Global: Data Science Platform (BFSI) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 27: Global: Data Science Platform (BFSI) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 28: Global: Data Science Platform (Manufacturing) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 29: Global: Data Science Platform (Manufacturing) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 30: Global: Data Science Platform (Retail and E-commerce) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 31: Global: Data Science Platform (Retail and E-commerce) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 32: Global: Data Science Platform (Other Verticals) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 33: Global: Data Science Platform (Other Verticals) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 34: North America: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 35: North America: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 36: United States: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 37: United States: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 38: Canada: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 39: Canada: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 40: Asia-Pacific: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 41: Asia-Pacific: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 42: China: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 43: China: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 44: Japan: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 45: Japan: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 46: India: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 47: India: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 48: South Korea: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 49: South Korea: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 50: Australia: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 51: Australia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 52: Indonesia: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 53: Indonesia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 54: Others: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 55: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 56: Europe: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 57: Europe: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 58: Germany: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 59: Germany: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 60: France: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 61: France: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 62: United Kingdom: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 63: United Kingdom: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 64: Italy: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 65: Italy: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 66: Spain: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 67: Spain: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 68: Russia: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 69: Russia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 70: Others: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 71: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 72: Latin America: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 73: Latin America: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 74: Brazil: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 75: Brazil: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 76: Mexico: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 77: Mexico: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 78: Others: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 79: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 80: Middle East and Africa: Data Science Platform Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 81: Middle East and Africa: Data Science Platform Market: Breakup by Country (in %), 2022
  • Figure 82: Middle East and Africa: Data Science Platform Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 83: Global: Data Science Platform Industry: SWOT Analysis
  • Figure 84: Global: Data Science Platform Industry: Value Chain Analysis
  • Figure 85: Global: Data Science Platform Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: Data Science Platform Market: Key Industry Highlights, 2022 and 2028
  • Table 2: Global: Data Science Platform Market Forecast: Breakup by Component (in Million US$), 2023-2028
  • Table 3: Global: Data Science Platform Market Forecast: Breakup by Application (in Million US$), 2023-2028
  • Table 4: Global: Data Science Platform Market Forecast: Breakup by Vertical (in Million US$), 2023-2028
  • Table 5: Global: Data Science Platform Market Forecast: Breakup by Region (in Million US$), 2023-2028
  • Table 6: Global: Data Science Platform Market: Competitive Structure
  • Table 7: Global: Data Science Platform Market: Key Players
目次
Product Code: SR112023A3601

Abstract

The global data science platform market size reached US$ 8.9 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 48.5 Billion by 2028, exhibiting a growth rate (CAGR) of 32.7% during 2022-2028. The rising utilization of data science platforms in the healthcare industry, the growing demand for cloud-based programs in various business organizations, and the rising integration of advanced technologies in data science platforms represent some of the key factors driving the market.

A data science platform is a comprehensive software and hardware infrastructure that provides the tools, technologies, and resources necessary for various aspects of the data science process. Data science is a multidisciplinary field that involves collecting, cleaning, analyzing, and interpreting data to extract valuable insights and make data-driven decisions. These platforms include tools for data extraction, transformation, and loading (ETL), as well as connectors to databases, data warehouses, APIs, and other data sources. They also offer a wide range of machine learning algorithms and modeling tools for building predictive and descriptive models.

Currently, the increased adoption of data science platforms within the healthcare sector, owing to their ability to efficiently analyze, oversee, and integrate vast volumes of structured and unstructured data is primarily driving the market growth. Furthermore, the increasing preference for cloud-based solutions across diverse global business entities is fostering a favorable market landscape. Additionally, there is a growing demand for cost-effective, efficient, and enhanced decision-making tools on a global scale. This surge in demand, coupled with the expanding utilization of data science platforms, which enhance enterprise analysis and productivity, is propelling market growth. Moreover, the integration of artificial intelligence (AI), the internet of things (IoT), and machine learning (ML) into data science platforms is presenting lucrative growth opportunities for industry stakeholders. Furthermore, the increasing appetite for data science platforms, which offer a cohesive and integrated approach to constructing, managing, and optimizing predictive models for businesses, is exerting a positive influence on the market. Additionally, the escalating demand for data science platforms, driven by the evolution of big data technologies, is contributing to market expansion. Furthermore, the heightened need for data science platforms within the BFSI sector due to the growing utilization of banking services is further strengthening the market growth.

Key Questions Answered in This Report

  • 1. How big is the global data science platform market?
  • 2. What is the expected growth rate of the global data science platform market during 2023-2028?
  • 3. What are the key factors driving the global data science platform market?
  • 4. What has been the impact of COVID-19 on the global data science platform market?
  • 5. What is the breakup of the global data science platform market based on the component?
  • 6. What is the breakup of the global data science platform market based on the application?
  • 7. What is the breakup of the global data science platform market based on the vertical?
  • 8. What are the key regions in the global data science platform market?
  • 9. Who are the key players/companies in the global data science platform market?

Data Science Platform Market Trends/Drivers:

  • Rising utilization of data science platforms in the healthcare industry
  • Healthcare generates an enormous amount of data, both structured (patient records) and unstructured such as medical images and clinical notes. Data science platforms enable healthcare providers to effectively analyze, manage, and assimilate this wealth of information. For instance, they can use data analytics to identify trends, patterns, and potential health risks among patient populations. Besides, these platforms empower healthcare professionals to leverage predictive analytics. They can forecast disease outbreaks, identify high-risk patients who may require more attention, and even predict patient outcomes. This predictive capability enhances patient care and resource allocation. Moreover, in the pharmaceutical and biotechnology sectors, data science platforms are instrumental in drug discovery and development. Researchers can analyze genetic data, clinical trial results, and drug interactions to accelerate the process of bringing new treatments to market.
  • Growing demand for cloud-based programs in various business organizations
  • Cloud-based platforms offer scalability to handle large datasets and computational demands. Businesses can scale their resources up or down as needed, providing flexibility in managing their data science projects. Besides, these solutions often require lower upfront investment in hardware and infrastructure. This cost-effectiveness appeals to organizations of all sizes, especially startups and small businesses. Moreover, cloud-based platforms enable remote access, facilitating collaboration among geographically dispersed teams. This accessibility is crucial in today's globalized business environment. Additionally, cloud providers handle software updates and infrastructure maintenance, reducing the burden on in-house IT teams and ensuring that organizations always have access to the latest features and security patches.
  • Rising integration of advanced technologies in data science platforms
  • AI and ML algorithms are becoming integral parts of data science platforms. They enable automation, predictive modeling, natural language processing, and anomaly detection. These advanced capabilities are essential for extracting valuable insights from complex datasets. Moreover, with the proliferation of IoT devices in various industries, data science platforms are adapting to handle the massive influx of data generated by these devices. They can analyze data from sensors, devices, and machines to provide real-time insights and improve decision-making. Besides, advanced technologies enable data science platforms to offer more sophisticated data visualization techniques. This enhances the ability to convey insights to stakeholders effectively.

Data Science Platform Industry Segmentation:

  • IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global, regional and country levels from 2023-2028. Our report has categorized the market based on component, application and vertical.

Breakup by Component:

  • Software
  • Services
  • Software represents the most popular component
  • The report has provided a detailed breakup and analysis of the market based on the component. This includes software and services. According to the report, software represented the largest segment.
  • Data science software offers a wide range of tools and capabilities for data collection, cleaning, analysis, modeling, and visualization. It provides data scientists with the flexibility to perform a multitude of tasks within a single platform. Moreover, it is readily available and accessible to organizations of all sizes. Many software solutions are user-friendly, making them accessible to both data science experts and those with less technical expertise. Besides, software solutions can be scaled up or down to accommodate different data volumes and complexities. This scalability is crucial in handling the ever-increasing amount of data generated by organizations.

Breakup by Application:

  • Marketing and Sales
  • Logistics
  • Finance and Accounting
  • Customer Support
  • Others
  • Marketing and sales hold the largest market share
  • A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes marketing and sales, logistics, finance and accounting, customer support, and others. According to the report, marketing and sales represented the largest segment.
  • Marketing and sales are inherently data-intensive fields. They heavily rely on data to make informed decisions about product development, pricing strategies, customer segmentation, and sales forecasting. Data science platforms provide the tools and capabilities to process and analyze vast datasets, enabling more accurate and data-driven decision-making. Besides, understanding customer behavior, preferences, and needs is critical for effective marketing and sales strategies. Data science platforms help organizations gather, analyze, and extract actionable insights from customer data. This allows businesses to tailor their marketing campaigns and sales efforts to target specific customer segments more effectively. Moreover, these platforms assist in optimizing marketing campaigns by analyzing campaign performance metrics and identifying which strategies are most effective. This allows marketers to allocate resources to the most successful campaigns and refine their approaches in real-time.

Breakup by Vertical:

  • IT and Telecommunication
  • Healthcare
  • BFSI
  • Manufacturing
  • Retail and E-Commerce
  • Others
  • BFSI accounts for the majority of market share
  • A detailed breakup and analysis of the market based on the vertical has also been provided in the report. This includes IT and telecommunication, healthcare, BFSI, manufacturing, retail and e-commerce, and others. According to the report, BFSI represented the largest segment.
  • The BFSI industry deals with vast volumes of data, including customer transactions, financial records, market data, and risk assessments. Data science platforms are essential for processing and analyzing this extensive data to extract valuable insights, detect fraudulent activities, and make informed decisions. Besides, risk assessment is a critical aspect of the BFSI sector. Data science platforms equipped with machine learning and predictive analytics help banks and financial institutions assess and mitigate risks effectively. These platforms can identify potential credit defaults, market fluctuations, and fraudulent transactions, which is crucial for maintaining financial stability.

Breakup by Region:

  • North America
  • United States
  • Canada
  • Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
  • Latin America
  • Brazil
  • Mexico
  • Others
  • Middle East and Africa
  • North America leads the market, accounting for the majority of the data science platform market share
  • The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America was the largest market.
  • North America, particularly the United States, is home to many technology hubs such as Silicon Valley, which is known for innovation and technological advancements. This region fosters a fertile ground for the development and adoption of cutting-edge data science technologies and platforms. Moreover, the region hosts a vast number of large enterprises, including Fortune 500 companies, across various industries. These enterprises have substantial budgets and resources to invest in data science platforms to gain a competitive edge, improve operational efficiency, and drive innovation. Besides, North America leads in research and development activities related to data science and artificial intelligence (AI). Leading universities, research institutions, and tech companies in the region continually push the boundaries of data science capabilities, leading to the development of state-of-the-art platforms and tools.

Competitive Landscape:

  • The competitive landscape of the market is characterized by the presence of multiple players that include established brands, emerging startups, and specialty manufacturers. Presently, leading companies are investing in research and development to enhance their data science platforms. They are introducing new features, tools, and capabilities to stay ahead of evolving industry trends and customer demands. This includes the integration of artificial intelligence (AI), machine learning (ML), and automation to improve data analytics and predictive modeling. Besides, many key players are expanding their cloud-based data science platform offerings. Cloud platforms provide scalability, flexibility, and accessibility, which are highly valued by businesses. This expansion enables organizations to harness the power of data science without significant infrastructure investments. Moreover, they are acquiring innovative startups and smaller companies in the data science and analytics space. These acquisitions enable them to quickly gain access to cutting-edge technologies, talent, and customer bases.

The market research report has provided a comprehensive analysis of the competitive landscape. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

  • Alteryx Inc.
  • Cloudera Inc.
  • Dataiku Inc.
  • Google LLC (Alphabet Inc.)
  • H2O.ai Inc.
  • International Business Machines Corporation
  • Microsoft Corporation
  • RapidMiner Inc.
  • SAP SE
  • SAS Institute Inc.
  • The MathWorks Inc.
  • TIBCO Software Inc.
  • (Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Recent Developments:

  • In November 2022, Alteryx Inc., launched innovations in analytics and data science automation, analytics in the cloud, machine learning (ML), and artificial intelligence (AI) during the company's Virtual Global Inspire conference. The new designer interface will be powered by the Alteryx Analytics Cloud platform, providing all cloud users access to the browser-based no-code analytics tool, with in-database pushdown processing for cloud data warehouses.
  • In September 2021, Microsoft updates Microsoft Machine Learning Studio which adds a new PyTorch extension library for agile deep learning experimentation.
  • In September 2021, MathWorks updated The MATLAB and Simulink product families. They included new and updated features and functions major improvements, code refactoring and block editing, and the ability to run Python commands and scripts from MATLAB.

Key Questions Answered in This Report

  • 1. How big is the global data science platform market?
  • 2. What is the expected growth rate of the global data science platform market during 2023-2028?
  • 3. What are the key factors driving the global data science platform market?
  • 4. What has been the impact of COVID-19 on the global data science platform market?
  • 5. What is the breakup of the global data science platform market based on the component?
  • 6. What is the breakup of the global data science platform market based on the application?
  • 7. What is the breakup of the global data science platform market based on the vertical?
  • 8. What are the key regions in the global data science platform market?
  • 9. Who are the key players/companies in the global data science platform market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Data Science Platform Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Component

  • 6.1 Software
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Services
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast

7 Market Breakup by Application

  • 7.1 Marketing and Sales
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Logistics
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast
  • 7.3 Finance and Accounting
    • 7.3.1 Market Trends
    • 7.3.2 Market Forecast
  • 7.4 Customer Support
    • 7.4.1 Market Trends
    • 7.4.2 Market Forecast
  • 7.5 Others
    • 7.5.1 Market Trends
    • 7.5.2 Market Forecast

8 Market Breakup by Vertical

  • 8.1 IT and Telecommunication
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Healthcare
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast
  • 8.3 BFSI
    • 8.3.1 Market Trends
    • 8.3.2 Market Forecast
  • 8.4 Manufacturing
    • 8.4.1 Market Trends
    • 8.4.2 Market Forecast
  • 8.5 Retail and E-Commerce
    • 8.5.1 Market Trends
    • 8.5.2 Market Forecast
  • 8.6 Others
    • 8.6.1 Market Trends
    • 8.6.2 Market Forecast

9 Market Breakup by Region

  • 9.1 North America
    • 9.1.1 United States
      • 9.1.1.1 Market Trends
      • 9.1.1.2 Market Forecast
    • 9.1.2 Canada
      • 9.1.2.1 Market Trends
      • 9.1.2.2 Market Forecast
  • 9.2 Asia-Pacific
    • 9.2.1 China
      • 9.2.1.1 Market Trends
      • 9.2.1.2 Market Forecast
    • 9.2.2 Japan
      • 9.2.2.1 Market Trends
      • 9.2.2.2 Market Forecast
    • 9.2.3 India
      • 9.2.3.1 Market Trends
      • 9.2.3.2 Market Forecast
    • 9.2.4 South Korea
      • 9.2.4.1 Market Trends
      • 9.2.4.2 Market Forecast
    • 9.2.5 Australia
      • 9.2.5.1 Market Trends
      • 9.2.5.2 Market Forecast
    • 9.2.6 Indonesia
      • 9.2.6.1 Market Trends
      • 9.2.6.2 Market Forecast
    • 9.2.7 Others
      • 9.2.7.1 Market Trends
      • 9.2.7.2 Market Forecast
  • 9.3 Europe
    • 9.3.1 Germany
      • 9.3.1.1 Market Trends
      • 9.3.1.2 Market Forecast
    • 9.3.2 France
      • 9.3.2.1 Market Trends
      • 9.3.2.2 Market Forecast
    • 9.3.3 United Kingdom
      • 9.3.3.1 Market Trends
      • 9.3.3.2 Market Forecast
    • 9.3.4 Italy
      • 9.3.4.1 Market Trends
      • 9.3.4.2 Market Forecast
    • 9.3.5 Spain
      • 9.3.5.1 Market Trends
      • 9.3.5.2 Market Forecast
    • 9.3.6 Russia
      • 9.3.6.1 Market Trends
      • 9.3.6.2 Market Forecast
    • 9.3.7 Others
      • 9.3.7.1 Market Trends
      • 9.3.7.2 Market Forecast
  • 9.4 Latin America
    • 9.4.1 Brazil
      • 9.4.1.1 Market Trends
      • 9.4.1.2 Market Forecast
    • 9.4.2 Mexico
      • 9.4.2.1 Market Trends
      • 9.4.2.2 Market Forecast
    • 9.4.3 Others
      • 9.4.3.1 Market Trends
      • 9.4.3.2 Market Forecast
  • 9.5 Middle East and Africa
    • 9.5.1 Market Trends
    • 9.5.2 Market Breakup by Country
    • 9.5.3 Market Forecast

10 SWOT Analysis

  • 10.1 Overview
  • 10.2 Strengths
  • 10.3 Weaknesses
  • 10.4 Opportunities
  • 10.5 Threats

11 Value Chain Analysis

12 Porters Five Forces Analysis

  • 12.1 Overview
  • 12.2 Bargaining Power of Buyers
  • 12.3 Bargaining Power of Suppliers
  • 12.4 Degree of Competition
  • 12.5 Threat of New Entrants
  • 12.6 Threat of Substitutes

13 Price Analysis

14 Competitive Landscape

  • 14.1 Market Structure
  • 14.2 Key Players
  • 14.3 Profiles of Key Players
    • 14.3.1 Alteryx Inc.
      • 14.3.1.1 Company Overview
      • 14.3.1.2 Product Portfolio
      • 14.3.1.3 Financials
    • 14.3.2 Cloudera Inc.
      • 14.3.2.1 Company Overview
      • 14.3.2.2 Product Portfolio
      • 14.3.2.3 Financials
    • 14.3.3 Dataiku Inc.
      • 14.3.3.1 Company Overview
      • 14.3.3.2 Product Portfolio
    • 14.3.4 Google LLC (Alphabet Inc.)
      • 14.3.4.1 Company Overview
      • 14.3.4.2 Product Portfolio
      • 14.3.4.3 SWOT Analysis
    • 14.3.5 H2O.ai Inc.
      • 14.3.5.1 Company Overview
      • 14.3.5.2 Product Portfolio
    • 14.3.6 International Business Machines Corporation
      • 14.3.6.1 Company Overview
      • 14.3.6.2 Product Portfolio
      • 14.3.6.3 Financials
      • 14.3.6.4 SWOT Analysis
    • 14.3.7 Microsoft Corporation
      • 14.3.7.1 Company Overview
      • 14.3.7.2 Product Portfolio
      • 14.3.7.3 Financials
      • 14.3.7.4 SWOT Analysis
    • 14.3.8 RapidMiner Inc.
      • 14.3.8.1 Company Overview
      • 14.3.8.2 Product Portfolio
    • 14.3.9 SAP SE
      • 14.3.9.1 Company Overview
      • 14.3.9.2 Product Portfolio
      • 14.3.9.3 Financials
      • 14.3.9.4 SWOT Analysis
    • 14.3.10 SAS Institute Inc.
      • 14.3.10.1 Company Overview
      • 14.3.10.2 Product Portfolio
      • 14.3.10.3 SWOT Analysis
    • 14.3.11 The MathWorks Inc.
      • 14.3.11.1 Company Overview
      • 14.3.11.2 Product Portfolio
    • 14.3.12 TIBCO Software Inc.
      • 14.3.12.1 Company Overview
      • 14.3.12.2 Product Portfolio
      • 14.3.12.3 SWOT Analysis