When most people think of legacy software, we think of software that is outdated and due for replacement. Yet, an alternative definition of legacy, particularly when it comes to mainframe application, is, simply, software that works. This is a definition that our partner, Syncsort, is proud of. The legacy DMX Sort product has been helping…
A short post this week – I am still travelling Bias in decision making can trump data – as discussed in Is Bias the 7th data quality metric – and Is High Cholesterol bad? On the global stage – the analytics that predicted a Hillary Clinton victory in the 2018 US election was, in…
Let’s define data and analytics and how specifically they are interpreted within the business context. Within a business context, many people consider data and information to be one and the same. While one can argue the definition of each, when talked of in conjunction with analytics, data becomes a resource to be interrogated for a…
We are surrounded by huge amount of data. Data is everywhere and is gaining huge importance and relevance in today’s world. There are many firms that are performing tasks of gathering, retrieving and managing data. This requires systems that can help us handle that much amount of data. Machine Learning has helped us in gathering…
A few weeks back I wrote about the The 6 dimensions of big data quality. These are: Coverage – how well does the data source meet (or fail to meet) the business need? Continuity – How well does the data set cover all expected or needed intervals? Triangulation – How consistent is data when measured form…
The results of Syncsort’s 2018 Big Data Trends survey have been releases and can be accessed as a ebook by following the link. One clear result of the survey, which engaged several hundred IT professionals over multiple industries is that what was unfamiliar technology four years ago is now becoming an integral part of the…
Historically, data quality has been measured in terms of dimensions including: Accuracy – the degree to which data reflects the real world Completeness – data that is adequately populated Timeliness – That data is available when expected and needed Consistency – that data across all systems reflects the same reality Conformity – that data has…
