Unstructured data is any type of information that is not stored in a traditional database or spreadsheet. Examples of unstructured data include text (e.g., user reviews, documents, or social media chat history) and non-text content (e.g., visuals and sound). Geographical and IoT streaming info are among the newer types of unstructured data.
Unstructured data management is the process of collecting, storing, organizing, and听analyzing data听that doesn鈥檛 have any predefined structure.
Highlights
The global Unstructured Data Management market was valued at US$ million in 2022 and is anticipated to reach US$ million by 2029, witnessing a CAGR of % during the forecast period 2023-2029. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
North American market for Unstructured Data Management is estimated to increase from $ million in 2023 to reach $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
Asia-Pacific market for Unstructured Data Management is estimated to increase from $ million in 2023 to reach $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
The global market for Unstructured Data Management in Large Enterprises is estimated to increase from $ million in 2023 to $ million by 2029, at a CAGR of % during the forecast period of 2023 through 2029.
The key global companies of Unstructured Data Management include NetApp, Accenture, Astera Software, SAS(SAS Text Miner), Microsoft Azure(Azure Cognitive Services), IBM(Watson), Bismart Folksonomy, Provalis Research(Provalis WordStat) and IT PRO, etc. In 2022, the world's top three vendors accounted for approximately % of the revenue.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Unstructured Data Management, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Unstructured Data Management.
The Unstructured Data Management market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2022 as the base year, with history and forecast data for the period from 2018 to 2029. This report segments the global Unstructured Data Management market comprehensively. Regional market sizes, concerning products by type, by application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Unstructured Data Management companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by type, by application, and by regions.
By Company
NetApp
Accenture
Astera Software
SAS(SAS Text Miner)
Microsoft Azure(Azure Cognitive Services)
IBM(Watson)
Bismart Folksonomy
Provalis Research(Provalis WordStat)
IT PRO
MonkeyLearn Inc.
HubStor
Dell
Creme Global
Straive(SPi Global)
Oyster IMS
e-Zest
Quadratyx
Astera
Aparavi
Micro Focus
Komprise
Segment by Type
by Service Type
Platform-as-a-Service (PaaS)
Software-as-a-Service(SaaS)
by Storage Location
Cloud-Based
On-Premise
Segment by Application
Large Enterprises
SMEs
Other
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Core Chapters
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Unstructured Data Management companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the key companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 麻豆原创 Analysis by Service Type
1.2.1 Global Unstructured Data Management 麻豆原创 Size Growth Rate by Service Type: 2018 VS 2022 VS 2029
1.2.2 Platform-as-a-Service (PaaS)
1.2.3 Software-as-a-Service(SaaS)
1.3 麻豆原创 by Application
1.3.1 Global Unstructured Data Management 麻豆原创 Growth by Application: 2018 VS 2022 VS 2029
1.3.2 Large Enterprises
1.3.3 SMEs
1.3.4 Other
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Unstructured Data Management 麻豆原创 Perspective (2018-2029)
2.2 Unstructured Data Management Growth Trends by Region
2.2.1 Global Unstructured Data Management 麻豆原创 Size by Region: 2018 VS 2022 VS 2029
2.2.2 Unstructured Data Management Historic 麻豆原创 Size by Region (2018-2023)
2.2.3 Unstructured Data Management Forecasted 麻豆原创 Size by Region (2024-2029)
2.3 Unstructured Data Management 麻豆原创 Dynamics
2.3.1 Unstructured Data Management Industry Trends
2.3.2 Unstructured Data Management 麻豆原创 Drivers
2.3.3 Unstructured Data Management 麻豆原创 Challenges
2.3.4 Unstructured Data Management 麻豆原创 Restraints
3 Competition Landscape by Key Players
3.1 Global Top Unstructured Data Management Players by Revenue
3.1.1 Global Top Unstructured Data Management Players by Revenue (2018-2023)
3.1.2 Global Unstructured Data Management Revenue 麻豆原创 Share by Players (2018-2023)
3.2 Global Unstructured Data Management 麻豆原创 Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Unstructured Data Management Revenue
3.4 Global Unstructured Data Management 麻豆原创 Concentration Ratio
3.4.1 Global Unstructured Data Management 麻豆原创 Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Unstructured Data Management Revenue in 2022
3.5 Unstructured Data Management Key Players Head office and Area Served
3.6 Key Players Unstructured Data Management Product Solution and Service
3.7 Date of Enter into Unstructured Data Management 麻豆原创
3.8 Mergers & Acquisitions, Expansion Plans
4 Unstructured Data Management Breakdown Data by Type
4.1 Global Unstructured Data Management Historic 麻豆原创 Size by Type (2018-2023)
4.2 Global Unstructured Data Management Forecasted 麻豆原创 Size by Type (2024-2029)
5 Unstructured Data Management Breakdown Data by Application
5.1 Global Unstructured Data Management Historic 麻豆原创 Size by Application (2018-2023)
5.2 Global Unstructured Data Management Forecasted 麻豆原创 Size by Application (2024-2029)
6 North America
6.1 North America Unstructured Data Management 麻豆原创 Size (2018-2029)
6.2 North America Unstructured Data Management 麻豆原创 Growth Rate by Country: 2018 VS 2022 VS 2029
6.3 North America Unstructured Data Management 麻豆原创 Size by Country (2018-2023)
6.4 North America Unstructured Data Management 麻豆原创 Size by Country (2024-2029)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Unstructured Data Management 麻豆原创 Size (2018-2029)
7.2 Europe Unstructured Data Management 麻豆原创 Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 Europe Unstructured Data Management 麻豆原创 Size by Country (2018-2023)
7.4 Europe Unstructured Data Management 麻豆原创 Size by Country (2024-2029)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Unstructured Data Management 麻豆原创 Size (2018-2029)
8.2 Asia-Pacific Unstructured Data Management 麻豆原创 Growth Rate by Region: 2018 VS 2022 VS 2029
8.3 Asia-Pacific Unstructured Data Management 麻豆原创 Size by Region (2018-2023)
8.4 Asia-Pacific Unstructured Data Management 麻豆原创 Size by Region (2024-2029)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Unstructured Data Management 麻豆原创 Size (2018-2029)
9.2 Latin America Unstructured Data Management 麻豆原创 Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Latin America Unstructured Data Management 麻豆原创 Size by Country (2018-2023)
9.4 Latin America Unstructured Data Management 麻豆原创 Size by Country (2024-2029)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Unstructured Data Management 麻豆原创 Size (2018-2029)
10.2 Middle East & Africa Unstructured Data Management 麻豆原创 Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Middle East & Africa Unstructured Data Management 麻豆原创 Size by Country (2018-2023)
10.4 Middle East & Africa Unstructured Data Management 麻豆原创 Size by Country (2024-2029)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 NetApp
11.1.1 NetApp Company Detail
11.1.2 NetApp Business Overview
11.1.3 NetApp Unstructured Data Management Introduction
11.1.4 NetApp Revenue in Unstructured Data Management Business (2018-2023)
11.1.5 NetApp Recent Development
11.2 Accenture
11.2.1 Accenture Company Detail
11.2.2 Accenture Business Overview
11.2.3 Accenture Unstructured Data Management Introduction
11.2.4 Accenture Revenue in Unstructured Data Management Business (2018-2023)
11.2.5 Accenture Recent Development
11.3 Astera Software
11.3.1 Astera Software Company Detail
11.3.2 Astera Software Business Overview
11.3.3 Astera Software Unstructured Data Management Introduction
11.3.4 Astera Software Revenue in Unstructured Data Management Business (2018-2023)
11.3.5 Astera Software Recent Development
11.4 SAS(SAS Text Miner)
11.4.1 SAS(SAS Text Miner) Company Detail
11.4.2 SAS(SAS Text Miner) Business Overview
11.4.3 SAS(SAS Text Miner) Unstructured Data Management Introduction
11.4.4 SAS(SAS Text Miner) Revenue in Unstructured Data Management Business (2018-2023)
11.4.5 SAS(SAS Text Miner) Recent Development
11.5 Microsoft Azure(Azure Cognitive Services)
11.5.1 Microsoft Azure(Azure Cognitive Services) Company Detail
11.5.2 Microsoft Azure(Azure Cognitive Services) Business Overview
11.5.3 Microsoft Azure(Azure Cognitive Services) Unstructured Data Management Introduction
11.5.4 Microsoft Azure(Azure Cognitive Services) Revenue in Unstructured Data Management Business (2018-2023)
11.5.5 Microsoft Azure(Azure Cognitive Services) Recent Development
11.6 IBM(Watson)
11.6.1 IBM(Watson) Company Detail
11.6.2 IBM(Watson) Business Overview
11.6.3 IBM(Watson) Unstructured Data Management Introduction
11.6.4 IBM(Watson) Revenue in Unstructured Data Management Business (2018-2023)
11.6.5 IBM(Watson) Recent Development
11.7 Bismart Folksonomy
11.7.1 Bismart Folksonomy Company Detail
11.7.2 Bismart Folksonomy Business Overview
11.7.3 Bismart Folksonomy Unstructured Data Management Introduction
11.7.4 Bismart Folksonomy Revenue in Unstructured Data Management Business (2018-2023)
11.7.5 Bismart Folksonomy Recent Development
11.8 Provalis Research(Provalis WordStat)
11.8.1 Provalis Research(Provalis WordStat) Company Detail
11.8.2 Provalis Research(Provalis WordStat) Business Overview
11.8.3 Provalis Research(Provalis WordStat) Unstructured Data Management Introduction
11.8.4 Provalis Research(Provalis WordStat) Revenue in Unstructured Data Management Business (2018-2023)
11.8.5 Provalis Research(Provalis WordStat) Recent Development
11.9 IT PRO
11.9.1 IT PRO Company Detail
11.9.2 IT PRO Business Overview
11.9.3 IT PRO Unstructured Data Management Introduction
11.9.4 IT PRO Revenue in Unstructured Data Management Business (2018-2023)
11.9.5 IT PRO Recent Development
11.10 MonkeyLearn Inc.
11.10.1 MonkeyLearn Inc. Company Detail
11.10.2 MonkeyLearn Inc. Business Overview
11.10.3 MonkeyLearn Inc. Unstructured Data Management Introduction
11.10.4 MonkeyLearn Inc. Revenue in Unstructured Data Management Business (2018-2023)
11.10.5 MonkeyLearn Inc. Recent Development
11.11 HubStor
11.11.1 HubStor Company Detail
11.11.2 HubStor Business Overview
11.11.3 HubStor Unstructured Data Management Introduction
11.11.4 HubStor Revenue in Unstructured Data Management Business (2018-2023)
11.11.5 HubStor Recent Development
11.12 Dell
11.12.1 Dell Company Detail
11.12.2 Dell Business Overview
11.12.3 Dell Unstructured Data Management Introduction
11.12.4 Dell Revenue in Unstructured Data Management Business (2018-2023)
11.12.5 Dell Recent Development
11.13 Creme Global
11.13.1 Creme Global Company Detail
11.13.2 Creme Global Business Overview
11.13.3 Creme Global Unstructured Data Management Introduction
11.13.4 Creme Global Revenue in Unstructured Data Management Business (2018-2023)
11.13.5 Creme Global Recent Development
11.14 Straive(SPi Global)
11.14.1 Straive(SPi Global) Company Detail
11.14.2 Straive(SPi Global) Business Overview
11.14.3 Straive(SPi Global) Unstructured Data Management Introduction
11.14.4 Straive(SPi Global) Revenue in Unstructured Data Management Business (2018-2023)
11.14.5 Straive(SPi Global) Recent Development
11.15 Oyster IMS
11.15.1 Oyster IMS Company Detail
11.15.2 Oyster IMS Business Overview
11.15.3 Oyster IMS Unstructured Data Management Introduction
11.15.4 Oyster IMS Revenue in Unstructured Data Management Business (2018-2023)
11.15.5 Oyster IMS Recent Development
11.16 e-Zest
11.16.1 e-Zest Company Detail
11.16.2 e-Zest Business Overview
11.16.3 e-Zest Unstructured Data Management Introduction
11.16.4 e-Zest Revenue in Unstructured Data Management Business (2018-2023)
11.16.5 e-Zest Recent Development
11.17 Quadratyx
11.17.1 Quadratyx Company Detail
11.17.2 Quadratyx Business Overview
11.17.3 Quadratyx Unstructured Data Management Introduction
11.17.4 Quadratyx Revenue in Unstructured Data Management Business (2018-2023)
11.17.5 Quadratyx Recent Development
11.18 Astera
11.18.1 Astera Company Detail
11.18.2 Astera Business Overview
11.18.3 Astera Unstructured Data Management Introduction
11.18.4 Astera Revenue in Unstructured Data Management Business (2018-2023)
11.18.5 Astera Recent Development
11.19 Aparavi
11.19.1 Aparavi Company Detail
11.19.2 Aparavi Business Overview
11.19.3 Aparavi Unstructured Data Management Introduction
11.19.4 Aparavi Revenue in Unstructured Data Management Business (2018-2023)
11.19.5 Aparavi Recent Development
11.20 Micro Focus
11.20.1 Micro Focus Company Detail
11.20.2 Micro Focus Business Overview
11.20.3 Micro Focus Unstructured Data Management Introduction
11.20.4 Micro Focus Revenue in Unstructured Data Management Business (2018-2023)
11.20.5 Micro Focus Recent Development
11.21 Komprise
11.21.1 Komprise Company Detail
11.21.2 Komprise Business Overview
11.21.3 Komprise Unstructured Data Management Introduction
11.21.4 Komprise Revenue in Unstructured Data Management Business (2018-2023)
11.21.5 Komprise Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
NetApp
Accenture
Astera Software
SAS(SAS Text Miner)
Microsoft Azure(Azure Cognitive Services)
IBM(Watson)
Bismart Folksonomy
Provalis Research(Provalis WordStat)
IT PRO
MonkeyLearn Inc.
HubStor
Dell
Creme Global
Straive(SPi Global)
Oyster IMS
e-Zest
Quadratyx
Astera
Aparavi
Micro Focus
Komprise
听
听
*If Applicable.
