Anil Chawla, Managing Director, EIS, Verint Systems.
The Big Data analytics and related technology market is predicted by IDC to grow at a 26.4% compound annual growth rate to $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. 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. Big Data Analytics can be used to provide greater insight into customer behaviours and, through such analysis, an organisation becomes empowered to deliver a richer and more rewarding customer experience. In turn, this experience should lead to greater customer satisfaction, less customer churn and therefore greater profitability. This new generation of organisations will drive the need for predictive, real time analytics and cognitive-intelligence applications. Some of the current trends in the Big Data market include:
Big Data Analytics in the Cloud – Analysts have predicted that given the large amount of data that is being churned and collected along with the growing demand for the same across various organisations and departments within the organisation, the future state of big data will be a hybrid of on-premises and cloud.
Big Data Analysis to drive Datafication – The process that makes a business, data driven is by collecting huge data from various sources and storing them in centralized places to find new insights that lead to better opportunities – can be termed as Datafication. Datafication will take big data analysis to new heights – into real insights, future predictions and intelligent decisions. Datafication is what happens when technology reveals previously invisible processes—which can then be tracked and optimized
Multipolar Analytics – The process by which data is collected and analyzed in multiple places, according to the type of data and analysis required. This will involve both regular data feeds between poles and federated analysis to provide a connected view across the enterprise.
Data Security – Analytics have an increasingly important role to play in data security. Analytics are already transforming intrusion detection, differential privacy, digital watermarking and malware countermeasures. Strong security practices, including the use of advanced analytics capabilities to manage privacy and security challenges, can set businesses apart from the competition and create comfort and confidence with customers and consumers.
Predictive analytics – This includes using big data to recognize events before they occur. With newer and sophisticated big data analytics, extracting information from data and using it to predict trends and behaviour pattern is becoming the game changer for organisations.
Renewed Rise of Open Source – Open source is regaining popularity in the big data analytics space. Open source solutions are often free or inexpensive and the communities around them can enable rapid development and iteration. This is makes it the choice of solutions platform for many new and emerging organisations world over.
In this context, it is essential to highlight that the data referred to does not merely mean the usual data sets that are mentioned in conjunction with Big Data but also customer conversations obtained through transcriptions of contact centre recordings as well as email and social media interactions. Going ahead businesses will find more ways to harness this mix of structured and unstructured data, ideally helping them better address the needs of their employees and customers. These particular data sets can provide a unique insight into customer behaviours not generally available through standard transactional informationAll in all – Data Analytics is not only here to stay but will permeate into every department across organisations in all possible sectors.