Rising volume, variety and velocity of data are leveraging companies to embrace methods to analyze and process data for enhanced productivity. Growing smartphones penetration results to increase the digital interactions of individuals thus generating massive data. This attributes to the need for advanced analytics solutions thereby driving the big data analytics market. Factors such as quick & easy setup of data feeds without any manual coding and centralized monitoring & management capabilities benefits offered by big data analytics are influencing the market grow. Moreover, modern approach towards data warehouses for storing and processing huge data creates an opportunity for enterprises owing to the need for precisely identify and understand the data and workflows.
Segmental Insights
The Global Hadoop & BigData Analytics market is segmented by component, organization, application, end-user, and region.
Based on component, the big data analytics market is bifurcated into solution and services. The solution segment is to witness significant growth in bigdata analytics market due to growing demand for cost-effective data analytics solutions. Additionally, rising volume of data generation increases the need for data analytics solutions helping for better decision-making in real-time.
By application, the big data analytics market is segmented into customer analytics, risk & fraud analytics, IoT, and others. Modern big data use cases such as fraud detection, real-time customer marketing, trend analysis, IoT and others are vital parts of data management infrastructures. These factors are likely to gain traction for big analytics data market in the segment. Furthermore, solutions offered by competitive intelligence for improved decision making among enterprises analyzing useful information about competitor business is further increasing the demand for the market.
On the basis of end user, the big data analytics market is segmented into BFSI, IT & telecommunication, transportation & supply chain management (SCM), and others. Higher adoption of analytical tools by SMEs and online retailers for predictive analysis assists companies in segmenting products and services thereby results to drive the big data analytics market in this segment.
Regional Insights
Geographically, the Hadoop & BigData Analytics market is segmented to North America, Europe, Asia Pacific, and Latin America, Middle East and Africa (LAMEA).
In North America, Social media being one of the prominent means of communication is expected to witness significant growth in big data analytics market. On account of adoption of advanced data analytics solutions and rising demand for social media in the region is likely to propel the market growth. Furthermore, presence of strong players in big data analytics in the region are projected to boost the demand for the market in the region.
Europe is expected to maintain its dominance in the forecast period due to factors including increasing penetration of mobile devices and social media in the region that has emerged as significant factor impacting the growth of big data analytics market.
Asia Pacific is expected to witness dynamic growth owing to the factor of increasing technological advancement and widely growing opportunities across different segments of big data analytics market. Moreover, rapid increase in social media users in the region is to further increase the market growth.
LAMEA is expected to witness considerable growth in big data analytics market during the forecast period owing to growing technology expenditures demand for cost effective and user-friendly analytical software solutions.
Key Players
Some of the prominent players in the global Hadoop & BigData Analytics market are SAS Institute Inc. (U.S.), SAP SE (U.S.), IBM Corporation (U.S.), Oracle (U.S.) and others.
BigData Analytics Market Segmentation TOC
Recent Development
In November 2017, IBM launched IBM analytics engine that marked the new stage of Big Data analytics. It offers quick and simple way to deploy analytics applications separating the compute and storage infrastructure.