Data Wrangling Market is Expected to Grow During Forecast Period, 2024-2028
An increase in data volume
and increasing use of AI and machine learning are driving the global data
wrangling market in the forecast period.
According to
TechSci Research report, “Data Wrangling Market - Global Industry Size,
Share, Trends, Opportunity, and Forecast. 2018–2028,” the global data
wrangling market is predicted to expand over the forecast period of 2024 to 2028
owing to growing use of data manipulation technologies to address cyber risks. Data
wrangling is gaining popularity across the world. The use of data manipulation
technologies to address cyber risks is paving the way for business expansion.
Government authorities in nations such as the United Kingdom, the United
States, Germany, and Singapore are increasing their attention on data
protection rules, which is pushing the adoption rate of data wrangling.
Furthermore, incorporating complex technologies such as machine learning (ML)
and artificial intelligence (AI) into data wrangling tools increases the
overall production and productivity of the organization.
AI and machine
learning are used by the organizations to automatically evaluate sensitive data
behavior while increasing security measures to prevent a data breach and data
loss. With near-real-time data collection, managers can quickly assess the
outcomes and build a speedy feedback loop. The benefits of combining AI and ML
will aid in increasing the global penetration of data wrangling.
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Big data
necessitates data manipulation to give quality information for management
decision making. The need to categorize data is driven by its vast volume and
fast speed. Similarly, machine learning is expected to improve the market for
data wrangling due to its capacity to learn the tags for any type of
information stored in the system. Various firms are also integrating
technologies such as AI and ML to automatically evaluate sensitive data behaviors
and improve security measures to avoid data breaches. These technologies assist
businesses in reducing errors introduced by manual processes or user
intervention, while classifying sensitive data and empowering data wrangling
solutions to leverage continuous learning processes to automatically categorize
data in a more refined and precise manner, based on user-defined rules and
policies. Third-party businesses and government units may considerably improve
the quality of management systems and MDM platforms by offering better and more
complete data, allowing for more accurate decision-making. AI generates recommendations
based on a given collection of data and the build's data connections. Companies
may make more educated judgements when they have thorough and clean data in one
location. Data-Driven Decision-Making (DDDM) is the activity of
gathering data, analyzing it, and making decisions based on information-derived
insights. This technique is diametrically opposed to making conclusions based
on gut instinct, tradition, or theory. Decisions based on data are more
objective, and the influence on metrics can be swiftly assessed. A firm may
boost output by timing the assembly process and recording any delays. Managers
can re-time the process after implementing bottleneck remedies to evaluate if
the change results in time savings. They might also attempt another solution to
achieve the greatest outcomes for production acceleration.
Global
Data Wrangling Market
is segmented based on component,
by deployment model, by enterprise model and by end user, region, and competitive landscape.
Based on Component, the market is
segmented into Tools and Service.
Based on the
Deployment model, the market is segmented into On Cloud, and On Premises. The
cloud sector had the biggest revenue share and is anticipated to maintain its dominance
throughout the projected period.
Based on Enterprise
model, the market is segmented into small-medium enterprise and large enterprise.
Based on End User,
the market is segmented into IT and Telecommunication, Retail and BFSI, In 2022, the BFSI (Banking, Financial Services, and
Insurance) sector was at the forefront of the data wrangling industry, and is
projected to continue leading the market during the forecast period. This is
attributed to the adoption of data wrangling technology by banks, which enables
them to focus on relationships within banking data in order to identify
patterns of behavior that may be indicative of fraudulent activities.
Furthermore, the retail and e-commerce sectors are predicted to increase at a
substantial CAGR during the forecast period, owing to the e-commerce industry's
use of data wrangling technology for offering real-time suggestions to online
customers.
Key market
players in the Global Data Wrangling Market:
- Trifacta Software Inc
- Datawatch
Corporation
- TIBCO Software Inc
- Teradata
Corporation
- Oracle Corporation
- SAS Institute Inc
- Talend SA
- Alteryx Inc
- Paxata Inc
- Hortonworks Inc.
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The global market for Data Wrangling faces
several challenges which includes lack of product knowledge and higher
penetration of older ETL (Extract, Transform, and Load) solutions are limiting
market growth. Furthermore, with the use of various emerging technologies such
as machine learning and big data analytics, data wrangling is utilized to
derive valuable insights from raw data and to address time-sensitive business
scenarios. As a result, organizations lack the necessary functionality for
enterprises to use this technology, hampering market growth. Furthermore, a
lack of understanding of data wrangling techniques among organizations in
emerging markets such as China and India are impeding industry expansion.
Furthermore, the significant costs associated with using wrangle technology
impede industry expansion.
“Data wrangling market
trends include an increase in the volume and velocity of data across
businesses, as well as technology advancements such as AI and machine learning
technologies in data wrangling, which drive market growth. Furthermore, the
expansion of edge computing solutions promotes market development. However, a
reluctance to transition from old ETL tools to advanced automated solutions is
impeding market growth. Furthermore, increased regulatory pressure on
businesses is projected to create significant prospects for market development
in the future.” said, Mr. Karan Chechi, Research Director with TechSci
Research, a research based global management consulting firm.
“Data Wrangling Market - Global Industry Size, Share, Trends,
Opportunity, and Forecast, 2018–2028, Segmented By
Component (Tools and Service), By Deployment Model (On Cloud, On Premises), By
Enterprise Model (Small & Medium-Sized Enterprises,
Large), By End User (IT and Telecommunication, Retail and BFSI), By Region,” has evaluated the future growth potential of Global Data Wrangling
Market and provides statistics & information on market size, structure, and
future market growth. The report intends to provide cutting-edge market
intelligence and help decision makers take sound investment decisions. Besides,
the report also identifies and analyzes the emerging trends along with
essential drivers, challenges, and opportunities in Global Data Wrangling Market.
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