1 26 October 2013 Observation and Reflection on Official Statistics against Big Data Challenge Yuan Pengfei Research Institute of Statistical Sciences.

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Presentation transcript:

1 26 October 2013 Observation and Reflection on Official Statistics against Big Data Challenge Yuan Pengfei Research Institute of Statistical Sciences National Bureau of Statistics of China

2 The situation and our preparation  Big data rolls toward us.  In recent years , we constantly strengthen the construction of statistical informatization in NBS.

3 The characteristics of big data  Most of the big data are from automated generation.  There are many data sources of big data.  Unstructured data have taken a large proportion of big data.  The value of big data need to be filtrated and extracted.  From 3V to 6V.

4 Why from 3V to 6V  Volume: data volume is huge.  Value: application value is huge.  Variety: data types are various.  Velocity: processing speed is rapid.  Vender: the acquisition and transmission of big data are flexible.  Veracity: veracity and accuracy.

5 The challenges and influences: About system design  Statistical standard.  Statistical indicators.  Statistical range.  Statistical method.

6 The challenges and influences: About data collection  By searching on the internet.  By purchasing.  By cooperation.

7 The challenges and influences: About data processing We must try our best to explore the methods and techniques on how transform unstructured data into structured ones.

8  Processing big data with high capacity, high speed and complexity requires server cluster to support a variety of tools.  Cloud computing is generally considered as the most economical way. The challenges and influences: About data storage

9  Accuracy  Timeliness  Applicability  Economy The challenges and influences: About data quality assessment

10 The challenges and influences: About data release  Release will be more timely.  The choice of release media will be more diverse.  The content of release must be richer.

11 Some ideas for application: CPI statistics  To collect online transaction price data by searching on the internet.  To explore the cooperation with online stores, thus to acquire online transaction price data.  To establish a system on which malls, supermarkets and hospitals can submit their transaction records to official statistical departments.

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14 Some ideas for application: PPI statistics  Collecting relevant online data by means of searching, thus provide useful supplements for the compiling of PPI in NBS.  Establishing cooperation with related companies, thus to collect the price information of related industries for the evaluation and validation of PPI.

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16 Some ideas for application: Employment survey Statistical analysis on big data related to employment on the internet will, to some extent, be very useful for learning about the situation in the labor market.

17 Some ideas for application: Agricultural statistics  The application of spatial data.  The application of data on the network of things.  The application of data on the Internet.

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19 Some ideas for application: Wholesale and retail statistics  Collecting the base data of E-commerce transactions, including quality assessment.  Adding the indexes reflecting E-commerce transactions into statistical report forms, such as total volume of E-commerce transactions.  Building E-commerce index reflecting the level of E-commerce transactions.

20 Some ideas for application: Transportation statistics  Making use of the data collected from various transportation infrastructures.  Making use of the data recorded and transmitted by vehicles.  Making use of the data generated from the object of transportation service.

21 Thank You !