Tag Archive: Data warehousing

Data warehousing

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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Analytics for Small Companies

Over the last few years, we have seen large organisations implement analytical technologies, like Data Warehousing, Business Intelligence (BI) and even Big Data Analytics, and we have seen some of them achieve the objective of a positive Return on Investment (ROI) on these initiatives. However, does the same reality apply to small to medium sized …

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BI tools

As this is my last blog post for the year, I thought it would be fitting to explore how the Business Intelligence (BI) landscape has changed over the years, especially regarding toolsets. Having worked in the BI sector for numerous years – in the last five years the BI toolset landscape has not only expanded, …

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Elaborate Architectures

In the Big Data field, because of the potentially large volumes of data, very streamlined architectures are being used. Sure Big Data sometimes participates in complex data warehouse ecosystems, but the real “Big Data” part has to be kept incredibly simple and efficient to be able to cope with the load. However, by comparison even …

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Revolutionising the Data Warehouse and Business Analytics

Last week I presented a paper on the Impact of Big Data on Data Warehousing at the ARK Group’s conference on Revolutionising the Data Warehouse and Business Analytics, which was held in Melbourne. In this post I give you my impressions of the conference highlights and share with you some of my insights.

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Measuring Real-Time BI

As the business landscape becomes increasingly more complex, business decisions makers not only want to but also need to know more about their business, customers and competitors to compete effectively – and they need this information almost instantly. However, with an ever changing economic and technological environment, it is often difficult to forecast business prosperity …

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Handling the Data Explosion

There is an enormous amount of data around, and much of it in data warehouses. We question the realities and discuss the approaches to keep the data warehouse to a handleable size, without reducing the availability of any historic data and without suffering any loss of data and information.

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Combining Agile Prototyping and Data Warehousing

Agile BI is all about interactively prototyping the information requirements and information usage with the business users. You can deliver data as quickly as technically possible, but if you don’t workshop the information exploitation aspects interactively with the users, then you are not being agile. 

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Agile Data Warehousing

“Agile data warehousing” is a contradiction in terms. Very few activities are less agile than populating a 10 terabyte data warehouse…  However if you want to deliver information frequently and rapidly to the business, you have to speed up the ETL implementation.

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Real-time Analytics

Organisations are focusing more on real-time analytics to incorporate advanced analytics in their day-to-day decision-making processes. There are two very different approaches to implementing advanced analytics in real time.

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