AI & DATA ANALYTICS
“ To get the edge , hire great data scientists and arm them with the best data and business intelligence solution ”
RICH PUGH CHIEF DATA SCIENTIST , MANGO
With these developments we enter the realm of what we call ‘ data intelligence ’ With the exponential rise in data volumes across all industries , managed by both AI , machine learning and data scientists as described , data intelligence is the real fuel needed to accelerate past the competition in this field and create value . No company gets credit for simply being the best data collector around . It ’ s actually a risk and a liability if data is not curated and used responsibly .
So , what ’ s the secret ? The best data-driven organisations have basically learned how to build the best data refineries . And that means increasing data intelligence for knowledge workers through self-service data analytics , rather than being stuck , or mired in the tar of unusable data lakes . These organisations have several things in common ; they ’ ve taken all that raw data , curated it to understand what ’ s useful within their data lakes , catalogued it to make it fit for purpose and then democratised the data across the organisation to enable analytic insights from data intelligence . In essence , they ’ ve focused their data stewards on unleashing data intelligence to achieve actionable results based on metadatadriven insights .
Supercharged interest Rich Pugh , Chief Data Scientist at Mango Solutions , has more than 20 years ’ experience working with data . For him , data and business intelligence will be driven to data AI solutions in its quest to keep step with market competitors . “ In recent years , the need to become a more intelligent , relevant and efficient organisation has given rise to significant investment in both data and advanced analytics ,” he says . “ We understand that , if data is the new raw ingredient , we need to dynamically turn this insight and wisdom to support decision makers . This has supercharged interest in data science and AI and led to an increase in organisations looking to create data strategies that deliver ( and sometimes define ) their forward-looking business objectives . The broadening of the remit of data and analytics is also driving growth in data science teams . As a data scientist myself I can build the best model in the world , but if I can ’ t get someone in the business to change their behaviours to use the insight I ’ m generating , or if there are technical challenges that mean I can ’ t deploy my model in a repeatable way , then it stays as a beautifully crafted piece of code on a laptop .”
He went on : “ The need to deploy data and analytic outputs has seen significant increase in the need for data engineering teams who can build scalable and repeatable data pipelines and use DevOps approaches to put insight into the hands of the right decision makers at the right time . For businesses to get the edge , hire great data scientists and arm them with the best data and business intelligence solution you can find for your market .” technologymagazine . com 117