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Data, AI & ML
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Data, AI & ML
Global survey finds clear evidence that data works for business. What about New Zealand?
There's global evidence of the value of data, and New Zealand government has set out the world's first public sector standards on algorithm use - but will kiwi businesses follow suit?
The link between better data use and higher business value is clear, and it matters most to customer relationships in APAC, a global survey by IDC finds.
The survey included 10 countries, across the Asia Pacific, Americas and Europe.
A question of the research was the relationship of data use to customer satisfaction or loyalty – a factor especially critical for a COVID-19 impacted market. The most improvement was found in Australia (27%), with the highest average improvement in APAC (21.5%).
Some main benefits of effective data management were revealed in the IDC survey, with data-to-insight leaders seeing operational efficiency improvements (88%), revenue improvements (86%) and profit improvements (90%).
There were notable differences found between data-to-insights leadership between regions, too. Companies in the Americas, for example, saw a higher than average increase in profit (19%) while APAC saw a higher than average efficiency improvement (19.7%).
How about choosing data sources above others? Almost all of the companies in every country identified finding the value of data sources as difficult (96% or higher). Japan and Germany were exceptions to this, with a lower reported rate (89%).
New Zealand – setting the bar for data use
This bears major significance given New Zealand’s recent global leadership with a Charter of algorithm use in government. The Algorithm Charter for Aotearoa New Zealand involves six commitments – including, human oversight and transparency priorities.
While the central aim of the Charter is to give New Zealanders confidence that governments are using data safely and effectively, it is also hoped to set a precedent for algorithm use more widely.
On launching the Charter, Minister for Statistics, James Shaw, said, “Today we have set a world-leading example of how government can work with diverse groups of people, communities and organisations to improve transparency and accountability in the use of data. It is an example that we hope others will follow.”
This data-focused stance from the New Zealand government is an exciting move not only for amplifying New Zealand’s innovation and impact, but also for businesses and other organisations looking to organise and align their own data approach.
Data, AI, BI & ML
Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”
