Data Wrangling Market by Business Function, Component, Deployment Model, Organization Size, Industry Vertical, and Region - Global Forecast to 2023

DUBLIN, May 17, 2018 /PRNewswire/ --

The "Data Wrangling Market by Business Function (Marketing and Sales, Finance, Operations, HR, and Legal), Component (Tools and Services), Deployment Model, Organization Size, Industry Vertical, and Region - Global Forecast to 2023" report has been added to ResearchAndMarkets.com's offering.

The global data wrangling market is expected to grow from USD 1.29 Billion in 2018 to USD 3.18 Billion by 2023, at a Compound Annual Growth Rate (CAGR) of 19.7% during the forecast period.

A rapid increase of data volumes across industry verticals is triggering organizations to incorporate advanced analytics algorithms in their systems to gain substantial insights that help them to stay competitive. The proliferation of data across verticals is one of the main growth for the market.

The report provides detailed insights into the global data wrangling market based on business functions, components, deployment models, organization sizes, verticals, and regions. Among the component, data wrangling tools are expected to have the largest market size during the forecast period. With the proliferation of data, the data wrangling tools are expected to be adopted at a rapid pace, as they are a precursor to the analytics workflows.

A typical data wrangling tool encompasses functions, such as reformatting, de-duping, filtering, and cleaning data, so that proper analysis could be done. Moreover, data wrangling tools offer the self-service data preparation model that helps organizations to clean the data sets by themselves without involving data scientists. This has effectively empowered the executives to gain business insights without the intervention of IT teams.

The on-demand deployment model is expected to have a high adoption rate as compared to the on-premises deployment model. By using cloud-based deployment, organizations can avoid a large amount of cost pertaining to hardware, software, data, maintenance cost, and staff. The BFSI vertical is expected to hold the largest market size during the forecast period. Data wrangling tool leverages various capabilities specifically for banking and financial institutes, such as data discovery from numerus sources and formats, integration with existing tools, fraud detection, risk management, and higher operational productivity.

The report covers all the major aspects of the data wrangling market and provides an in-depth analysis in North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. The market in North America is expected to hold the largest market share. The APAC region is projected to provide significant opportunities to vendors in the market and is expected to grow at the highest CAGR during the forecast period. APAC, being a manufacturing hub, is expected to adopt the data wrangling substantially, to remain cost efficient and export high-quality goods to other countries.

Reluctance to shift from traditional ETL tools to advanced automated tools is the major restraining factor for the growth of the market. Lack of awareness of data wrangling tools among SMEs, and concerns regarding data quality are the major challenges for the data wrangling market growth.

Most of the vendors in the data wrangling market have adopted various growth strategies, such as acquisitions, agreements, collaborations and partnerships, new product launches, product upgradations, and expansions, to expand their client base and enhance the customer experience. For instance, in March 2017, Trifacta collaborated with Google to create Google Cloud Dataprep. This solution would enable Google to help enterprises shift their data to the cloud, where in Trifacta would help them resolving their data wrangling challenges.

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Attractive Opportunities in the Data Wrangling Market
4.2 Market By Application and Region
4.3 Market Share, By Region
4.4 Life Cycle Analysis, By Region, 2018

5 Market Overview
5.1 Introduction
5.1.1 Drivers
5.1.1.1 Increasing Volume and Velocity of Data
5.1.1.2 Advancements in AI and Ml Technologies
5.1.2 Restraints
5.1.2.1 Reluctance to Shift From Traditional ETL Tools to Advanced Automated Tools
5.1.3 Opportunities
5.1.3.1 Increasing Regulatory Pressure
5.1.3.2 Growth of Edge Computing
5.1.4 Challenges
5.1.4.1 Lack of Awareness of Data Wrangling Tools Among SMEs
5.1.4.2 Concerns Regarding Data Quality
5.2 Data Types
5.2.1 Customer Data
5.2.2 Product Data
5.2.3 Finance Data
5.2.4 Compliance Data
5.2.5 Supplier Data
5.3 Data Wrangling: Use Cases
5.3.1 Use Case #1: Unification of Data
5.3.2 Use Case #2: Data Wrangling and Analytics to Obtain Customer Insights
5.3.3 Use Case #3: Data Integration Saved Fortune 50 Telecom Giant Millions in Call Center Interactions
5.3.4 Use Case #4: Onedot Made IT Simple for Zageno to Integrate Unstructured Data and Deliver the Best Possible Search Results

6 Data Wrangling Market, By Business Function
6.1 Introduction
6.2 Finance
6.3 Marketing and Sales
6.4 Operations
6.5 Human Resources
6.6 Legal

7 Data Wrangling Market, By Component
7.1 Introduction
7.2 Tools
7.3 Services
7.3.1 Managed Services
7.3.2 Professional Services
7.3.2.1 Consulting Services
7.3.2.2 Support and Maintenance Services

8 Data Wrangling Market, By Deployment Model
8.1 Introduction
8.2 On-Premises
8.3 Cloud

9 Data Wrangling Market, By Organization Size
9.1 Introduction
9.2 Large Enterprises
9.3 Small and Medium-Sized Enterprises

10 Data Wrangling Market, By Industry Vertical
10.1 Introduction
10.2 Banking, Financial Services, and Insurance
10.3 Government and Public Sector
10.4 Healthcare and Life Sciences
10.5 Retail and Ecommerce
10.6 Travel and Hospitality
10.7 Automotive and Transportation
10.8 Energy and Utilities
10.9 Telecommunication and IT
10.10 Manufacturing
10.11 Others

11 Data Wrangling Market, By Region

12 Competitive Landscape
12.1 Overview
12.2 Prominent Players in the Data Wrangling Market
12.3 Competitive Scenario

13 Company Profiles
13.1 IBM
13.2 Oracle
13.3 SAS Institute
13.4 Trifacta
13.5 Datawatch
13.6 Talend
13.7 Alteryx
13.8 Dataiku
13.9 TIBCO Software
13.10 Paxata
13.11 Informatica
13.12 Hitachi Vantara
13.13 Teradata
13.14 IRI, the Cosort Company
13.15 Brillio
13.16 Onedot
13.17 TMMData
13.18 Datameer
13.19 Cooladata
13.20 Unifi Software
13.21 Rapid Insight
13.22 Infogix
13.23 Zaloni
13.24 Impetus
13.25 Ideata Analytics

For more information about this report visit https://www.researchandmarkets.com/research/k227jp/data_wrangling?w=5

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