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Detailed examination of the Global business analytics market forecast from 2017 to 2022

IT Market Research

This report helps to analyze competitive developments such as joint ventures, strategic alliances, mergers and acquisitions, new product developments, and research and developments in the Global Business Analytics Market.

The Global Business Analytics Market is valued at USD 48.86 billion in 2016 and is expected to reach a value of USD 91.81 billion by the end of 2022, growing at a projected CAGR of 9.43% during the forecast period of 2017 - 2022.

We live in a complex society, where all too often decisions have to be taken in ignorance of what the outcome is likely to be. That ignorance arises partly because, in a changing society past experience is increasingly irrelevant as a guide to future action.

Thus, business organizations today are facing unprecedented challenges.

Increased complexities and competition plus tougher demands from consumers require more sophisticated business strategies

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An increase in purchasing power, demand and stiff market competition due to the entry of multiple players, corporates are forced to make crucial strategic and marketing decisions frequently. With the pressure to make informed decisions and the growing volume of raw data: both structured and unstructured; it is becoming increasingly essential to understand, interpret and manipulate the Big data and find patterns and trends in customer purchases and behavior to help effective and precise decision making.

The availability of sophisticated tools and techniques and the advancement in algorithm development has facilitated data analytics and business intelligence in a big way. Business Analytics, at the junction of business and technology, involves finding innovative techniques to study and analyze data to understand customer preferences, behavior and other useful business insights.

Its aim is to acquire competitive advantage in the market scenario by improving financial performance and decisions, strategic planning and achieving operational efficiency.

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The effective use of advanced data analytics is seen to contribute in higher financial performance, better and faster decision making based on quantitative findings and higher likelihood to execute decisions as intended. Business Analytics is extensively being used in diverse areas such as retail, e-commerce, financial services, software and IT domains, governmental organizations, healthcare, media and mass communication and energy utilities.

The growing importance of data discovery, the emergence of software as a service (SaaS) and the need for customer analytics are some of the factors that are driving the growth of the Business Analytics market. Investing in addressing specific consumer demands reduces the risks and errors involved in decision-making and lower the operational costs, resulting in a bigger profit share from the pie.

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The top active vendors of data analytics are SAS, IBM, Microsoft and SAP. Many other players, such as Oracle, Wipro and Accenture have gained prominence due to their active involvement in the development of platforms for Analytics.

The report involves a detailed account of recent trends, its analysis, key driving factors, the competitive landscape and projections pertaining to business analytics in the near future. It also elucidates market size, market value and shares, the recent mergers and acquisitions, the current attractive opportunities based on different market segmentations: by type (descriptive, decisive, predictive, diagnostic, prescriptive and event analytics) , by end-user, by vertical applications, by analytical functions and business category and by Geography.

What the report offers

  1. Market Definition for the Business Analytics along with identification of key drivers and restraints for the market.
  2. Market analysis for the Business Analytics Market, with region specific assessments and competition analysis on a global and regional scale.
  3. Identification of factors instrumental in changing the market scenarios, rising prospective opportunities and identification of key companies which can influence the market on a global and regional scale.
  4. Extensively researched competitive landscape section with profiles of major companies along with their strategic initiatives and market shares.

 

Table of Contents

  1. Introduction

1.1 Market Definition

1.2 Market Scope

1.3 Market Constraints

 

  1. Research Methodology

 

  1. Executive Summary

 

  1. Market Overview

4.1 Overview

4.2 Market Size and Forecast

4.3 Market Share Estimation

4.4 Industry Value Chain Analysis

4.5 Porter's Five Industry Forces Analysis

4.5.1 Industry competition

4.5.2 Potential of new entrants

4.5.3 Power of suppliers

4.5.4 Power of customers

4.5.5 Threat of substitute products

 

  1. Market Dynamics

5.1 Introduction

5.2 Drivers

5.2.1 Increase in Big Data: Structured and Unstructured

5.2.2 Availability of advanced Tools and Techniques

5.2.3 Growing Need for Customer Analytics

5.3 Constraints

5.3.1 Lack of Specialized skilled workforce

5.3.2 Data Privacy and Security

 

  1. Business Analytics Market Segmentation

6.1 By Deployment

6.1.1 Cloud

6.1.2 On-Premise

6.2 By Type

6.2.1 Decisive Analytics

6.2.2 Descriptive Analytics

6.2.2.1 Clustering Analytics

6.2.2.2 Personalization Analytics

6.2.3 Predictive Analytics

6.2.3.1 Cross-channel Analytics

6.2.3.2 Recommendation Analytics

6.2.3.3 Next Best Offer Analytics

6.2.3.4 Next Best Action Analytics

6.2.4 Diagnostic Analytics

6.2.5 Prescriptive Analytics

6.2.6 Event Analytics

6.3 By End-User

6.3.1 Retail

6.3.2 Healthcare

6.3.3 Communications

 

  1. Market Trends and Projections

7.1 Future Trends and Forecasts

7.2 New Product Development

7.3 Mergers and Acquisitions

  1. Competitive Intelligence - Market Shares, Profiles, Overview, Products and Services, Innovations and recent developments

8.1 IBM

8.2 Accenture

8.3 Deloitte

8.4 SAP

8.5 SAS

8.6 Oracle

8.7 HP

 

  1. Recommendations

9.1 Faster and Cheaper Analytical Executions

9.2 Trends in Analytical Outsourcing

9.2.1 Need for Analytical Outsourcing

9.2.2 Models for Analytical Outsourcing

9.2.3 Resource cost models

9.2.4 Pricing cost models

9.2.4.1 Cost Plus

9.2.4.2 Unit Pricing

9.2.4.3 Fixed Pricing

9.2.4.4 Variable Pricing

9.2.4.5 Incentive-based/Performance-based Pricing

9.2.4.6 Risk/Reward Sharing

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