From Singapore to Australia, the Asia-Pacific region (APAC) is in the midst of a big data transformation. Companies are collecting and storing more data than ever. Emerging technologies are building on older innovations to open up new frontiers in areas including transport, health, safety and urban planning.

Analytics applications that were unheard of just a few years ago have changed how organisations, governments and individuals interact. In Singapore, event organisers use geolocation data to monitor crowd movements. Banks in the Philippines assess loan eligibility based on mobile phone usage patterns. Thai telecommunications companies have analysed customer movement behaviour to optimise store opening hours. Social media companies in Singapore  monitored social media sentiment and engagement to gauge the opinions of the silent majority during the General Elections. As a result of recent advancements led by DataSpark, Singapore transport agencies have moved from analysing train performance to using predictive modelling to anticipate queue length.

Gartner analysts predict that over the next few years, “analytics will be pervasive and mission-critical for decisions and actions across the business”. At the same time, IDC reports that organisations in APAC have rapidly improved their capabilities for leveraging big data and analytics. More than a third (34 per cent) have even progressed to more mature stages – that’s an almost five-fold increase from the seven per cent in 2014.

Combined with the fast pace of technology change, these figures highlight the need for business and political leaders to embrace data analytics and its potential applications. With Singapore on track to be the world’s first smart nation – and neighbouring countries expected to follow suit – the time for action is now.

This white paper comprises key concepts presented at IGNITE, a client engagement forum organised by DataSpark in Singapore. With a focus on the APAC region, it will:

  • Examine the role of data analytics in improving public health, mobile interconnectivity, urban transport, safety, security and poverty challenges.
  • Identify top privacy issues facing organisations and data scientists, and discuss practical ways to overcome them.
  • Outline the most urgent data analytics challenges and list opportunities for change.
  • Explore what’s next in data analytics, including a forecast of future innovations.
  • Share best practices on how data-driven enterprises should navigate the new data analytics frontier.

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