With the rapid growth of data and the shift towards rapid development solutions much data is being stored in NoSQL stores such as Hadoop and MongoDB. The infrastructure built upon relational databases that have been used for decades cannot keep up with the volume and scope of data being captured. Further to this SQL is also a really good invention and method for extracting and analysing data that is very widely used.  In short it will not be replaced by hierarchical query techniques…

Traditional approaches to enterprise reporting, analysis and Business Intelligence such as Data Warehousing, upfront modelling and ETL have given way to new, more agile tools and ideas. Within this landscape Data Preparation tools have become very popular for good reason.  Data preparation has traditionally been a very manual task and consumed the bulk of most data project’s time.  Profiling data, standardising it and transforming it has traditionally been very manual and error…