Category Archive: Data warehousing

Data warehousing

Data strategy investment vs perceived cost – can they meet in the middle?

As data continues to surge into organisations from all different corners within this digitally transforming world, business decision makers no doubt feel compelled to invest in their data strategies and the technology that supports these, for long-term gain – and rightly so. Enterprise Information Management (EIM) has thus become a critical focus for many business …

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Cloudy with a chance of risk

You may have picked up from my last few blog posts that I have paid quite a bit of attention to the theme of data governance. With a passion for the theme, I recently picked up on some research specifically around governance of the cloud data warehouse. This caught my interest and reminded me that …

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The Elastic Data Warehouse

Some days I get really flexed out of shape about the rate at which new terms become spontaneously combusted in the BI and analytics industry. The latest I came across is the term “elastic data warehouse.” So what are we doing here – bending the rules, stretching the imagination or flexing our muscles here? Now …

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Using a Modern Analytics Platform

The increased use of analytics, coupled with an exponential growth in the volume and complexity of data, has changed the business intelligence landscape forever. Business users’ sophistication has extended beyond descriptive reports and dashboards into data exploration, predictive modelling and aspects of cognitive computing. Traditional requirements-driven ETL, data warehouse and reporting approaches do not meet …

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Accidental Data Warehouse

In many organisations we find what is called the “accidental data warehouse”. Sometimes you may even find more than one such data store floating around. These data warehouses have typically grown organically and uncontrolled as the result of separate and uncoordinated BI development and implementation initiatives.

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Dimensional Models for Predictive Analytics

Even though it has been around for years, predictive analytics has seen a much stronger uptake over the past few years. For example, store owners are now trying to predict what products their customers will buy and which products should be taken off the shelf completely; marketers are interested in analysing customer sentiment; telcos need …

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Revolt against the Data Lake as Staging Area

In previous posts I covered the data lake, approaches to “building” the lake and the data lake’s relationship with the traditional data warehouse. However as rosy as all that may seem, there are some people quite opposed to using the data lake as an all-encompassing free-for-all at-scale staging area. To an extent, I tend to …

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Building a Data Lake

The engineering analogy to building a data lake carries quite well. Putting a data lake in place is about as complex as building a man-made lake – there are so many aspects to consider. In this post I comment on some of the wisdom that have been published about building and populating data lakes. At …

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