Author Archives: hbuchta

OpenStreetMap and other map sources for Reporting Services maps

SQL Server 2005-2016 The map functionality in Reporting Services may seem a little bit outdated with all the nice and interactive fancy maps for example in Power BI. However, standard reports still play an important role for distributing information in … Continue reading

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Why doesn’t my decision tree recognize a simple pattern?

Data Mining algorithms are sometimes perceived to be extremly intelligent and established with many super powers, humans don’t have. In today’s post I’d like to show a simple example in which a mining model fails to detect a very simple … Continue reading

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Using R Server in SQL Server 2016 to calculate the expected value for CRM leads (Monte Carlo method)

SQL Server 2016 In this post I’m demonstrating a use case for the new R Server (formerly known as Revolution R Enterprise) in SQL Server 2016 to calculate the expected value for CRM leads using a Monte Carlo approach. To … Continue reading

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A common pitfall with correlations in timeseries

Correlations are often considered an important measure to understand the underlying (probably hidden) patterns in data sets. But as with other statistical measures, a complex situation (many variables, many rows of data) is reduced to a simple numeric value which … Continue reading

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Fill down table in T-SQL (last-non-empty value)

SQL Server 2012-2016 A common task in data processing is to fill null values in a table with the latest existing value. For example, look at the following inventory table Let’s assume we only get an inventory record, if the … Continue reading

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Using R in SQL Server 2016 CTP 3 to train and query a predictive model

SQL Server 2016 CTP 3 One of the exciting features of SQL Server 2016 is the R integration based on Revolution R Enterprise. The online documentation contains detailed information about the installation steps but only a few examples about how … Continue reading

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Trend in times series analysis

  Time series analysis is widely used to forecast logistics, production or other business processes. Usually you want to understand if there is a trend or a seasonality in the time series. This could support forecasting and planning. However, there … Continue reading

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