SQL Information Protection with Data Discovery and Classification

The public preview of SQL Information Protection brings advanced capabilities built into Azure SQL Database for discovering, classifying, labeling, and protecting the sensitive data in your databases. SQL Data Discovery and Classification are also added to SQL Server Management Studio.

This tools will help meet data privacy standards and regulatory compliance requirements, such as GDPR. It will enable data-centric security scenarios, such as monitoring (auditing) and alerting on anomalous access to sensitive data to be viewed in dashboards. It will help with controlling access to and hardening the security of databases containing highly sensitive data.

The SQL Information Protection (SQL IP) introduces a set of advanced services and new SQL capabilities, forming a new information protection paradigm in SQL aimed at protecting the data. The four areas covered are:

• Discovery and recommendations 
• Labeling
• Monitoring/Auditing (Azure SQL Db only)
• Visibility

Ph.D Graduation

“A story has no beginning or end: arbitrarily one chooses that moment of experience from which to look back or from which to look ahead.”
― Graham Greene, The End of the Affair

After 7 years of hard work, bringing industry and research together, I was excited to attend my Ph.D graduation. What an awesome and humbling day. Words can't express how it felt as a Ph.D graduate, with a Doctor of Philosophy, to sit on the stage along side the university academic staff. It is something I will never forget.

Now it is time to utilize my research skills gained throughout the Ph.D and begin something new. My aspirations in the academic field, are to write many  papers, share my research findings and to become a research fellow. 

Microsoft Professional Program for Artificial Intelligence

With Artificial Intelligence (AI) defining the next generation this Microsoft course seems a great way to jump start your skills.



The course covers these modules

• Introduction to AI
• Use Python to Work with Data
• Use Math and Statistics Techniques
• Consider Ethics for AI
• Plan and Conduct a Data Study
• Build Machine Learning Models
• Build Deep Learning Models
• Build Reinforcement Learning Models
• Develop Applied AI Solutions
• Final Project

At the end you gain the Microsoft Professional Program Certificate in Artificial Intelligence.

Leverage data for building

The leverage data to build intelligent apps presentation gives an insightful overview of the Microsoft Data Platform and how to innovate with analytics and AI. 

Advice and guidance on becoming a speaker or volunteer

I watched this great session giving 'advice and guidance on becoming a speaker or volunteer' from SQLBits this year. 

I felt humbled when I listened to the SQLBits session recording as I am named as an absolute legend for attending all 16 SQLBits and helping for over 8 years. I had never spoken, never presented or been involved in the public facing side of the conference. It is such a great feeling helping the conference be successful, helping others enjoy what working with data brings and being a part of the sqlfamily. Thanks to SQLBits for enabling me to be a part of such an amazing event for all of these years.

The PhD Bookshelf

Following on from the creation of a literature map for my PhD, I started to formulate a plan of literature to read. These are some of the books on my bookshelf.

I also read many academic papers, stored in seven box files and in Mendeley. 

Mendeley is a free reference manager.  It enables you to manage your research, showcase your work, connect and collaborate with over six million researchers worldwide.

I found the Communications of the ACM journal and SIGMOD, the ACM Special Interest Group on Management of Data journal great reads.

Demystify complex relationships with SQL Server 2017 and graph

This great infographic shows some quick tips about SQL Server 2017 and graph databases. You can view this at: http://msft.social/jCIE18 . The picture demonstrates nodes and edges and provides a clear example of the code changes between the Traditional SQL query and the Graph query.