Market Trends in India: Current and Predictive

Indian market is still in early stages of adoption of analytics. However, with surplus talent, established infrastructure, and a mature ecosystem, India is on its way to become a global hub for analytics.
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According to a recent NASSCOM report, the Indian IT and BPM sector is estimated to have generated revenue of USD 150 billion in 2015, marking an increase of about USD 17 billion over the last year. Of this, the analytics market in India, according to NASSCOM is expected to be around US$2.3 billion by the end of 2017-18, up from approximately US$1.5 billion in 2015.
Globally the Big Data analytics and related technology market is predicted by IDC to grow at a 26.4% compound annual growth rate to reach US$41.5 billion through 2018. In fact by 2020 IDC believes that analytics will be one of the key drivers for the economic growth of any nation worldwide.
According to Nasscom the Indian market is still in early stages of adoption of analytics. However, with surplus talent, established infrastructure, and a mature ecosystem, India is on its way to become a global hub for analytics. India Inc is now increasingly being seen to be seeking big data opportunities in the context of a rapidly shifting technological landscape and disruptive forces that produce and demand new data types and new kinds of information processing. Data liberation is leading to new technologies and new approaches to data, which is creating new business scenarios by extracting insights for decision-making and operational efficiency that were not previously available.
This huge opportunity brings in the need for new tools, solutions, frameworks, hardware, software and services to make the most of it. Good big data toolsets provide scalable, high-performance analytics at the lowest cost and in near-real time as business users increasingly demand continuous access to data. India currently stands at between the first and the second stage i.e. while it has embraced traditional analytics; it is yet to implement big data analytics effectively. In 2015, analytics started making an appearance with regard to customers, finance, risk management and operations; 2016 will see a major focus with regard to analytics in these areas.
As digital transformation grows, so does the reliance on new software and architectures. Today, software is not only driving business processes, but entire business models, and the need to manage, monitor, and troubleshoot applications in real-time has never been more critical. Thus, the need for speed, full-stack visibility, and agility — all in real-time — is the true business demand underpinning the growth of big-data analytics. Organisations are now driving the need for predictive, real time analytics and cognitive-intelligence applications. Some of the trends predicted going forward (or being witnessed) in this arena include:
Big Data Analytics will become all-pervasive: Self-service big data discovery takes centre-stage today. There will be an expansion of big data analytics with tools to make it possible for managers and executives to perform comprehensive self-service exploration with big data when they need it, at their level, without major handholding from information technology (IT) officers.
Data generation and analytics basis consumer behaviour - The much abused social media is really the biggest missing link to big data. Every piece of user generated social discussion is a rich source of metadata - it comprises of a unique user ID, creation data, time-stamp and geo-location tag. With the right kind of measurement solution, this pool of marked intelligence can reveal and cross-tag user benefits, affinities and their digital footprint. When millions of records are collated together, the big data resulting thereof has the potential to power products, brands and governments. 
Cloud – Private, Public and Shared: Today, the cloud is the place where all data that is being churned, is collected. The increase in the volume of data generated along with the growing demand for this across various organisations as well as various departments within the organisation will ensure that in future, big data will stored both on-premises and on the cloud.
Consolidation of data science, predictive and prescriptive analytics merge and the focus on multipolar analytics:
The merging of the science of data and predictive analytics will allow organisations to recognize events before they occur. This along with prescriptive analytics will help in extracting information from data and using it to predict trends and behaviour pattern making them forerunners in this sphere. In addition, multipolar analytics means the process by which data is collected and analyzed in multiple places, according to the type of data and analysis required. This is indeed a game changer for organisations today
Renewed popularity and demand for open source: Open source is witnessing renewed rise  in the big data analytics space given that it is relatively inexpensive and helps in the rapid development of communities around it. This is makes it the choice of solutions platform for many new and emerging organisations world over especially for start-ups that have limited financial resources at their disposal.
Internet of Things (IoT): Internet of Things has become a force to reckon with today as far as data analytics is concerned. According to Gartner, the revenue generated from IoT devices will exceed $300 billion in 2020. It has slowly but gradually penetrated into a wide variety of sectors with BFSI, Manufacturing, Healthcare, Retail, Government and Transportation being the ones which it has seen maximum penetration. The impact of this will be palpable across the data universe, encouraging companies to upgrade their tools and processes to derive maximum benefits from the growing volume of data generated.
Weaving together a data story:  The ability to tell a story with analytics is a key requirement today and with analytics becoming more advanced, storytelling is a must for all organisations. A data story—a narrative that includes analysis—can move beyond recounting of facts to weaving together pieces of analysis that make an impact and propel people to take action.
The ecosystem is becoming more complex and evolved, with new technologies being implemented to address a more diverse set of analytic needs changing buying behaviour, data generation from every possible touch point and sensors gathering information from all possible interactions; big data analytics is definitely here to stay. While India has some distance to go with regard to large scale implementation of big data across all sectors and in every sphere, the fact that it is sensitised to the need for this is evident from the fact that organisations across most sectors have adopted big data at some level. 2016 will see a lot of big data analytics, a combination of big data and advanced analytics which will definitely prove to be a game changer for organisations irrespective of its size and the sector in which it operates. 
As technology and companies embrace the cloud to increase business speed, functionality and agility, business intelligence will naturally follow, in order to delivering solutions that create continuous and real-time intelligence for the CXO. By harnessing this embedded intelligence in real-time through data analytics, companies will have faster access to operational and customer data that can enable 24/7 innovation and sustain their competitive edge. 
Authored by: Teradata India
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