Big Data and the Opportunity
By Ajay Sunder, Senior Director, Frost & Sullivan
Technology today is radically transforming our lives in a way we have not envisioned before. Smartphones, Internet of Things (IoT), Bitcoin, e-commerce, and smartwatches, among others, are changing the way we live. At the same time, technologies like Big Data are transforming the way businesses are run.
The promise of new technologies is capturingtremendous investor interest. In fact, it is estimated that approximately US$120 billion will be invested by Venture Capital firms (VCs) in 2015, with the bulk of funding going into technology companies. Private companies with more than US$1 billion in valuation, termed unicorns, are increasingly common today. There are more than 140 technology unicorns globally as of September 2015. It is expected that many of these companies will go for public listing in the near future, drawing significant interest from retail investors.
Big Data has been attracting much interest and publicity over the past few years as companies and solution providers highlight the tremendous potential benefits of the technology.
Big Data is a phenomenon that describes the exponential growth of data, from every imaginable digital source, including machine data, social media data, pictures, audio and videocollected by commercial and government organizations. Traditionally, much of these different data sources were not stored and analyzed in a meaningful way due to the size, speed at which they were generated. What’s more, the datawas not organized into fields to be stored in Relational Database Management System (RDBMS), the de-facto standard for databases in the past. The amount of data generated each day has surpassed the capturing and processing capabilities of traditional database management tools and enterprise systems. Big Data refers to a new set of technologies that enable companies to store, manage and analyze large volumes of data being generated at a high velocity from varied sources in different formats. This capability is a game changer for multiple industries including the financial sector that extensively uses Big Data technologies for multiple use cases including fraud detection (primarily fraudulent credit card transactions), credit scoring and risk analysis of customers and identifying cross-selling and upselling opportunities based on past activities of their clients.
The global Big Data market is experiencing exponential growth, expecting to reach US$78 billion by 2020, and grow at a CAGR of 18.7% for the period of 2014 to 2020. The initial growth of the market is being driven by the need to manage the cost of storage and adoption of new visualization tools that simplify data integration and analysis, but will give way to a more advanced analytical need as organizations increasingly compete on information.
There are many new start-ups appearing on the Big Data Analytics scene. While the large analytics companies like IBM, HP, Google, Facebook, EMC, Baidu and SAS have long history and experience in the relevant markets, and extensive capabilities to match, many new Big Data Analytics companies are relatively small, and hence, unproven. Many of thesecompanies operate with few employees and deliver solutions with relatively low capital by leveraging the cloud. As deep Big Data Analytics talent is in short supply, it is vital to understand the expertise and experience of individuals that form the company and its technical team. This is one of the most critical value drivers for evaluating Big Data Analytics start-up companies. In fact, many large Big Data Analytics companies have been going on a shopping spree, purchasing companies with an intention to acquire talents in the respective fields of expertise. For example, Google acquired DeepMind Technologies, a start-up based in London, with the intention of adding experts in deep learning rather than specific products to the company.
A key value driver for Big Data Analytics firms is identifying the relevant potential addressable market for the solution. Big Data Analytics solutions are custom built for a variety of purposes, from business intelligence, human capital analytics, network performance analytics to social media analytics, and reducing the cost of storage of data. Understanding the potential market requires the current segments and geographies the company plays, in how they might grow in future, and which other segments and geographies may find use of the company’s solutions. For example, companies such as Tableau operate in the data discovery and analytics segment. Currently, it has around 35,000 customers in form of large and medium sized organizations across the world. But its products can potentially be adopted by a number of small companies, individuals, research scientists, and students in future.
Embedded User Base and Interoperability
Other key value drivers are the size of the solution provider’s embedded base of users and interoperability of its solutions into existing systems. The number of active users and licenses are important to sustain the development of features and asset utilization for solutions providers offering pay-as-you-use services.
Similarly, interoperability is essential as organizations invest significantly in their existing information infrastructure and require Big Data Analytics vendors to support integration for new solutions into existing systems. The current interest in visualization tools such as Tableau and Qlik are due to their increasing support for data integration into existing systems, making it easier for solutions to be deployed and consumed.
Similarly, mature Big Data Analytics companies continue to incorporate changes in the landscape, for instance, Microsoft working with Hortonworks to introduce Hadoop to Azure, and more recently, Spark.
There are opportunities for the ICT ecosystem players to utilize the big data potential for new revenue streams. Data is the new energy and ultimately provides a competitive advantage to enterprises over their competitors. So the ICT players need to be clear how they can enable this for the enterprises.
Quote: Analytics companies have been going on a shopping spree, purchasing companies with an intention to acquire talents in the respective fields of expertise
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