Today most organizations rely on data-driven insights to make critical operational and strategic decisions. But given the complexity and vastness of the modern enterprise data ecosystem, finding the right data set and extracting actionable insights is an extremely complicated and time-consuming process.
That’s where data virtualization can be used to abstract that complexity and introduce simplicity. Data Virtualization is a modern data integration technique that uses a single unified semantic layer to give you visibility into all of your data assets so that they can be better leveraged across the business. Attend this session to understand how data virtualization can be used to:
· Complete the self-service model by allowing business users to easily discover data for their specific business purpose
· Promote trust in data and encourage re-use of existing data assets
· Apply consistent security and governance policies across the enterprise data landscape
As Shaheen decided to build out data science and machine learning capability at MinterEllison, he noticed how many organisations struggle with operationalising this capability and the challenges they face with retaining highly skilled data scientists and analysts who end up disengaged when the organisation’s data capabilities are unreliable and the adoption of data-led thinking in the business is low.
In this talk, Shaheen will share from his 4-Horizon Roadmap, how leaders should take a sustainable approach towards data science that gives them bang for their buck.
· Getting the 3 Horizons in order - Creating a strong education, governance and cloud foundation across the enterprise to improve speed, accuracy and reliability of data assets leveraged across 2000 staff for decision making
· 4th Horizon -Taking an experimental, resource-light approach to put up “runs on the board” that drive business funding around data science
· The role of auto-AL/ML tools in driving early and easy wins for data science
· How to create a business-led push up the maturity curve for analytics rather than an IT/analytics team push