For those out there who like to use Yahoo’s Site Explorer to investigate the Yahoo index and mange their sites, the day you’ve been dreading has arrived.

In my free time lately I’ve been getting into the superb online multi-player in EA and DICE’s Call of Duty baiter, Battlefield 3 on Xbox 360.  For anyone who’s not tried the series, it’s a large scale multi-player military shooter with wide open maps and a variety of land, sea and air vehicles with which to play.  While it’s enormous fun, especially if your fellow players work as a team it’s unfortunately riddled with game-breaking bugs.  Some players seem worse affected than others and the issues seem to be spread across all three of the game’s platforms; Playstation 3, Xbox 360 and PC.

If you’re a reasonably social media-savvy person, you’ll no doubt have heard of (and perhaps used) Klout, an innovative online service for measuring online influence via social media.  Klout’s unique selling point is their own calculation of influence, the Klout Score.  While it’s not exactly new to the social sphere, having been on the go in some shape or form since 2008, Klout have recently been engaging in a substantial push to increase the scope of their offering by adding many more social networks and features.

I recently encountered a scenario where I wanted to display my report content in the form of a multi-column list. In essence, I was looking to create the SQL Server Reporting Services (SSRS) equivalent of an ASP.NET Repeater, to render my report content both horizontally and vertically (in this case a dynamically repeated SubReport) a number of times dictated by my source dataset. I spent a little bit of time investigating some more complicated possibilities such as building a matrix of row and column groupings when the solution finally hit me. It is simply brilliant in its simplicity. Here’s how to do it.

Far too long ago, I posted part 1 of an article solving the import of large data files with varying columns using SQL Server integration Services (SSIS).  This is the belated follow up.  In part 1, I explained some example file structures and how we approach the problem of inserting these files, which all have a varying number of columns with different data types.   The solution combines a mixture of SSIS script tasks, external C# code in a referenced DLL and a flexible SQL Server DB schema.  This post will walkthrough my overall SSIS Control Flow, as well as detail how we translate a code based, dynamic object model into something well-defined which we can insert into a SQL Server DB.

Just a quick note for anyone visiting the site that there may be some downtime and/or interruptions here on picnicerror.net over the next couple of days as I’m moving to a new hosting provider.  The site will hopefully be back up and stable by the beginning of next week.

A couple of months ago I posted an article titled Vizualize.Me - your CV as an infographic in a single click, regarding an interesting new visualisation service which, using data from your LinkedIn profile can generate an entire, graphical representation of your CV in a single click.  At the time of writing the post, the service was gearing up to launch their private beta, with a public beta soon to follow.  Unfortunately, I didn’t quite make the cut for the private beta but the public beta is now live!  So, I’ve been straight in and created a visualisation of my CV (below) from my LinkedIn profile.

Just over a year ago I posted a question on my favourite programming Q&A site, Stack Overflow regarding an issue I was having with processing some large, variable column data files using SSIS (SQL Server Integration Services). Thanks to the great community there, I received an answer rather quickly and was able to develop a solution to solve the problem. I’ve been intending to document this for some time, as it’s a good solution, combining SSIS Control and Data Flow logic with custom C# code and a flexible SQL server database schema. I was working with a database schema which was set up to handle variable columns from a number of different files by transposing the columns into rows within the database. The upside of this is that it could support any number of columns from different files, in any order and with any type of data. The downside is that each row in a file, suddenly becomes row x column number of rows in the database, meaning processing large files can slow down exponentially if not handled correctly.