Global Data Wrangling Market Size, Industry Analysis By Segmentations, Top Key Players, Trends, Future Development & Forecast 2024-2035
- PUBLISHED ON
- 3/1/2023
- NO OF PAGES
- 224
- CATEGORY
- Information Technology
Market Overview:
The Global Data Wrangling Market size was valued at USD 3.45 million in 2022 and is projected to reach USD 7.58 million by 2032 at a CAGR of 21.5% from 2022 to 2032.
Data wrangling, also known as data munging, is the process of cleaning and transforming raw data into a usable form for analysis. It involves various steps such as data cleaning, data transformation, and data integration to convert data from multiple sources into a structured format. One of the driving factors for the adoption of data wrangling is the exponential growth of data, which is making it increasingly difficult for organizations to manage and analyze their data using traditional methods. By automating the data wrangling process, organizations can save time and resources while improving the quality of their data.
Additionally, the increasing demand for data-driven insights and the rise of machine learning and artificial intelligence are also driving the adoption of data wrangling. By cleaning and transforming data into a structured format, data wrangling helps to create high-quality data sets that can be used for machine learning and other advanced analytics applications. However, challenges to the adoption of data wrangling include the lack of standardization in data formats and the complexity of integrating data from multiple sources. Additionally, the need for specialized skills and expertise in data wrangling can be a barrier for some organizations.
The increasing volume and complexity of data is driving the growth of the global data wrangling market.
Data wrangling, also known as data cleaning or data preprocessing, refers to the process of transforming and mapping raw data from various sources into a usable format for analysis. With the rise of big data and the Internet of Things (IoT), organizations are generating huge amounts of data on a daily basis. However, this data is often incomplete, inconsistent, and contains errors, making it difficult to extract insights and value from it. Data wrangling addresses these challenges by providing a way to clean, transform, and structure data into a usable format. The growth of the data wrangling market is being driven by the increasing volume and complexity of data being generated by organizations. This includes data from a wide range of sources such as sensors, social media, mobile devices, and machine-generated data. As the volume of data continues to grow, organizations are facing significant challenges in managing and making sense of it. Data wrangling tools and techniques can help to address these challenges by providing a way to automate data cleaning, transformation, and integration.
One of the key advantages of data wrangling is that it can help to improve data quality and accuracy. By cleaning and transforming data, organizations can reduce errors and inconsistencies in their data, which can improve the accuracy of their analysis and decision-making. Data wrangling can also help to save time and resources by automating the data cleaning and transformation process, which can be a time-consuming and resource-intensive task when done manually. Data wrangling has a wide range of uses across industries and applications. In the financial industry, data wrangling can be used to analyze large volumes of financial data and identify patterns and trends that can be used to inform investment decisions. In the healthcare industry, data wrangling can be used to clean and integrate patient data from different sources to improve patient outcomes and drive research. The adoption of data wrangling is growing rapidly, as organizations seek to gain insights from their data and make data-driven decisions. This is being driven by the increasing availability of data wrangling tools and technologies, as well as the growing awareness of the benefits of data-driven decision-making.
Segmentation:
By Component
· Solution
· Service
By Deployment Mode
· On-Premise
· Cloud
By Organization Size
· Large Enterprises
· Small & Medium Enterprises
Geography:
As per recent market industry experts, North America and Europe hold the largest market share in the data wrangling market. However, the Asia-Pacific region is expected to grow at a significant pace in the coming years due to the increasing adoption of cloud-based technologies and the growing focus on big data analytics in emerging economies like China and India.
Impact of COVID-19 on the global Data Wrangling Market:
The COVID-19 pandemic has impacted the data wrangling market in several ways. With the widespread adoption of remote work, the demand for cloud-based data wrangling solutions has increased significantly. Many businesses have had to adapt to remote work and rely on digital platforms for communication and collaboration, which has created a higher need for efficient data management and processing. On the other hand, the pandemic has also caused disruptions in the supply chain and resulted in reduced IT budgets for some companies, which may have slowed down the adoption of data wrangling solutions. Some industries, such as travel and hospitality, have been severely impacted by the pandemic and may have cut back on technology investments. Overall, the impact of the pandemic on the data wrangling market has been mixed, with both positive and negative effects. The long-term effects are yet to be seen as the world continues to navigate the pandemic and its aftermath.
Impact of the Russia-Ukraine War on the global Data Wrangling Market:
The political and economic instability in any region can have indirect impacts on the market. It is possible that any disruption in the supply chain or changes in trade policies due to the war could have an impact on the market. Additionally, if the war causes significant damage to technology infrastructure, it could potentially impact the market. When there is political instability or conflict in a region, it can cause economic uncertainty and disrupt supply chains, which may impact businesses and their investments. This uncertainty can cause a reduction in demand for services and products, including data wrangling services. Additionally, geopolitical events can also impact the availability of skilled labor and talent in the market. In the case of the Russia-Ukraine war, it could potentially result in a shortage of data wrangling talent or difficulty in finding qualified professionals to work on projects. It is also possible that the conflict could lead to changes in regulations or trade policies that could impact the data wrangling market. For example, if economic sanctions are put in place, it could make it more difficult for companies to do business with clients in certain countries or to access specific technologies and tools.
Company Profiles:
· Alteryx, Inc.
· Hitachi Vantara Corporation
· International Business Machines Corporation
· Impetus Technologies, Inc.
· Oracle Corporation
· Paxata, Inc.
· SAS Institute Inc.
· TIBCO Software Inc.
· Teradata Corporation
· Trifacta
Global Data Wrangling Market: By Regions
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia, and Rest of Asia-Pacific)
South America (Brazil, Argentina, Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
Key Benefits:
• The analysis provides an overview of the factors driving and limiting the growth of the market including trends, structure and others.
• Market estimation for type and geographic segments is derived from the current market scenario and expected market trends.
• Porter’s Five Force Model and SWOT analysis are used to study the global Data Wrangling market and would help stakeholders make strategic decisions.
• The analysis assists in understanding the strategies adopted by the companies for the growth of this market.
• In-depth analysis of the types of Data Wrangling would help in identifying future applications in this market.
Reasons to Purchase this Report:
• Qualitative and quantitative analysis of the market based on segmentation involving both economic as well as non-economic factors
• Provision of market value (USD Billion) data for each segment and sub-segment
• Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market
• Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region
• Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled
• Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players
• The current as well as the future market outlook of the industry with respect to recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions
• Includes in-depth analysis of the market of various perspectives through Porter’s five forces analysis
• Provides insight into the market through Value Chain
• Market dynamics scenario, along with growth opportunities of the market in the years to come
• 6-month post-sales analyst support
Objectives of the Study:
• To provide with an exhaustive analysis on the Data Wrangling Market by Product, By Application, By End User and by Region.
• To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
• To evaluate and forecast micro-markets and the overall market
• To predict the market size, in key regions— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
• To record and evaluate competitive landscape mapping- product launches, technological advancements, mergers and expansions
Historic Year: 2016-2022
Forecast: 2024-2035
1.1 Product Overview and Scope of Data Wrangling
1.2 Classification of Data Wrangling by Type
1.2.1 Overview: Global Data Wrangling Market Size by Type: 2017 Versus 2022 Versus 2032
1.2.2 Global Data Wrangling Revenue Market Share by Type in 2022
1.2.3 On-premises
1.2.4 Cloud Based
1.3 Global Data Wrangling Market by Application
1.3.1 Overview: Global Data Wrangling Market Size by Application: 2017 Versus 2022 Versus 2032
1.3.2 BFSI
1.3.3 Telecom and IT
1.3.4 Retail and eCommerce
1.3.5 Healthcare and Life Sciences
1.3.6 Travel and Hospitality
1.3.7 Government
1.3.8 Manufacturing
1.3.9 Energy and Utilities
1.3.10 Transportation and Logistics
1.3.11 Others
1.4 Global Data Wrangling Market Size & Forecast
1.5 Global Data Wrangling Market Size and Forecast by Region
1.5.1 Global Data Wrangling Market Size by Region: 2017 VS 2022 VS 2032
1.5.2 Global Data Wrangling Market Size by Region, (2016-2021)
1.5.3 North America Data Wrangling Market Size and Prospect (2017-2032)
1.5.4 Europe Data Wrangling Market Size and Prospect (2017-2032)
1.5.5 Asia-Pacific Data Wrangling Market Size and Prospect (2017-2032)
1.5.6 South America Data Wrangling Market Size and Prospect (2017-2032)
1.5.7 Middle East and Africa Data Wrangling Market Size and Prospect (2017-2032)
1.6 Market Drivers, Restraints and Trends
1.6.1 Data Wrangling Market Drivers
1.6.2 Data Wrangling Market Restraints
1.6.3 Data Wrangling Trends Analysis
2 Company Profiles
2.1 IBM
2.1.1 IBM Details
2.1.2 IBM Major Business
2.1.3 IBM Data Wrangling Product and Solutions
2.1.4 IBM Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.1.5 IBM Recent Developments and Future Plans
2.2 Oracle
2.2.1 Oracle Details
2.2.2 Oracle Major Business
2.2.3 Oracle Data Wrangling Product and Solutions
2.2.4 Oracle Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.2.5 Oracle Recent Developments and Future Plans
2.3 SAS
2.3.1 SAS Details
2.3.2 SAS Major Business
2.3.3 SAS Data Wrangling Product and Solutions
2.3.4 SAS Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.3.5 SAS Recent Developments and Future Plans
2.4 Trifacta
2.4.1 Trifacta Details
2.4.2 Trifacta Major Business
2.4.3 Trifacta Data Wrangling Product and Solutions
2.4.4 Trifacta Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.4.5 Trifacta Recent Developments and Future Plans
2.5 Datawatch
2.5.1 Datawatch Details
2.5.2 Datawatch Major Business
2.5.3 Datawatch Data Wrangling Product and Solutions
2.5.4 Datawatch Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.5.5 Datawatch Recent Developments and Future Plans
2.6 Talend
2.6.1 Talend Details
2.6.2 Talend Major Business
2.6.3 Talend Data Wrangling Product and Solutions
2.6.4 Talend Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.6.5 Talend Recent Developments and Future Plans
2.7 Alteryx
2.7.1 Alteryx Details
2.7.2 Alteryx Major Business
2.7.3 Alteryx Data Wrangling Product and Solutions
2.7.4 Alteryx Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.7.5 Alteryx Recent Developments and Future Plans
2.8 Dataiku
2.8.1 Dataiku Details
2.8.2 Dataiku Major Business
2.8.3 Dataiku Data Wrangling Product and Solutions
2.8.4 Dataiku Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.8.5 Dataiku Recent Developments and Future Plans
2.9 TIBCO Software
2.9.1 TIBCO Software Details
2.9.2 TIBCO Software Major Business
2.9.3 TIBCO Software Data Wrangling Product and Solutions
2.9.4 TIBCO Software Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.9.5 TIBCO Software Recent Developments and Future Plans
2.10 Paxata
2.10.1 Paxata Details
2.10.2 Paxata Major Business
2.10.3 Paxata Data Wrangling Product and Solutions
2.10.4 Paxata Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.10.5 Paxata Recent Developments and Future Plans
2.11 Informatica
2.11.1 Informatica Details
2.11.2 Informatica Major Business
2.11.3 Informatica Data Wrangling Product and Solutions
2.11.4 Informatica Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.11.5 Informatica Recent Developments and Future Plans
2.12 Hitachi Vantara
2.12.1 Hitachi Vantara Details
2.12.2 Hitachi Vantara Major Business
2.12.3 Hitachi Vantara Data Wrangling Product and Solutions
2.12.4 Hitachi Vantara Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.12.5 Hitachi Vantara Recent Developments and Future Plans
2.13 Teradata
2.13.1 Teradata Details
2.13.2 Teradata Major Business
2.13.3 Teradata Data Wrangling Product and Solutions
2.13.4 Teradata Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.13.5 Teradata Recent Developments and Future Plans
2.14 IRI
2.14.1 IRI Details
2.14.2 IRI Major Business
2.14.3 IRI Data Wrangling Product and Solutions
2.14.4 IRI Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.14.5 IRI Recent Developments and Future Plans
2.15 Brillio
2.15.1 Brillio Details
2.15.2 Brillio Major Business
2.15.3 Brillio Data Wrangling Product and Solutions
2.15.4 Brillio Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.15.5 Brillio Recent Developments and Future Plans
2.16 Onedot
2.16.1 Onedot Details
2.16.2 Onedot Major Business
2.16.3 Onedot Data Wrangling Product and Solutions
2.16.4 Onedot Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.16.5 Onedot Recent Developments and Future Plans
2.17 TMMData
2.17.1 TMMData Details
2.17.2 TMMData Major Business
2.17.3 TMMData Data Wrangling Product and Solutions
2.17.4 TMMData Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.17.5 TMMData Recent Developments and Future Plans
2.18 Datameer
2.18.1 Datameer Details
2.18.2 Datameer Major Business
2.18.3 Datameer Data Wrangling Product and Solutions
2.18.4 Datameer Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.18.5 Datameer Recent Developments and Future Plans
2.19 Cooladata
2.19.1 Cooladata Details
2.19.2 Cooladata Major Business
2.19.3 Cooladata Data Wrangling Product and Solutions
2.19.4 Cooladata Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.19.5 Cooladata Recent Developments and Future Plans
2.20 Unifi Software
2.20.1 Unifi Software Details
2.20.2 Unifi Software Major Business
2.20.3 Unifi Software Data Wrangling Product and Solutions
2.20.4 Unifi Software Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.20.5 Unifi Software Recent Developments and Future Plans
2.21 Rapid Insight
2.21.1 Rapid Insight Details
2.21.2 Rapid Insight Major Business
2.21.3 Rapid Insight Data Wrangling Product and Solutions
2.21.4 Rapid Insight Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.21.5 Rapid Insight Recent Developments and Future Plans
2.22 Infogix
2.22.1 Infogix Details
2.22.2 Infogix Major Business
2.22.3 Infogix Data Wrangling Product and Solutions
2.22.4 Infogix Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.22.5 Infogix Recent Developments and Future Plans
2.23 Zaloni
2.23.1 Zaloni Details
2.23.2 Zaloni Major Business
2.23.3 Zaloni Data Wrangling Product and Solutions
2.23.4 Zaloni Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.23.5 Zaloni Recent Developments and Future Plans
2.24 Impetus
2.24.1 Impetus Details
2.24.2 Impetus Major Business
2.24.3 Impetus Data Wrangling Product and Solutions
2.24.4 Impetus Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.24.5 Impetus Recent Developments and Future Plans
2.25 Ideata Analytics
2.25.1 Ideata Analytics Details
2.25.2 Ideata Analytics Major Business
2.25.3 Ideata Analytics Data Wrangling Product and Solutions
2.25.4 Ideata Analytics Data Wrangling Revenue, Gross Margin and Market Share (2017-2022)
2.25.5 Ideata Analytics Recent Developments and Future Plans
3 Market Competition, by Players
3.1 Global Data Wrangling Revenue and Share by Players (2017-2022)
3.2 Market Concentration Rate
3.2.1 Top 3 Data Wrangling Players Market Share
3.2.2 Top 10 Data Wrangling Players Market Share
3.2.3 Market Competition Trend
3.3 Data Wrangling Players Head Office, Products and Services Provided
3.4 Mergers & Acquisitions
3.5 New Entrants and Expansion Plans
4 Market Size Segment by Type
4.1 Global Data Wrangling Revenue and Market Share by Type (2016-2021)
4.2 Global Data Wrangling Market Forecast by Type (2021-2026)
5 Market Size Segment by Application
5.1 Global Data Wrangling Revenue Market Share by Application (2016-2021)
5.2 Data Wrangling Market Forecast by Application (2021-2026)
6 North America by Country, by Type, and by Application
6.1 North America Data Wrangling Revenue by Type (2017-2032)
6.2 North America Data Wrangling Revenue by Application (2017-2032)
6.3 North America Data Wrangling Market Size by Country
6.3.1 North America Data Wrangling Revenue by Country (2017-2032)
6.3.2 United States Data Wrangling Market Size and Forecast (2017-2032)
6.3.3 Canada Data Wrangling Market Size and Forecast (2017-2032)
6.3.4 Mexico Data Wrangling Market Size and Forecast (2017-2032)
7 Europe by Country, by Type, and by Application
7.1 Europe Data Wrangling Revenue by Type (2017-2032)
7.2 Europe Data Wrangling Revenue by Application (2017-2032)
7.3 Europe Data Wrangling Market Size by Country
7.3.1 Europe Data Wrangling Revenue by Country (2017-2032)
7.3.2 Germany Data Wrangling Market Size and Forecast (2017-2032)
7.3.3 France Data Wrangling Market Size and Forecast (2017-2032)
7.3.4 United Kingdom Data Wrangling Market Size and Forecast (2017-2032)
7.3.5 Russia Data Wrangling Market Size and Forecast (2017-2032)
7.3.6 Italy Data Wrangling Market Size and Forecast (2017-2032)
8 Asia-Pacific by Region, by Type, and by Application
8.1 Asia-Pacific Data Wrangling Revenue by Type (2017-2032)
8.2 Asia-Pacific Data Wrangling Revenue by Application (2017-2032)
8.3 Asia-Pacific Data Wrangling Market Size by Region
8.3.1 Asia-Pacific Data Wrangling Revenue by Region (2017-2032)
8.3.2 China Data Wrangling Market Size and Forecast (2017-2032)
8.3.3 Japan Data Wrangling Market Size and Forecast (2017-2032)
8.3.4 South Korea Data Wrangling Market Size and Forecast (2017-2032)
8.3.5 India Data Wrangling Market Size and Forecast (2017-2032)
8.3.6 Southeast Asia Data Wrangling Market Size and Forecast (2017-2032)
8.3.7 Australia Data Wrangling Market Size and Forecast (2017-2032)
9 South America by Country, by Type, and by Application
9.1 South America Data Wrangling Revenue by Type (2017-2032)
9.2 South America Data Wrangling Revenue by Application (2017-2032)
9.3 South America Data Wrangling Market Size by Country
9.3.1 South America Data Wrangling Revenue by Country (2017-2032)
9.3.2 Brazil Data Wrangling Market Size and Forecast (2017-2032)
9.3.3 Argentina Data Wrangling Market Size and Forecast (2017-2032)
10 Middle East & Africa by Country, by Type, and by Application
10.1 Middle East & Africa Data Wrangling Revenue by Type (2017-2032)
10.2 Middle East & Africa Data Wrangling Revenue by Application (2017-2032)
10.3 Middle East & Africa Data Wrangling Market Size by Country
10.3.1 Middle East & Africa Data Wrangling Revenue by Country (2017-2032)
10.3.2 Turkey Data Wrangling Market Size and Forecast (2017-2032)
10.3.3 Saudi Arabia Data Wrangling Market Size and Forecast (2017-2032)
10.3.4 UAE Data Wrangling Market Size and Forecast (2017-2032)
11 Research Findings and Conclusion
12 Appendix
12.1 Methodology
12.2 Research Process and Data Source
12.3 Disclaimer
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Case Study- Automotive Sector
One of the key manufacturers of automotive had plans to invest in electric utility vehicles. The electric cars and associated markets being a of evolving nature, the automotive client approached Straits Research for a detailed insight on the market forecasts. The client specifically asked for competitive analysis, regulatory framework, regional prospects studied under the influence of drivers, challenges, opportunities, and pricing in terms of revenue and sales (million units).
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Conclusion
The report aided the client in understanding the market trends, including country-level business scenarios, consumer behavior, and trends in 50 countries. The report also provided financial insights of crucial players and detailed market estimations and forecasts till 2028.
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