MICROSOFT AZURE
AI & DATA ANALYTICS
54
COUNTDOWN
Top 10 best practices for next gen analytics 1 . Realise there is no silver bullet , but don ’ t do nothing 2 . Consider new infrastructure technology 3 . Consider more advanced analytics 4 . Start with a proof of concept 5 . Utilise disparate data 6 . Take training seriously 7 . Put controls in place 8 . Act on your data 9 . Build a center of excellence 10 . Remember to monitor your analysis Source : SAS
IBM ©
Infuse Finally , IBM Watson Explorer , provides its users with the ability to explore and analyse structured and unstructured , interal , external and public content to discover trends and patterns to improve decision-making , customer service and return on investment ( ROI ).
“ Operationalize AI throughout the business ” — IBM
MICROSOFT AZURE
As part of its multitude of analytics offerings , Microsoft Azure has a dedicated service for enterprise-grade , machine learning service for building and deploying models faster .
With its offerings , Microsoft Azure strives to “ accelerate the end-to-end machine learning life cycle ” for data analytics , by empowering developers and data scientists with a wide range of products to build , train and deploy machine learning models faster . Microsoft Azure boasts its ability to accelerate time to market and to foster team collaboration with industry leading MLOps and DevOps , in order to innovate on a secure and trusted platform specifically designed for AI .
MAY 2020