Data Analytics Outsourcing Market by Type (descriptive, predictive, and prescriptive), Application (CRM Analytics, supply chain analytics, other), Industry (automotive, manufacturing, BFSI, Other), and Region (North America, Europe, Asia Pacific, Middle East, and Africa, and South America), Global Forecast 2020 to 2030

The large amount of structured and unstructured data being generated is providing new opportunities to the global data analytics outsourcing market.

The global Data Analytics Outsourcing market worth USD 107.9 billion by 2030, growing at a CAGR of 34.1%

Covid-19 Impact & Market Status

The COVID-19 situation had a severe impact on most of the industrial sectors and business companies. Due to lockdown, most of the companies had to forcefully stop their work as there was a lack of infrastructure, transportation, laborers, etc. Despite all these factors, the data analytics outsourcing market took a positive shift during the COVID-19 period because of many factors. The main factor was that this whole process was online where the related authorities can work from home. Other than this, the data analytics outsourcing market helped other sectors like media and entertainment, financial sector, healthcare, etc. to take suitable steps for further development by providing data insights via predictive analytics.

In this way, the market value of the global data outsourcing market increased as it provided precise analysis results and helped other sectors to grow and develop.

The rising production, preprocessing, and analysis of digital data requires highly advanced tools and techniques.

The market has transformed from manual data to digital data with the growth and development of the IT sector enabling most of the industries to do their work in online mode. With the generation of digital data, there is an increased demand for sophisticated tools and techniques that will help organizations to draw insights from this data by drawing suitable patterns and relationships. For this, various machine learning and artificial intelligence algorithms are required so that the data can be processed and proper insights can be drawn from it. This plays an important role when it comes to predictive analytics that would help an organization to take proper steps and actions to ensure timely and quality delivery of the final product.

Apart from selecting a suitable algorithm, there is an immediate requirement for highly advanced data analysis tools and techniques that will help the analytical team to process the data efficiently. In this way, a potential organization can handle unstructured data that is rapidly growing in the market and has the most informative details.

The increasing advancement in technologies like big data analytics and artificial intelligence are driving the global data analytics outsourcing market.

The number of industries is growing at a rapid rate and this increases the amount of data generated by these organizations. There is an increase in the number of online users who use one or more online platforms for work or entertainment. This increase in the number of online platforms and users is increasing the total amount of generated data that needs to be classified and processed.

Data generation and management are crucial tasks when it comes to the IT industries and business companies because these organizations are highly dependent on data for future insights and planning their goals and market strategy. The whole market is dependent on data for its growth and development as it provides information on various sectors. With quality data, the information generated can be drawn into valuable insights that would help various potential organizations o take required measures for product development or maintenance. The main source of data are the customers who use the products and provide feedback to the production companies.

Apart from the data generated via feedback, there are many other sources of data like company generated, product-related metadata, and much more. There is a requirement for proper data preprocessing techniques so that this data can be used for further processing. After pre[rocessing, this data can be given as input to various machine learning algorithms depending on the required output type. The processed data will serve as the information to the organization that will provide insights to the organization. This all comes with proper data analytical skills and tools. Hence, knowledge of big data analytics is a must to work with data analytics.

Currently, digital data has taken over the entire market and various social media platforms that generate a huge amount of data like WhatsApp, Instagram, LinkedIn, and much more. The amount of digital media usage is increasing as people prefer online modes of communication and meet up. Hence, we are pilled up with a huge amount of unstructured data that needs proper classification, filtering, and processing. This is a difficult task as unstructured data requires complex machine learning algorithms for their processing and result generation.

 There is high demand for predictive modeling techniques that will provide the most suitable analysis and option for the development of a company. For this, data analysis is very important as it helps in predictive, prescriptive, and descriptive analytics of the company project. This gives a fine description of the factors that will influence the development and related stages of the project and also provides priority order of these factors. In this way, a company can take all the necessary actions on time and be prepared to handle any risk that might impact its growth rate.

Simultaneously, the marketing of the source and information is equally important as it helps to highlight the product scope and features. Today many e-commerce platforms and social media sites are highly acceptable for this purpose as they help to reach a huge audience. Most people use social media platforms, hence, it is easy to approach them via these platforms. These platforms support media and marketing, hence, data analytics outsourcing becomes easy and efficient as it gains recognition and importance. There are many other advantages of the data analytics outsourcing market that include modeling structures, drawing data patterns, boosting performance, and much more.

The implementation of a data analytics platform is a difficult task because a proper machine learning model needs to be selected for unstructured data that comes in randomly and hence, there is no specified model until unstructured data is not classified properly. Many potential companies are doing their best to solve this challenge by developing various software platforms for precise data structuring, modeling, and categorization that would help in the categorization of unstructured data effectively and efficiently.

The major players of the global data analytics outsourcing market are IBM Corp., Accenture PLC, Genpact Ltd., Capgemini SE, Mu Sigma Inc., Fractal Analytics, Wipro Ltd., Opera Solution LLC, TCS, ZS Associates, Electrifai LLC, Trianz, and Cognizant Technology Solutions Corp.

Latest Innovations in the Global Data Analytics Outsourcing Market: a Snapshot

• Mu Sigma, Accenture, and many other major companies are trying their best to increase the overall CAGR of the data analytics outsourcing market by the end of the forecast period.

Data Analytics Outsourcing Market Scope

Key Segments of the Global Data Analytics Outsourcing Market

Type Overview (USD Billion)

• Descriptive
• Predictive
• Prescriptive

Application Overview, (USD Billion)

• CRM Analytics
• Supply Chain Analytics
• Other

End-User Industry Overview, (USD Billion)

• Automotive
• Manufacturing
• BFSI
• Other

Regional Overview, (USD Billion)

North America

• U.S
• Canada

Europe

• Germany
• France
• UK
• Rest of Europe

Asia Pacific

• China
• India
• Japan
• Rest of Asia Pacific

South America

• Mexico
• Brazil
• Rest of South America

The Middle East and South Africa