Welcome

Passionately curious about Data, Databases and Systems Complexity. Data is ubiquitous, the database universe is dichotomous (structured and unstructured), expanding and complex. Find my Database Research at SQLToolkit.co.uk . Microsoft Data Platform MVP

"The important thing is not to stop questioning. Curiosity has its own reason for existing" Einstein



Friday, 9 February 2018

Saturday, 27 January 2018

Data Scientist Skills

There are an avalanche of skills required to become a data scientist. I came across this useful diagram.


The hierarchy of needs for data science could help you be more effective with AI and machine learning.




Monday, 22 January 2018

Migration from the Relational world to Graph
















I came across this useful blog SQL2Gremlin which translates the Northwind dataset. This was used as a sample database in older versions of SQL Server. The blog post explains the Apache TinkerPop's Gremlin graph traversal language using typical patterns found when querying data with SQL. The SQL examples make use of the T-SQL syntax.

This blog was helpful when looking at Azure Cosmos DB (Microsoft’s globally distributed multi-model database service). The  Gremlin console on the Azure portal is explained in the documentation, Azure Cosmos DB: create, query, and traverse a graph in the Gremlin console. The tutorial creates and queries vertices and edges, updates a vertex property, queries vertices, traverses the graph, and drops a vertex.
















The Gremlin console runs on Linux, Mac, and Windows. It can be downloaded from the Apache TinkerPop site.


Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP).

Wednesday, 17 January 2018

Field Guide to Data Science

I read this really useful  guide about data science. The Field Guide to Data Science was created to help organizations of all types and missions understand how to make use of data as a resource

More details about understanding the DNA of data can be found here.



Saturday, 30 December 2017

Diagrams help explain complex data

Diagrams are useful to help explain qualitative data. There are various diagramming tools that can help with understanding complex systems. These are the main tools that I use

  • Rich Pictures
  • Spray Diagrams
  • Systems Map
  • Influence Diagram
  • Multiple Cause Diagram

The  diagrams above were provided by the Open University and guidelines for constructing such  diagrams are explained.

The Open University guide to using diagrams can be seen in this video.


Wednesday, 20 December 2017

Continual Change and Complexity

This year has been an entire year of change for me, that will continue into the new year.  Continual change is the way of the new world. With data and AI being embedded into every realm of technology, we can expect more frequent and smaller changes on a day to day basis. I have enjoyed researching immensely and being able to apply that research to understanding the complexity of real world database problems.

As the holidays approach I wish you all a very Merry Christmas and Happy a New Year.

Thursday, 14 December 2017

The DevOps Model

TechNet UK had a live stream of talks back in September and this was a diagram that they shared. I think it is a helpful picture describing the process.