## Section 1 Value Generated by Big Data

### 1. Expanding applications for big data

## (1) ICT advances drive the creation, distribution, and accumulation of big data

The soaring volume of digital data in global distribution is predicted to jump from about 1.8 zettabytes (1.8 trillion gigabytes) in 2011 to about 40 zettabytes in 2020. This explosive growth is being driven by increasingly sophisticated networks and devices that have become entrenched worldwide as essential infrastructure for daily living and economic activities. The evolution of ser-

### 2. Ascertaining data distribution volumes

## (1) Framework for estimates

### a. Surveyed entities

Big data, as it is called, includes data that individuals, corporations, governments, and all other economic entities generate through a myriad of means and routes. Vast amounts of structured and unstructured data are generated, the use and application of which is thought to generate new social and economic value. Ideally, we would prefer to ascertain the distribution volumes of all data categorized as big data, but it is implausible to get an accurate measure of all data, especially data generated by individuals. For this survey, we used a wider scope than last year's survey to estimate the traffic volumes of targeted entities and targeted data.

As for the selection of entities to include in the estimates, we calculated the volume of data corporations receive electronically, the same criterion as last year, as corporations are regarded as the primary economic engines that generate social and economic value applying big data.

We selected nine of the 13 industries on the inter-industry table—excluding the agriculture, fishing, and forestry industry, the mining industry, the government services industry, and the unclassified category—and tabulated the necessary data from these industries for the estimates.

### b. Surveyed data types

The types of data included in the data distribution volumes estimates for this survey were selected on the basis of whether the required data were obtainable and whether the data are used in economic activities at the corporate level, such as corporate marketing strategies and decision making. A total of 21 data types were included in the estimates: eight structured data types, especially the proliferation of social media and cloud services, is also powering the creation, distribution, and accumulation of enormous amounts of digital data. Furthermore, devices long considered completely unrelated to communications are expected to become entwined with communications and generate massive amounts of data, due to the emergence of wearable devices and other new communication devices and the advancement of M2M and IoT technology.

(customer databases, accounting data, POS data, medical receipt data, log data for e-commerce sales, GPS data, RFID data, and meteorological data) and 13 unstructured data types (business log data, CTI voice log data, fixed IP telephone voice data, mobile phone voice data, email, blogs, SNS, and other article data, access log data, electronic medical records data, image diagnosis data, monitoring and surveillance camera data, sensor log data, traffic and traffic-congestion data, and movie and video viewing logs).

## (2) Estimates of corporate data distribution volumes

The survey estimated the volume of data distribution in 2013 for 21 types of data in nine industries (service industry, ICT industry, transport industry, real estate industry, finance and insurance industry, wholesale and retail industry, electricity, gas, and water industry, construction industry, and manufacturing industry). The total was estimated to be approximately 13.5 exabytes.

Looking at how data traffic volumes have transitioned finds that data distribution volume has climbed from approximately 1.6 exabytes in 2005 to approximately 13.5 exabytes (estimated) in 2013. Thus, data distribution volume has increased by about 8.7 times (an average annual increase of 27.1 percent) over the eight-year period from 2005 to 2013 (Figure 3-1-2-1).

## (3) Analysis of the relationship between data distribution volumes and economic growth

We attempted to verify, using the estimated data distribution volumes by industry, what kind of influence the distribution and use of data by corporations has on Japan’s economic performance and whether data distribution contributes to overall real GDP. The economic effects of data distribution volume could not be confirmed.