Big Data Analytics

Share Your Thoughts! We’re opening the conversation on integrity and anti-corruption in new tech to our community. Each week we’ll explore one of the 2019 OECD Global Anti-Corruption & Integrity Forum themes and want to hear what you think of the challenges and opportunities of integrity in *Artificial Intelligence, Blockchain, Big data analytics, and Civic technologies. Comment below!

What is big data?

The use of techniques, technologies and software tools for analysing big data.  Big data is huge amounts of data generated from activities that are carried out electronically through machine-machine communications. It is defined by 3Vs: Volume, Variety (structured/semi-structured/unstructured) and Velocity (high speed at which data are generated, become available and change overtime).

What are the opportunities?

· The increased availability of and access to multiple data sources enables improved monitoring, supervision and enforcement of policies.

· Big data analytics can help experts across a range of disciplines to identify, analyse, and prevent strategic, operational and reputational risks, including the risk of corruption, fraud, waste and abuse. For example, government entities responsible for health and unemployment benefits make use of analytics to assess risks and ensure public funds go to their intended beneficiaries, whilst ensuring efficient service delivery.

What are the challenges?

· Big data analytics create complex legal, ethical and technical issues surrounding data collection, processing, and re-use. This includes ensuring the availability of audits and controls, supported by strong data governance models, as means to enforce the reliability, protection and integrity of data.

· The increased granularity of data and data inter-operability and sharing between government agencies across both public-private partnerships and borders can generate digital security vulnerabilities and concerns over individual privacy, consent and confidentiality.

· Having the right government-wide policies, institutional strategies and data governance approaches in place to ensure an effective data-driven public service and integration of data analytics into day-to-day activities.

· Enabling the right context to support coherent policy implementation drawing upon cultural change, high-level commitment, collaboration and skills can help to institutionalise data-driven approaches.