Dataops Platform Market
DataOps Platform Market Forecasts to 2028 - Global Analysis By Offering (Platform and Services), By Type (Lean Manufacturing, Devops, Agile Development and Other Types), By Deployment Mode, By Application, By End User and By Geography
|
Years Covered |
2020-2028 |
|
Estimated Year Value (2022) |
US $1.21 BN |
|
Projected Year Value (2028) |
US $4.09 BN |
|
CAGR (2022 - 2028) |
22.5% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
North America |
|
Highest Growing Market |
Asia Pacific |
According to Stratistics MRC, the Global DataOps Platform Market is accounted for $1.21 billion in 2022 and is expected to reach $4.09 billion by 2028 growing at a CAGR of 22.5% during the forecast period. The objective of the DataOps platform is to increase the quality, speed, and business value of data-related activities by combining agile approaches, automation, and collaboration across data professionals. This comprehensive approach to data management goes beyond technology. The goal of the DataOps platform is to improve communication, integration, and automation of data flow between data sources and consumers. This is a radical departure from traditional DevOps.
Market Dynamics:
Driver:
Increased data complexity and accelerating data volumes
Organizations are having to manage ever-increasing amounts of data from many sources, in both structured and unstructured formats, as well as real-time data streams. The quantity, velocity, and diversity of data frequently make it challenging for traditional data management techniques to keep up, which causes inefficiencies, mistakes, and delays in data processing and analysis. Organizations may integrate, process, and analyze data effectively with the help of DataOps platforms, which provide the required tools and technology to handle this complexity. Platforms for data operations can enable both batch processing and real-time data streaming.
Restraint:
Data privacy and security concerns
Sensitive data must be protected, and organizations must abide by data privacy laws as awareness of this fact grows. Data that is sensitive and private is handled by DataOps platforms. The maintenance of robust security measures while ensuring data privacy and compliance with laws (such as GDPR or CCPA) can be a difficult task. The concerns raised in this instance must be addressed, and strong security mechanisms are required to exist. As a result of the integration of numerous tools and systems used by DataOps platforms, there may be more attack surfaces and possible weaknesses. If the DataOps platform is not properly secured, organizations can be concerned about the possibility of data breaches and their potential impact on data privacy.
Opportunity:
Need to bridge gap between data engineers and data analysts
Additionally, DataOps arose as an approach to bridging the gap between data engineers and data analysts, who have various priorities and goals. Data engineering, data science, business analysis, and IT operations teams, as well as these teams' cross-functional alignment, are all supported by data operations platforms. DataOps systems make it possible for teams to collaborate, exchange knowledge, and adhere to uniform procedures, which boosts output and productivity by giving every individual access to the same tools and processes. Furthermore, DataOps platforms promote collaboration and cross-functional alignment, which reduces barriers between teams, promotes knowledge sharing, and improves the overall efficacy and efficiency of data operations. Organizations can take advantage of the team's aggregate knowledge in this collaborative environment to spur innovation and provide high-quality data-driven insights.
Threat:
Need to mitigate the challenges of skilled talent shortage
The lack of highly skilled workers is one of the major issues facing the market for data operations platforms. Data engineering, data science, software development, and operations experts are needed for DataOps platforms. A talent gap has developed because of the industry's significant lack of experts with these particular talents. As a result, businesses are having trouble finding qualified individuals to create, launch, and maintain DataOps platforms. The speed at which technology is developing makes this talent deficit increasingly severe. For existing team members to adjust to the DataOps strategy, further training or retraining may be required. Additionally, primarily data scientists and machine learning engineers are affected by the scarcity of qualified talent.
Covid-19 Impact:
The COVID-19 outbreak has increased the dependence of firms on remote labor and digital technologies, necessitating higher demands for digital transformation. DataOps tools are becoming increasingly necessary to help firms manage their data more efficiently. One of COVID-19's most significant consequences on the market for DataOps platforms is an increase in demand for cloud-based solutions. As remote work becomes the new norm, businesses are looking for solutions to access their data from anywhere. Cloud-based DataOps solutions, which let teams collaborate and work remotely on data pipelines, provide this flexibility.
The platform segment is expected to be the largest during the forecast period
Platform segment commanded the largest market share throughout the domination period. DataOps platforms are made to simplify data management and analysis procedures, enabling businesses to increase operational effectiveness over time. The market for DataOps platforms offers significant, lucrative potential due to the growing volume of data that enterprises must manage, process, and analyze. These elements are augmenting the segments growth.
The cloud segment is expected to have the highest CAGR during the forecast period
Cloud segment is projected to have profitable growth during the estimation period. Depending on the particular needs of a business, the cloud segment of the deployment method plays a vital role in setting up the necessary IT infrastructure for managing the IT ecosystem in the market for DataOps platforms. However, the popularity of cloud deployment mode in the market for DataOps platforms is driven by the opportunity to have more control over data location and accessibility across a network.
Region with largest share:
North America region is estimated to have the largest share over the forecasted period because of its thriving IT sector and continuous commitment to innovation and digital transformation. It has also become a leader in implementing DataOps systems. Major nations like the United States and Canada are included in the region, with the United States driving the adoption of DataOps due to the presence of multiple internationally recognized technology enterprises. The region's unwavering focus on innovation and digital transformation is the primary factor behind the widespread use of DataOps platforms in North America.
Region with highest CAGR:
Because big data is rapidly growing, cloud computing is widely used, artificial intelligence is advancing, and DataOps platforms are being used rapidly, the Asia-Pacific region is expected to have lucrative growth over the extrapolated period. Businesses are looking for automated solutions to manage their data effectively as a result of the unprecedented growth in data volumes in an effort to reduce costs, enhance operational efficiency, and improve data quality. Moreover, in the Asia-Pacific area, the DataOps platform business environment is broad and continuously changing. It includes a wide range of technology manufacturers, service providers, and consulting companies that offer complete end-to-end data management solutions to enterprises of all kinds.
Key players in the market
Some of the key players in DataOps Platform market include Accenture , Atlan, AWS, Databricks, Dataiku, Datakitchen, Fosfor, Hitachi Vantara, IBM, Informatica, Microsoft, Oracle, SAS Institute, Teradata and Wipro.
Key Developments:
In April 2023, DataOps.live partnered with AWS and joined the AWS Partner Network on the Software Path and obtained the AWS Qualified Software Certification after successfully completing the AWS Foundational Technical Review.
In March 2023, Blechwarenfabrik Limburg GmbH collaborated with Hitachi Vantara and adopted its Lumada DataOps Platform which includes Pentaho, to achieve real-time, standardized, integrated data analysis for increased sustainability and accelerated production.
In February 2023, Informatica announced the launch of Cloud Data Integration-Free and PayGo, which is the only free cloud data loading, integration, and ETL/ELT service. This new service targets data practitioners and non-technical users such as in marketing, sales, and revenue operations teams to build data pipelines within minutes.
In November 2022, Wipro had announced the launch of Data Intelligence Suite speeding up the cloud modernization and data monetization, focused on modernizing data estates, including data stores, pipelines, and visualizations, running on Amazon Web Services. It also provides a dependable and safe way to migrate from existing platforms and fragmented legacy systems to the cloud.
In June 2022, Teradata announced the general availability and integration of the Teradata Vantage multi-cloud data and analytics platform with Amazon SageMaker. It enables organizations to widely employ advanced analytics to fully leverage their data.
Offerings Covered:
• Platform
• Services
Types Covered:
• Lean Manufacturing
• Devops
• Agile Development
• Other Types
Deployment Modes Covered:
• On Premises
• Cloud
Applications Covered:
• Banking, Financial Services and Insurance (BFSI)
• Healthcare & Life Sciences
• Retail & E Commerce
• Manufacturing
• Other Applications
End Users Covered:
• Government & Defense
• Telecommunications
• Transportation & Logistics
• IT/ITES
• Media & Entertainment
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Application Analysis
3.7 End User Analysis
3.8 Emerging Markets
3.9 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global DataOps Platform Market, By Offering
5.1 Introduction
5.2 Platform
5.2.1 Master Data Management
5.2.2 Data Governance
5.2.3 Data Quality
5.2.4 Data Integration
5.2.5 Data Visualization
5.2.6 Collaboration
5.2.7 Automation
5.2.8 Data Analytics
5.2.9 Other Platforms
5.3 Services
5.3.1 Professional Services
5.3.1.1 Deployment & Integration
5.3.1.2 Consulting Services
5.3.1.3 Training, Support & Maintenance
5.3.2 Managed Services
6 Global DataOps Platform Market, By Type
6.1 Introduction
6.2 Lean Manufacturing
6.3 Devops
6.4 Agile Development
6.5 Other Types
7 Global DataOps Platform Market, By Deployment Mode
7.1 Introduction
7.2 On Premises
7.3 Cloud
7.3.1 Hybrid Cloud
7.3.2 Private Cloud
7.3.3 Public Cloud
8 Global DataOps Platform Market, By Application
8.1 Introduction
8.2 Banking, Financial Services and Insurance (BFSI)
8.2.1 Financial Data Optimization
8.2.2 Investment Analysis
8.2.3 Credit Scoring
8.2.4 Fradulent Transactions Identification
8.2.5 Other Banking, Financial Services and Insurance (BFSI) Applications
8.3 Healthcare & Life Sciences
8.3.1 Drug Discovery
8.3.2 Precision Medicine
8.3.3 Electronic Health Record
8.3.4 Clinical Trial Management
8.3.5 Other Healthcare & Life Sciences
8.4 Retail & E Commerce
8.4.1 Demand Forecasting
8.4.2 Inventory Management
8.4.3 Personalized Product Recommendation
8.4.4 Pricing Optimization
8.4.5 Other Retail & E Commerce Applications
8.5 Manufacturing
8.5.1 Product Planning and Scheduling
8.5.2 Product Quality Control
8.5.3 Supply Chain Optimization
8.5.4 Predictive Maintenance
8.5.5 Other Manufacturing Applications
8.6 Other Applications
9 Global DataOps Platform Market, By End User
9.1 Introduction
9.2 Government & Defense
9.2.1 Geospatial Analysis
9.2.2 Emergency Response
9.2.3 Intelligent Gathering and Analysis
9.2.4 Public Safety
9.3 Telecommunications
9.3.1 Network Capacity Planning
9.3.2 Real Time Analytics
9.3.3 Network Performance
9.3.4 Network Security
9.4 Transportation & Logistics
9.4.1 Fleet Management
9.4.2 Real Time Tracking
9.4.3 Route Optimization
9.5 IT/ITES
9.5.1 Incident Management
9.5.2 Application Performance Management
9.5.3 IT Infrastructure Management
9.5.4 Software Development
9.6 Media & Entertainment
9.6.1 Audience Segmentation
9.6.2 Content Optimization
9.6.3 AD Targeting
9.7 Other End Users
10 Global DataOps Platform Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa
11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies
12 Company Profiling
12.1 Accenture
12.2 Atlan
12.3 AWS
12.4 Databricks
12.5 Dataiku
12.6 Datakitchen
12.7 Fosfor
12.8 Hitachi Vantara
12.9 IBM
12.10 Informatica
12.11 Microsoft
12.12 Oracle
12.13 SAS Institute
12.14 Teradata
12.15 Wipro
List of Tables
1 Global DataOps Platform Market Outlook, By Region (2020-2028) ($MN)
2 Global DataOps Platform Market Outlook, By Offering (2020-2028) ($MN)
3 Global DataOps Platform Market Outlook, By Platform (2020-2028) ($MN)
4 Global DataOps Platform Market Outlook, By Master Data Management (2020-2028) ($MN)
5 Global DataOps Platform Market Outlook, By Data Governance (2020-2028) ($MN)
6 Global DataOps Platform Market Outlook, By Data Quality (2020-2028) ($MN)
7 Global DataOps Platform Market Outlook, By Data Integration (2020-2028) ($MN)
8 Global DataOps Platform Market Outlook, By Data Visualization (2020-2028) ($MN)
9 Global DataOps Platform Market Outlook, By Collaboration (2020-2028) ($MN)
10 Global DataOps Platform Market Outlook, By Automation (2020-2028) ($MN)
11 Global DataOps Platform Market Outlook, By Data Analytics (2020-2028) ($MN)
12 Global DataOps Platform Market Outlook, By Other Platforms (2020-2028) ($MN)
13 Global DataOps Platform Market Outlook, By Services (2020-2028) ($MN)
14 Global DataOps Platform Market Outlook, By Professional Services (2020-2028) ($MN)
15 Global DataOps Platform Market Outlook, By Managed Services (2020-2028) ($MN)
16 Global DataOps Platform Market Outlook, By Type (2020-2028) ($MN)
17 Global DataOps Platform Market Outlook, By Lean Manufacturing (2020-2028) ($MN)
18 Global DataOps Platform Market Outlook, By Devops (2020-2028) ($MN)
19 Global DataOps Platform Market Outlook, By Agile Development (2020-2028) ($MN)
20 Global DataOps Platform Market Outlook, By Other Types (2020-2028) ($MN)
21 Global DataOps Platform Market Outlook, By Deployment Mode (2020-2028) ($MN)
22 Global DataOps Platform Market Outlook, By On Premises (2020-2028) ($MN)
23 Global DataOps Platform Market Outlook, By Cloud (2020-2028) ($MN)
24 Global DataOps Platform Market Outlook, By Hybrid Cloud (2020-2028) ($MN)
25 Global DataOps Platform Market Outlook, By Private Cloud (2020-2028) ($MN)
26 Global DataOps Platform Market Outlook, By Public Cloud (2020-2028) ($MN)
27 Global DataOps Platform Market Outlook, By Application (2020-2028) ($MN)
28 Global DataOps Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
29 Global DataOps Platform Market Outlook, By Financial Data Optimization (2020-2028) ($MN)
30 Global DataOps Platform Market Outlook, By Investment Analysis (2020-2028) ($MN)
31 Global DataOps Platform Market Outlook, By Credit Scoring (2020-2028) ($MN)
32 Global DataOps Platform Market Outlook, By Fradulent Transactions Identification (2020-2028) ($MN)
33 Global DataOps Platform Market Outlook, By Other Banking, Financial Services and Insurance (BFSI) Applications (2020-2028) ($MN)
34 Global DataOps Platform Market Outlook, By Healthcare & Life Sciences (2020-2028) ($MN)
35 Global DataOps Platform Market Outlook, By Drug Discovery (2020-2028) ($MN)
36 Global DataOps Platform Market Outlook, By Precision Medicine (2020-2028) ($MN)
37 Global DataOps Platform Market Outlook, By Electronic Health Record (2020-2028) ($MN)
38 Global DataOps Platform Market Outlook, By Clinical Trial Management (2020-2028) ($MN)
39 Global DataOps Platform Market Outlook, By Other Healthcare & Life Sciences (2020-2028) ($MN)
40 Global DataOps Platform Market Outlook, By Retail & E Commerce (2020-2028) ($MN)
41 Global DataOps Platform Market Outlook, By Demand Forecasting (2020-2028) ($MN)
42 Global DataOps Platform Market Outlook, By Inventory Management (2020-2028) ($MN)
43 Global DataOps Platform Market Outlook, By Personalized Product Recommendation (2020-2028) ($MN)
44 Global DataOps Platform Market Outlook, By Pricing Optimization (2020-2028) ($MN)
45 Global DataOps Platform Market Outlook, By Other Retail & E Commerce Applications (2020-2028) ($MN)
46 Global DataOps Platform Market Outlook, By Manufacturing (2020-2028) ($MN)
47 Global DataOps Platform Market Outlook, By Product Planning and Scheduling (2020-2028) ($MN)
48 Global DataOps Platform Market Outlook, By Product Quality Control (2020-2028) ($MN)
49 Global DataOps Platform Market Outlook, By Supply Chain Optimization (2020-2028) ($MN)
50 Global DataOps Platform Market Outlook, By Predictive Maintenance (2020-2028) ($MN)
51 Global DataOps Platform Market Outlook, By Other Manufacturing Applications (2020-2028) ($MN)
52 Global DataOps Platform Market Outlook, By Other Applications (2020-2028) ($MN)
53 Global DataOps Platform Market Outlook, By End User (2020-2028) ($MN)
54 Global DataOps Platform Market Outlook, By Government & Defense (2020-2028) ($MN)
55 Global DataOps Platform Market Outlook, By Geospatial Analysis (2020-2028) ($MN)
56 Global DataOps Platform Market Outlook, By Emergency Response (2020-2028) ($MN)
57 Global DataOps Platform Market Outlook, By Intelligent Gathering and Analysis (2020-2028) ($MN)
58 Global DataOps Platform Market Outlook, By Public Safety (2020-2028) ($MN)
59 Global DataOps Platform Market Outlook, By Telecommunications (2020-2028) ($MN)
60 Global DataOps Platform Market Outlook, By Network Capacity Planning (2020-2028) ($MN)
61 Global DataOps Platform Market Outlook, By Real Time Analytics (2020-2028) ($MN)
62 Global DataOps Platform Market Outlook, By Network Performance (2020-2028) ($MN)
63 Global DataOps Platform Market Outlook, By Network Security (2020-2028) ($MN)
64 Global DataOps Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
65 Global DataOps Platform Market Outlook, By Fleet Management (2020-2028) ($MN)
66 Global DataOps Platform Market Outlook, By Real Time Tracking (2020-2028) ($MN)
67 Global DataOps Platform Market Outlook, By Route Optimization (2020-2028) ($MN)
68 Global DataOps Platform Market Outlook, By IT/ITES (2020-2028) ($MN)
69 Global DataOps Platform Market Outlook, By Incident Management (2020-2028) ($MN)
70 Global DataOps Platform Market Outlook, By Application Performance Management (2020-2028) ($MN)
71 Global DataOps Platform Market Outlook, By IT Infrastructure Management (2020-2028) ($MN)
72 Global DataOps Platform Market Outlook, By Software Development (2020-2028) ($MN)
73 Global DataOps Platform Market Outlook, By Media & Entertainment (2020-2028) ($MN)
74 Global DataOps Platform Market Outlook, By Audience Segmentation (2020-2028) ($MN)
75 Global DataOps Platform Market Outlook, By Content Optimization (2020-2028) ($MN)
76 Global DataOps Platform Market Outlook, By AD Targeting (2020-2028) ($MN)
77 Global DataOps Platform Market Outlook, By Other End Users (2020-2028) ($MN)
Note: Tables for North America, Europe, Asia Pacific, South America and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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