SDMX a market view 6 th Global SDMX

SDMX – a market view 6 th Global SDMX conference, Addis Ababa Kristian Billeskov, Director 2 -10 2017 CONFIDENTIAL AND PROPRIETARY This presentation, including any supporting materials, is owned by Gartner, Inc. and/or its affiliates and is for the sole use of the intended Gartner audience or other intended recipients. This presentation may contain information that is confidential, proprietary or otherwise legally protected, and it may not be further copied, distributed or publicly displayed without the express written permission of Gartner, Inc. or its affiliates. © 2017 Gartner, Inc. and/or its affiliates. All rights reserved.

What is SDMX? • SDMX is a powerful ISO standard for exchanging statistical data and metadata. • It supports the exchange of a broad range of statistical data and metadata. • It is a complex niche standard based on XML (SDMX-ML). Analogous standards include XBRL and CML. • The work was initiated in 2001 and release 2. 1 is from 2011. 1 CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved.

What is the maturity of SDMX? expectations Data Catalog Data as a Service Data Classification API Standards in finance Citizen Data Science XBRL Data Quality Tools HTML 5 Cloud Computing Metadata Management Solutions SDMX Bitcoin Hadoop Distributions As of August 2017 Innovation Trigger Peak of Inflated Expectations Trough of Disillusionment Slope of Enlightenment Plateau of Productivity time Years to mainstream adoption: less than 2 years 2 2 to 5 years 5 to 10 years CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved. more than 10 years obsolete before plateau

Data and analytics is a massive investment area in business and government, providing an opportunity for SDMX § Overall, the BI and analytics market is expected to continue to grow 7. 9% (CAGR adjusted for constant currency) through 2020. § The modern sub segment of the BI and analytics market segment continues to expand much more rapidly than the overall market § 63. 6% growth in 2015 § 30% in 2016 § 19% by 2020. 3 CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved. § By 2021, the number of users of modern BI and analytics platforms that are differentiated by smart data discovery capabilities will grow at twice the rate of those that are not, and will deliver twice the business value. § By 2020, natural-language generation and artificial intelligence will be a standard feature of 90% of modern BI platforms. § By 2020, organizations that offer users access to a curated catalog of internal and external data will realize twice the business value from analytics investments than those that do not.

Successful standards require powerful players who backs the standards § Official statistics organisations hold the key to promoting the standard as they will be producers of SDMX data and metadata. § Investments in Data analytics are massive, but SDMX is not yet on the radar among the major providers of BI and Data analytics software. § Simpler and less powerful standards enjoy wide adoption for exchange of data sets. 4 CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved.

What is the status of the SDMX standard Technology support: Adoption: § Connectors have been written § Decision to invest and initial for key data analytics platforms (Excel, R, SAS, § There is no mature market for § No indications of widespread SDMX software, but open source software is available. adoption beyond statisticsproducing organisations. § There is no mature market for § Adoption is still mostly in pilot SDMX solution providers, but offerings are available. 5 implementations in multiple organisations. CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved. /initial adoption mode.

SDMX users and use cases Producers of official statistics • • Automated exchange of statistical data sets • Support programmatic access to meta data • Internal use of meta data for the design and management of production Users of official statistics (i. e. service providers or end-user organisations) • • Support automated discovery and assessment of statistical data sets. • Support automated bundling of statistical output with other data source. • Support AI Providers of BI and data analytics software • • 6 Out-of-the-box access to statistical data sets. CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved.

What is the potential scope of SDMX is an ambitious, powerful and complex standard with a niche potential § Will statistical organisations use SDMX between organisations or are there use cases within an organization as well? § Opportunities exist for automated reuse of multiple meta data across statistical organisations. § SDMX has a potential role in modernizing statistical production systems and SDMX might be a useful standard for end-to-end metadata management systems. § There may be a use case for using SDMX for dissemination, but competition is significant (JSON, CSV, XSLX) § What could be the trigger for accelerating SDMX? § For XBRL it was the reporting requirements following the financial crisis 7 CONFIDENTIAL AND PROPRIETARY I © 2017 Gartner, Inc. and/or its affiliates. All rights reserved.