A data strategy enables business goals and objectives by ensuring appropriate delivery of data management capabilities required to meet business goals. Let’s examine each in more detail. Cloud “Cloud First” has become a battle cry for many companies – driven by various factors including the desire to optimise infrastructure (and associated costs) as well as…
Welcome to 2020 everyone Kicking off by borrowing a look forward from our partner, Syncsort How to Modernize Your Traditional Database in 2020 If your data center is like many others, you have several important applications that rely on traditional database implementations. For example, it’s not unusual for companies to have business-critical applications that use…
A recent post on Information Week highlights 10 data and analytics trends that Gartner analyst, Rita Sallam, predicts will expand over the next 3 to 5 years. These trends fit into three main themes – intelligence, structures and scale – bringing together the potential of big data and machine learning. Augmented Analytics Sallam predicts that…
Today I overheard someone say, “Most business users give up trying to find or understand the data they need to do their jobs within 30 minutes of trying.” I gave up after 3 minutes of trying to find its source The digital business is dependent on data Self-service BI is dependent on data. Business goals,…
Cloud computing offers new opportunities and challenges to enterprises grappling with the explosion of data sources, growing data storage needs, and the problem of ensuring data quality.
What can you do to become data literate?
Everybody that works with data, and that makes decision based on data, needs to have an understanding of the underlying, fundamental data management competencies – such as data governance, data quality and data modelling – that allow them to assess whether data is fit for purpose.
The constant and relentless nature of ‘always-on’ data generation also makes real time analytics even more important. Much of this data is only relevant now, in the moment, and once it is historical it no longer has worth. It must be analysed immediately and then deleted, otherwise no value can be gained.
Emerging digital channels are driving an explosion of useful data: data available in every area, from sensors to social media, our customers to our machines. Yet, without the ability to analyse this information, it is of no value, as we cannot use it to derive actionable insight that will allow us to deliver what our…
New questions on ethical implications, data privacy, or public safety are studied seemingly daily.
How businesses manage the knowledge gap between decision makers and data specialists could be the difference between boom and bust
data quality, hyperscale and Python – the foundation of machine learning
