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1430560

資料角力：市場佔有率分析、產業趨勢與統計、成長預測（2024-2029）

Data Wrangling - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3個工作天內

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簡介目錄

根據預測，資料角力市場規模到 2024 年將達到 34.1 億美元，到 2029 年將達到 57.5 億美元，在預測期內（2024-2029 年）年複合成長率為 11.03%。

資料整理-市場-IMG1

隨著各種自動化技術的出現，資料縮減程序已經得到增強和改進。該行業可能會創建更複雜的人工智慧解決方案，以幫助預測期內的資料細化和資料分析過程。

主要亮點

  • 由於許多工業部門收集的資料數量和可靠性的快速發展，採用複雜的分析演算法來選擇可能徹底改變營業單位的見解。巨量資料使用的激增也產生了大量的非結構化資料。迭代和互動式資料分析的應用程式可以識別分佈和不一致，並提案流程改進建議。
  • 資料操作可以透過提高資訊一致性來提供對元資料的統計洞察。更一致的元資料允許自動化技術更快、更準確地詢問資料，通常會帶來這樣的發現。資料縮減可以清理資訊以確保模型運作良好，尤其是在開發有關預期市場表現的模型時。
  • 企業擴大使用資料角力來即時預測和監控可能影響業務績效的眾多事件。資料角力市場正在不斷成長，因為它有可能透過針對不可預見的事件（例如網路攻擊和其他緊急情況）做出複雜的決策來降低風險。此外，隨著網路攻擊的增加，對資料角力的需求也在增加，因為它使得發現和恢復資料變得更加容易。
  • 對資訊遺失或竊盜的擔憂日益加劇、BYOD（自帶設備）趨勢不斷成長以及業務敏捷性只是顯著加速資料角力市場成長的部分因素。這只是一個部門。預計資料角力行業將從邊緣運算的進步中受益匪淺。
  • 然而，資料品質問題限制了市場的擴張。資料角力產業預計將面臨挑戰，因為它尚未準備好從傳統 ETL 工具轉向尖端自動化技術。此外，這一市場擴張的主要障礙之一是中小型企業缺乏對資料角力工具的了解。
  • COVID-19 的爆發導致大量資料湧入。科技公司和資料聚合商利用來自手機訊號塔和行動應用程式的本地資料，使用儀表板來監控和追蹤聯絡人，以實施社會隔離並減少差異。該應用程式使用藍牙、建模工作和定位服務來預測醫院需求和傳染病負擔。由於透過此程式創建的資料存在缺陷，預計數百萬人將受到不利影響。資料角力用於清理、格式化和豐富原始資料，以幫助使用者更快、更準確地做出決策。因此，COVID-19 的資料角力要求提供了市場擴張的潛力。

資料角力市場趨勢

分析顯示，大公司佔較大市場佔有率

  • 預計大公司將在資料角力市場中​​佔據重要的市場佔有率，這主要是由於人工智慧和機器學習的採用不斷增加，以及由於先進技術的大量採用而導致資料量的增加。此外，大公司日益增加的監管壓力預計將為未來的市場擴張提供重大成長機會。
  • 此外，資料管理解決方案能夠透過快速分析資訊並採取行動來實現更好更快的決策並提供競爭優勢，這進一步推動了大型企業的需求。此外，大型企業正在採用資料角力來即時監控和預測可能影響大型組織績效的各種事件。
  • 此外，根據 IBM 的說法，人工智慧的採用因公司、國家和行業而異。大公司積極使用人工智慧作為營運一部分的可能性是大公司的兩倍，但小公司這樣做的可能性較小。公司更有可能調查人工智慧而不是積極追求它。到 2022 年，中國和印度超過一半的 IT 員工認為他們的公司已經積極參與人工智慧領域，而韓國 (22%)、美國(24%)、英國市場 ( 26%）。我相信公司正在根據這項政策採取。
  • 此外，隨著巨量資料的進步，大公司不斷發現新類型的資料。然而，隨著科技創造出越來越多的資料來源，資料管理持續成為企業面臨的更重要的挑戰。這類公司已經認知到資料管理在大型企業中的重要性，並正在推動市場的成長。
資料整理-市場-IMG2

北美預計將佔據很大佔有率

  • 預計北美將在預測期內主導資料角力市場，因為它是對資料角力工具和服務的採用貢獻最大的地區之一。此外，還分析了主要供應商的存在以及最終用戶行業不斷成長的採用率，以促進預測期內該地區的市場成長。
  • 隨著工業4.0服務的出現和巨量資料的應用，該地區預計將出現大規模成長。此外，巨量資料在美國是一個巨大的現象，各行各業的公司都透過從多個來源收集、分析和操作大量資料來獲利。
  • 持有大量股份的公司主要位於北美地區，並透過在該地區的大量投資和開拓而擁有重要的市場領導地位。 Trifacta、Altair Engineering, Inc、TIBCO Software Inc、Oracle Corporation 和 SAS Institute Inc 等公司均位於美國，並活躍於該地區的資料管理業務。
  • 該地區日益成長的技術趨勢，例如各種技術的投資、採用和整合，預計將為資料角力技術創造重要的商機，從而幫助公司有效地處理大量資料。此外，疫情後不斷成長的雲端採用趨勢正在推動該地區的市場成長。
資料整理-市場-IMG3

資料角力產業概述

資料角力市場因 Alteryx, Inc.、Oracle Corporation 和 Teradata Corporation 等幾家主要參與者的存在而得到鞏固。 Alteryx、Oracle、Teradata 等幾家主要企業正在透過持續的技術創新來獲得競爭優勢。透過研發、策略夥伴關係和併購，這些參與者正在市場上留下更強大的足跡。

2023 年 3 月，Simplebim 發布了 BIM資料管理軟體第 10 版，供建設公司、BIM 經理、建築師以及結構和設計工程師使用。該公司表示，其最新版本開闢了利用 IFC 文件中的資料來增強生產計畫和調度、採購、競標、成本估算、監控、安裝操作和其他下游 BIM資料使用的新方法。我將使之成為可能。

其他福利：

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章 簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業價值鏈分析
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 買家/消費者的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度
  • COVID-19 市場影響評估

第5章市場動態

  • 市場促進因素
    • 資料量增加
    • 人工智慧和巨量資料技術的進步
    • 人們對資料可靠性的擔憂日益加深
  • 市場限制因素
    • 企業缺乏資料管理工具意識
    • 顯式資料權限

第6章市場區隔

  • 按成分
    • 工具
    • 按服務
  • 按發展
    • 雲端基礎
    • 本地
  • 按公司類型
    • 小到中尺寸
    • 規模大
  • 按最終用戶產業
    • 資訊科技/通訊
    • 零售
    • 政府機關
    • BFSI
    • 衛生保健
    • 其他最終用戶產業
  • 地區
    • 北美洲
      • 美國
      • 加拿大
    • 歐洲
      • 英國
      • 德國
      • 法國
      • 歐洲其他地區
    • 亞太地區
      • 中國
      • 日本
      • 新加坡
      • 其他亞太地區
    • 拉丁美洲
      • 墨西哥
      • 巴西
      • 其他拉丁美洲
    • 中東/非洲
      • 阿拉伯聯合大公國
      • 沙烏地阿拉伯
      • 其他中東/非洲

第7章 競爭形勢

  • 公司簡介
    • Alteryx, Inc.
    • TIBCO Software Inc.（Cloud Software Group, Inc.）
    • Altair Engineering Inc.
    • Teradata Corporation
    • Oracle Corporation
    • SAS Institute Inc.
    • Datameer, Inc.
    • DataRobot, Inc.
    • Cloudera, Inc.
    • Cambridge Semantics, Inc.

第8章投資分析

第9章 市場機會及未來趨勢

簡介目錄
Product Code: 64268

The Data Wrangling Market size is estimated at USD 3.41 billion in 2024, and is expected to reach USD 5.75 billion by 2029, growing at a CAGR of 11.03% during the forecast period (2024-2029).

Data Wrangling - Market - IMG1

The creation of various automated technologies has already enhanced and improved the data-wrangling procedure. The industry would create more complex AI solutions during the forecast period to assist the processes of data wrangling and data analysis.

Key Highlights

  • The adoption of sophisticated analytics algorithms to choose insights that might revolutionize a business entity results from the rapid development in the quantity and reliability of data collected throughout many industrial verticals. Massive amounts of unstructured data have also been produced due to the surge in Big Data usage. Applications for iterative and interactive data wrangling may identify distributions and inconsistencies and suggest process improvement.
  • Data manipulation can offer statistical insights into the metadata by making the information more consistent. Increased metadata consistency makes it possible for automated technologies to examine the data more quickly and precisely, frequently leading to these findings. Data wrangling would clean the information to enable a model to operate without problems, mainly in developing a model about expected market performance.
  • Businesses are increasingly using data wrangling for real-time forecasting and monitoring of numerous events that may impact their performance. The market for data wrangling is expanding due to the potential to mitigate risks by executing complicated judgments concerning unplanned occurrences, such as cyberattacks and other emergencies. Also, as more cyberattacks occur, there is a growing demand for data wrangling since it makes data simpler to find and recover.
  • Growing concerns about information loss and theft, expanding Bring Your Own Device (BYOD) trends, and business mobility are just a few factors that are significantly accelerating the growth of the data wrangling market.The industry of data wrangling is predicted to benefit significantly from advances in edge computing.
  • However, issues with data quality are limiting the market's ability to expand.The data-wrangling industry is anticipated to face challenges due to a lack of readiness to switch from conventional ETL tools to cutting-edge automated technologies. Further, one of the key obstacles to this market's expansion is the lack of knowledge about data-wrangling tools among small and medium-sized businesses.
  • The COVID-19 epidemic brought on a considerable data influx. Technological firms and data aggregators exploited local data from cell towers and mobile applications to impose social segregation and close the gaps using dashboards that monitored and tracked contacts. Applications predicted hospital requirements and epidemic burden using Bluetooth, modeling efforts, and geolocation services. As a result of the flawed data produced throughout this procedure, millions of people were expected to be negatively impacted. Data wrangling is used to clean, arrange, and enhance raw data into the appropriate format for users to make better decisions more quickly and accurately. As a result, COVID-19's requirement for data wrangling provided market potential for expansion.

Data Wrangling Market Trends

Large Enterprises are Analyzed to Hold Significant Market Share

  • Large enterprises are expected to hold significant market share in the data wrangling market primarly due to increasing adoption of AI and ML, growing volume of data owing to the substantial adoption of advanced technologies. Furthermore, increasing regulatory pressure among the large enterprises is expected to present major growth opportunities for the expansion of the market in future.
  • Additionally, the ability of data-wrangling solutions to deliver better and faster decision-making and to offer a competitive advantage by analyzing and acting upon information promptly further boosts the demand among large enterprises. Furthermore, large enterprises are adopting data wrangling for real-time monitoring and forecasting of various occasions that may affect the performance of large organizations.
  • Moreover, according to IBM, the adoption of AI varies amongst businesses, countries, and sectors. While larger firms are twice as likely to have actively used AI as part of their company operations, smaller businesses are less likely. Companies are more likely to investigate AI than actively pursue it. As of 2022, a majority of IT workers in China and India, compared to markets like South Korea (22%), Australia (24%), the United States (25%), and the United Kingdom (26%), believe their organization is already actively employing AI.
  • Further, large businesses are constantly discovering new data kinds as big data continues to progress. Data management, however, keeps becoming a more significant challenge for firms as technology produces more and more data sources. Such companies significantly recognize the importance of data wrangling in the large businesses, thereby driving market growth.
Data Wrangling - Market - IMG2

North America is Expected to Hold the Significant Share

  • North America is expected to dominate data wrangling during the forecast period, as the region remains one of the most significant contributors to the adoption of data wrangling tools and services. Further, the presence of major market vendors coupled witg growing adoption among end-user industries is analyzed to boost the market growth in the region over the forecast period.
  • The region is expected to witness massive growth along with the application of big data due to the emergence of Industry 4.0 services. Moreover, big data is an enormous phenomenon in the United States, and companies from various industries benefit from collecting, analyzing, and manipulating vast amounts of data from multiple sources.
  • The significant shareholding firms are considerably based in the North America region, which significantly drives the market with considerable investments and developments in the region. Companies such as Trifacta, Altair Engineering, Inc., TIBCO Software Inc., Oracle Corporation, SAS Institute Inc., etc., are based in the United States and are actively engaged in the operation of data wrangling in the region.
  • The rising technological trends in terms of investments, adoption, and integration of various technologies in the region would significantly create opportunities for data wrangling technology in assisting firms to work effectively in handling huge amounts of data. Further, the increased trends of cloud adoption in the region post-pandemic boosted market growth in the region.
Data Wrangling - Market - IMG3

Data Wrangling Industry Overview

The data wrangling market is consolidated owing to the presence of a few key players, such as Alteryx, Inc., Oracle Corporation, and Teradata Corporation, amongst others. Their ability to continually innovate their offerings has allowed them to gain a competitive advantage over others. Through research and development, strategic partnerships, and mergers and acquisitions, these players have gained a stronger footprint in the market.

In March 2023, Simplebim released version 10 of its BIM data wrangling software used by construction firms, BIM managers, architects, and structural and design engineers. According to the company, the latest release by the company opens up new ways to use data in IFC files to enable enhanced production planning and scheduling, procurement, tendering, cost estimation, monitoring, installation work, and other downstream BIM data usage.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Value Chain Analysis
  • 4.3 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.3.1 Bargaining Power of Suppliers
    • 4.3.2 Bargaining Power of Buyers/Consumers
    • 4.3.3 Threat of New Entrants
    • 4.3.4 Threat of Substitute Products
    • 4.3.5 Intensity of Competitive Rivalry
  • 4.4 Assessment of the Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Growing Volumes of Data
    • 5.1.2 Advancement in AI And Big Data Technologies
    • 5.1.3 Growing Concern about Data Veracity
  • 5.2 Market Restraints
    • 5.2.1 Lack Of Awareness Of Data Wrangling Tools Among Enterprises
    • 5.2.2 Explicit Data Access Permission

6 MARKET SEGMENTATION

  • 6.1 By Component
    • 6.1.1 Tools
    • 6.1.2 Service
  • 6.2 By Deployment
    • 6.2.1 Cloud-Based
    • 6.2.2 On-premises
  • 6.3 By Enterprise Type
    • 6.3.1 Small and Medium Sized
    • 6.3.2 Large
  • 6.4 By End-user Industry
    • 6.4.1 IT and Telecommunication
    • 6.4.2 Retail
    • 6.4.3 Government
    • 6.4.4 BFSI
    • 6.4.5 Healthcare
    • 6.4.6 Other End-user Industries
  • 6.5 Geography
    • 6.5.1 North America
      • 6.5.1.1 United States
      • 6.5.1.2 Canada
    • 6.5.2 Europe
      • 6.5.2.1 United Kingdom
      • 6.5.2.2 Germany
      • 6.5.2.3 France
      • 6.5.2.4 Rest of Europe
    • 6.5.3 Asia-Pacific
      • 6.5.3.1 China
      • 6.5.3.2 Japan
      • 6.5.3.3 Singapore
      • 6.5.3.4 Rest of Asia-Pacific
    • 6.5.4 Latin America
      • 6.5.4.1 Mexico
      • 6.5.4.2 Brazil
      • 6.5.4.3 Rest of Latin America
    • 6.5.5 Middle East and Africa
      • 6.5.5.1 United Arab Emirates
      • 6.5.5.2 Saudi Arabia
      • 6.5.5.3 Rest of Middle-East & Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Alteryx, Inc.
    • 7.1.2 TIBCO Software Inc. (Cloud Software Group, Inc.)
    • 7.1.3 Altair Engineering Inc.
    • 7.1.4 Teradata Corporation
    • 7.1.5 Oracle Corporation
    • 7.1.6 SAS Institute Inc.
    • 7.1.7 Datameer, Inc.
    • 7.1.8 DataRobot, Inc.
    • 7.1.9 Cloudera, Inc.
    • 7.1.10 Cambridge Semantics, Inc.

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS