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and analyse data , rather than just data scientists or engineers .
These risks could be mitigated by employing an automated data analytics stack .
Data enables outcomes for every area of a business . So , whether it is improving the customer and employee experience or complying with rules and regulations , each line of business should be able to creatively solve its own analytic problems and apply its own specialist domain knowledge to the use cases which matter most .
By way of illustration , consider how a tech stack capable of automating data analytics can be used to ensure regulatory compliance in the financial services industry .
A combination of data engineering capabilities and a mixture of visual analytics tools can be used to create a streamlined workflow which will alert institutions in real time if they need to make corrections to ensure compliance .
By transforming the QA process from reactive to proactive , this allows teams to address any issues as they arise , instead of possibly having to wait months for results .
Under regulations like MiFIR and MiFID II , financial institutions are required to report applicable transactions to the relevant regulatory authorities .
But millions of transactions can take place every minute , especially at larger institutions ; the manual preparation and cleansing of this data for quality assurance ( QA ) purposes can therefore be a tremendously slow process .
In fact , it can take as long as up to two months to notify regulators . This can leave financial institutions vulnerable .
If any part of the system should fail and require correcting during that time , they risk facing regulatory fines .
Of course , this is just one example of how automated data analytics can be applied to a business use case .
Their potential scope is much broader , though , enabling organisations across all industries to deploy an analytics strategy to identify new opportunities , improve efficiencies , meet ESG criteria , and more .
Data is hugely valuable to every business . As the data generated and used by businesses continues to grow in volume and variety , a modern automated data analytics stack with a simple and accessible interface is key to allowing everyone within an organisation to unlock that value for the benefit of internal and external stakeholders alike . p
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