Electric Vehicle Data Analysis with Machine Learning & Business Intelligence

August 4, 2017
Recently we collaborated with Microsoft and Prospect Silicon Valley (ProspectSV) on a project to assess the viability and value of several Azure services. Specifically, we were asked to demonstrate how the cloud-based platform could be used to retrieve, store, visualize and predict trends based on data from multiple sources. In order to demonstrate these capabilities, we built an ASP.NET MVC application leveraging the following Azure components:

  • Azure App Services
  • Azure Machine Learning
  • Azure Power BI Embedded
  • Azure Storage

Figure 1: ProspectSV Application Architecture depicts how the system uses these four Azure components. This diagram also describes which external data sources are used and where that data is stored.
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Customizing FAST Search for SharePoint 2010: Rank by Content Type

July 3, 2013
The standard configuration of FAST Search for SharePoint does not always yield the most relevant results.  This is often the case when developing SharePoint applications composed of custom content types and documents. The FAST Search for SharePoint 2010 default rank profile applies a -4000 point boost (or 4000 point penalty) to list items, thus drastically reducing their relevance in search. One can verify this by executing the following commands from a FAST PowerShell console:

$rp = Get-FASTSearchMetadataRankProfile -name default
$rp.GetManagedPropertyBoosts()

Executing the above commands in my environment produces this:

Default Rank Profile Managed Property Boosts

The impact of this configuration is often undesired in custom SharePoint solutions, where content types derived from Item (0x01) typically contain crucial information, or provide links to other related items. In these scenarios, some types of list items should appear at the top of search results. Fortunately, FAST Search for SharePoint offers a means of accomplishing this goal. Read More…