The Magic of Data

It was the 10th anniversary of SQLBits this year, with the conference tag line being, the magic of data. The conference was held at Olympia, London between 21-24 February. I am proud to have attended every conference since its inception and that I have been a helper for the last 8 years. At the start of each conference it is always an interesting challenge to understand the new venue layout and what things we can do to make this the best SQLBits conference ever for the attendees and speakers.

There were the usual two days of expert instructor led training days. I looked after a PowerBI day with Adam Saxton and Python day with Dejan Sarka. The Python training included Machine Learning for in-database SQL Server. It was a very helpful to have an overview of data mining, machine learning and statistics for data scientists. Having an appreciation of the maths and algorithms is important in this new diverse data world.

Friday arrived with a mix of general sessions running in multiple tracks. I initially attended a session by Mark Wilcock on Text Analytics Of A Bank's Public Reports. The recording can be seen here. The text analysis in R that was demonstrated was very similar to the type of qualitative analysis I undertook in my PhD. The session an introduction to HDInsight was a great starting point for managing big data.

The date that every data person has in their head this year, is 25 May 2018. That is the GDPR deadline. The big question for Microsoft was understanding the telemetry data collected and its pipeline to ensure that they comply to GDPR. It was great to hear about all the work they have done to address GDPR for the data platform.

I attended more sessions in data science and SQL Graph. Graph databases are very useful in certain scenarios. The on-premises SQL Server 2017 graph engine is different to that of the graph API in Cosmos DB and has different syntax. There are many new features still to come for SQL Graph.

Other very interesting sessions were on performance tuning with the tiger tool box, R in PowerBI, the flexibility of SQL Server 2017, inside the classic machine learning algorithms with Professor Mark Whitehorn, and a session on don't cross the streams, a closer look at Stream Analytics by Johan Ludvig Brattås. That concluded the breath of topics I  covered in this years conference. The conference covers an amazing breadth and depth of topics from database management, development, BI, data management and data science. My lightning talk experience from this year is shared here.

The rest of my time was spent mingling and sharing data experiences. It was an honor to have been able to be a part of the conference again.