NRI Announces IT Roadmap for Data Analytics Technology through 2015
Effectively using data to create a competitive advantage

Nomura Research Institute, Ltd. (NRI: Tokyo; Tadashi Shimamoto, President, CEO & COO) has released its latest IT Roadmap1 forecasting progress in data analytics technology through 2015 and its impact. With progress in technology, it is now possible to analyze massive data faster than ever before, which is expected to bring about substantial changes of the value of data in enterprises.

Three major changes have emerged in the field of data analytics in recent years. First, major IT vendors acquired and launched data warehouse appliances, which are a set of servers, storage devices and DBMS for the purpose of data analysis. Second, cloud computing2 infrastructure technology led to the establishment of an environment where vast amounts of data can be analyzed, which was difficult in the past. Third, thanks to the development of sensor technology, the amount of data that can be collected on a real-time basis from home appliances and embedded systems3 has been increasing. In order to use these data effectively, progress is being made in technology offering higher real-time analytic performance.

In the future, data analytics technology will provide companies with deep and broad insights. For example, companies will understand each customer in detail and give him/her their best offer from not only his/her profile but also from purchasing behavior. This technology will also contribute to alleviating traffic congestion and improving energy efficiency by analyzing data from sensor networks. Data analytics technology is expected to drive the creation of advanced IT services and new applications.

NRI forecasts that data analytics technology will evolve as shown in the following roadmap.

Data Analytics Technology Roadmap

Notes:

• DWH (data warehouse) appliance
• BI (business intelligence) refers to techniques whereby data is systematically stored, sorted, searched, analyzed and processed so that it can be effectively used for making business decisions.
• OLTP (online transaction processing) refers to a process through which a database is always kept consistent at data entry and retrieval.
• CEP (complex event processing) is technology to detect events by applying rules and analyzing time-series data.

■2010 – 2011: Beginning phase of use of cloud-computing-type analytic platforms

Major IT vendors have been successively offering data warehouse appliances that consist of integrated packages of databases and hardware. The use of data warehouse appliances will enable users to reduce the time for developing a business intelligence and analytic application system. Because of the pre-integration of database and hardware, companies will be able to reduce the cost required for operations, which will provide more time for them to focus on analytic work.

In addition, distributed application technology of cloud computing with commodity hardware is being used for analytic purposes as data-intensive applications.

In the commercial database product market, the share of products geared to analyze vast amounts of data, which are known as "analytic databases," has been increasing.

These analytic platform technologies will first be used in analytic applications in which data are processed automatically based on analytic results such as recommendation engines4, fraud detection, etc.

■2012 – 2013: Development phase of use of cloud-computing-type analytic platforms

Analytic applications that make use of large amounts of data will expand

During this period, many companies will be storing several terabytes or more of data in their data warehouses. Rather than simply storing such vast amounts of data, the number of companies that will employ analytic applications to effectively make use of such stored data to gain a competitive advantage will increase.

Data warehouse appliances will also expand by including more components in their integrated packages such as business intelligence software and large-scale data analytics technology. As a result, it will become easier for companies to analyze large amounts of data to support their decision making and to use analytic applications.

■2014 – 2015: Diffusion phase of real-time analysis technology

In addition to the expansion of components in integrated packages of data warehouse appliances and the storage and analysis of large amounts of data, there will be a growing need for higher real-time analytic performance.

With the diffusion of sensor networks and vast amounts of data captured from sensors, data stream processing technology offering higher real-time analytic performance will start to be used. The objective of data analytics will also expand from business data stored within companies and the Internet to include tangible objects such as devices with built-in sensors. In this way, data analytics technology is expected to contribute to the development of smart cities where social infrastructure such as transport, logistics and energy is optimized.

IT roadmaps for other technologies will be included in a book entitled "IT Roadmap 2011 Edition – Changes in Information and Communications Technologies over the Next Five Years" (in Japanese), which is scheduled for publication on December 24, 2010, by Toyo Keizai Inc.

1. "IT Roadmap" is published semiannually by NRI's Information Technology Research Department, forecasting trends in information technology over the next five years.
2. "Cloud computing" is computing infrastructure in which huge amounts of virtual IT resources are provided (or used) as a service through the Internet.
3. "Embedded system" is a computer system that is embedded into a home appliance and/or machine to provide one or a few dedicated functions.
4. "Recommendation engine" is a system that recommends products and services to users of websites such as electronic commerce websites.

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