PUBLISHER: Stratistics Market Research Consulting | PRODUCT CODE: 1351059
PUBLISHER: Stratistics Market Research Consulting | PRODUCT CODE: 1351059
According to Stratistics MRC, the Global Data Pipeline Tools Market is accounted for $8.4 billion in 2023 and is expected to reach $34.5 billion by 2030 growing at a CAGR of 22.3% during the forecast period. Data pipelines are specialized solutions for analytics, data science, artificial intelligence (AI), and machine learning that allow data from one system to move to and be used in another system. A data pipeline's fundamental function is to take data from the source, apply transformation and processing rules, and then deliver the data where it is needed. Data is sent from a main place where it is gathered or stored to a secondary location where it is merged with other data inputs via a data pipeline. Due to security and privacy concerns, many firms put data on an on-premises system. These businesses occasionally need data pipeline technologies as well.
According to research by Software AG, there are 7.8 billion individuals in the globe, and each one generates 2.5 quintillion bytes of data each day. Data pipelines turn raw information into data that is suitable for insights, applications, machine learning, and artificial intelligence (AI) systems.
Data should be accessible at all times to businesses that require it. Traditional pipelines demand that many groups within a business have access to data. Outages and disturbances may happen concurrently. Instead of requiring days or weeks, organizations must grow data storage and processing capabilities rapidly and inexpensively. Legacy data pipelines are frequently inflexible, precise, sluggish, challenging to debug, and difficult to grow. A lot of time, money, and effort are needed for production and management. Additionally, it affects peak company operations since many procedures are often incompatible. As a result, cutting-edge pipeline technologies offer instant cloud flexibility at a fraction of the cost of conventional systems.
The main engine underlying decision-making and business operations in data-driven organizations is data. Particularly during occasions like infrastructure upgrades, mergers and acquisitions, restructurings, and migrations, data might become inaccurate or incomplete. Customer complaints to subpar analytical results are just a few of the ways that a lack of data access may hurt a firm. The integrity of these pipelines is something that data engineers spend a substantial amount of effort upgrading, maintaining, and verifying. Thus, the market is being hampered by the above issues.
Anytime a business needs data, they must be able to access it. When several organizations in a business demand data access at once, traditional pipelines may have shutdowns and interruptions. The business should be able to swiftly and economically grow its data storage and processing capacity, rather than needing many days or weeks. Legacy data pipelines typically display rigidity and slowness, include errors, are challenging to troubleshoot, and are challenging to expand. They need a significant outlay of time, money, and effort during both their creation and management. Additionally, they typically are unable to operate many processes concurrently, which hurt the company's performance during busy times. Advanced data pipelines offer the immediate flexibility of the conventional systems at a fraction of the cost which create wide range of opportunities for the growth of the market.
Organizations must use cutting-edge data pipeline technology to gather and integrate massive amounts of data from various internal and external data sources, merge the information silos, and provide valuable business intelligence. Because of their poor knowledge and abilities, the workforce is unable to adopt data pipeline solutions. Because businesses frequently function in silos, a data pipeline is increasingly necessary to gain a thorough understanding of a variety of applications and industries. Numerous studies and publications assert that polls routinely show that employees in organizations have insufficient knowledge and skills which hinders the market growth.
The COVID-19 outbreak had a favorable effect on the market for data pipeline products. A vast amount of organized, semi-structured, and unstructured data in the forms of video, audio, emails, and other internet platforms was produced as the majority of people began to adopt the work-from-home lifestyle. The technologies are also growing in popularity as data corruption events increase globally. The amount of data produced has increased dramatically, particularly since the COVID-19 pandemic. Tools are therefore designed to safeguard data flow and lower the chance of data corruption. As a result, the aforementioned reasons accelerated the expansion of the data pipeline industry.
The streaming data pipeline segment is estimated to have a lucrative growth, due to the point of use as it is being generated. Data lakes, data warehouses, messaging systems, and data streams may all be published to using streaming data pipelines. By streaming data from on-premises systems to cloud data warehouses for real-time analytics, ML modelling, reporting, and producing BI dashboards, streaming data pipelines assist enterprises in gaining insightful information. The flexibility, agility, and cost-effectiveness of processing and storage are all benefits of moving workloads to the cloud.
The small and medium enterprises segment is anticipated to witness the highest CAGR growth during the forecast period, due to the widespread presence of small and medium-sized businesses in nations like India, China, the United States, France, and Italy. In order to develop in their growth plan and successfully compete with their larger competitors, SMEs can utilize data to make crucial business choices. Small and medium-sized businesses (SMEs), particularly in emerging and transitional countries, are a potent force behind industrial growth and, consequently, overall economic development. By utilizing data insights, the SME sector is dispelling the myth that giant corporations are the only ones that can utilize data extensively.
Given that major industry players like Microsoft Corporation, IBM Corporation, and AWS, Inc. are believed to be present in this region and play a significant role in determining the direction of the global market, North America is predicted to hold the largest market share during the forecast period. The primary variables influencing the North American industry are the quick transfer of large data volumes and the subsequent development of trustworthy data. Data pipeline systems are used by a variety of industrial and commercial organizations in the United States and Canada to streamline operations, lessen data security, and boost regional economic growth.
Europe is projected to have the highest CAGR over the forecast period, due to rising innovation and the emergence of new technologies like artificial intelligence (AI) and machine learning (ML), In the U.K. and France, there is an increasing requirement for data pipelines and integration due to the growing desire to integrate various data sets from various sources via a single cloud, which is anticipated to drive the market over the projected period.
Some of the key players profiled in the Data Pipeline Tools Market include: Amazon Web Services, Inc., Actian Corporation, Blendo, Google LLC, Hevo Data Inc., IBM, Informatica, Inc, K2VIEW, Microsoft Corporation, Oracle, Precisely Holdings, LLC, SAP SE, Skyvia, Snap Logic Inc., Snowflake, Inc., Software AG and Tibco Software, Inc.
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Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.