Growth of Data Wrangling Market is
Estimated to Grow Incredible CAGR
till 2023
BusinessIndustryReports have new report on “Global Data Wrangling Market
2019-2023”. The report provides the newest industry data and industry future
trends. The industry report lists the leading competitors and provides the
insights strategic industry Analysis of the key factors influencing the market.
This Report covers the Major Players data, including: shipment, revenue, gross profit, interview
record, business distribution etc., these data help the consumer know about the competitors’ better
market. This report also covers all the regions and countries of the world, which shows a regional
development status, including market size.
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Data wrangling is defined as a process of mapping or transforming raw data into a valuable one for
different downstream purposes such as analytics. Different types of data problems faced by data
analyzer are inconsistent representations of the same data, missing data, the requirement of human
intervention for data problems, incorrect data, and overly sanitizing data. Visualization is a
technique to identify raw data or data issues. Some of the visual representations are a matrix view,
node-link diagram, and sorted matrix view.
Data wrangling tools would be adopted exponentially with the rise of digitalization in the healthcare
and life sciences vertical. A complete end-to-end digitalization in healthcare would only be possible if
right tools are adopted to clean, de-duplicate, and format the data to investigate and analyze such
datasets.
Geographically, North America is expected to continue to dominate the Data wrangling market
during the forecast period. The region remains the single largest contributor when it comes to the
adoption of data wrangling tools and services. Moreover, growing partnerships, agreements, and
strategic alliances also testify that the region will be at the forefront in the adoption of digital
technologies. APAC is expected to grow at the highest rate in the global data wrangling market
during the forecast period.