Predictive Learning Market - Global Industry Trend Analysis 2012 to 2017 and Forecast 2017 - 2025


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With recent advances in science and technology, particularly in machine learning, organizations need to adopt more comprehensive analytics strategies rather than basic analytics as large volumes of data is needed to be analyzed. Predictive learning is a technique of machine learning which aims to build a model that makes predictions based on evidence in the presence of uncertainty. It can be called as an attempt to learn with a minimum of pre-existing mental structure.

Predictive learning helps in solving real world’s problems in economics, business and government sector. Apart from this, it can be applied to a range of businesses to influence the future strategies including BFSI companies on account of escalating incidences of defaulters and stringent regulations for ensuring compliance with banking principles. Predictive learning has the ability of a machine to model the environment, predict possible futures and understand how the world works by observing it and acting in it. Predictive learning have many algorithms with strong theoretical guarantees.

Predictive Learning Market: Drivers and Challenges

The market is driven by the growing need to replace uncertainty in business forecasting with probability and increasing popularity of prediction as a key towards improved decision making. The rising budgetary expenditure on events and increasing adoption of cloud platform are also expected to drive the growth in the market.

However, Lack of expertise can be a hinder in the growth of the market.

Predictive Learning Market: Segmentation

On the basis of deployment, predictive learning market can be segmented into cloud and on-premises.

On the basis of end-user, predictive learning market can be segmented into BFSI, Retail, Telecommunications and IT, Energy and Utilities, Manufacturing, Government and Public Sector, Transportation and Logistics, Healthcare and Life Sciences, Media and Entertainment, Travel and Hospitality and Others.

On the basis of Application, predictive learning can be segmented into finance and risk, operations and workforce, Customer and channel, and Sales and marketing.

On the basis of region, predictive learning market can be segmented into North America, Latin America, Western Europe, Middle East & Africa (MEA), Asia Pacific excluding Japan (APEJ) and Japan.

Predictive Learning Market: Regional Outlook

North America is the largest market for predictive learning due to continuous advancement of technologies and increasing priorities among different enterprises over the past couple of years. It is expected to continue growing for the next five years, followed by Latin America and Europe.  The market growth in developing regions such as APAC and MEA can attribute to the massive data surge and a need to provide real-time analysis.

Key Market Players:

Some of the leading players of predictive learning market are: SAS Institute, International Business Machines Corporation (IBM), Microsoft Corporation, Tableau Software Inc, Oracle Corporation and Fair Isaac Corporation.

These vendors have adopted different types of organic and inorganic growth strategies such as new product launches, partnerships and collaborations, and mergers and acquisitions to expand their offerings in the market.

MRR.BIZ has been compiled in-depth market research data in the report after exhaustive primary and secondary research. Our team of able, experienced in-house analysts has collated the information through personal interviews and study of industry databases, journals, and reputable paid sources.

The report provides the following information:

  • Tailwinds and headwinds molding the market’s trajectory
  • Market segments based on products, technology, and applications
  • Prospects of each segment
  • Overall current and possible future size of the market
  • Growth pace of the market
  • Competitive landscape and key players’ strategies

The main aim of the report is to:

  • Enable key stakeholder’s in the market bet right on it
  • Understand the opportunities and pitfalls awaiting them
  • Assess the overall growth scope in the near term
  • Strategize effectively with respect to production and distribution

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