Showing posts from 2015

Tableau Dashboards Published...

A few Tableau dashboards I have published off late to give a flair for different visualizations within Tableau:

Cyclotron's Android App

Just created a Xamarin Android mobile application . Extremely easy to use and did not require much reading the resources to understand how to go about building it. The first iteration is as shown in the figure below:
Though the emulator (Nexus 5 through 7) did not render as clearly I wanted it to, but still a great start for v1.0. The next version would basically integrate with Google maps. As soon as one clicks the app, you get a splash screen and then navigate to Cyclotron's main menu from where you can navigate to the layouts. The support aspect would also be a part of the next iteration of the app along with the Login. There were a few more images added to the individual activities .

Probably leverage this article as the initial help on how to use the app.... The follow up items are as follows: 1. Integration with Google Maps 2. Synchronization with Cyclotron's support database 3. Login for Support 4. Tweak the UI
5. Replicate for IOS

Excel Regular Expression Parsing

Sample piece of code to parse Excel files with regular expressions using Excel Query (The first piece does not loop through all the rows to make it more efficient and fetches the resultant set based on the first row. The second piece goes through all the columns and finds a match):

//This piece uses ExcelQuery -->using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.IO; using System.Text; using System.Web.UI; using System.Text.RegularExpressions; using System.Web.UI.WebControls; using Scanning; using System.Data; using Innovative.Data;
//Install ExcelQuery namespace WebApplication1 { public

Elasticsearch Notes

Been recently playing with a lot of open source tool sets to figure out core solutions for different product ideas that I have. One of the recent technologies I have used is the Elasticsearch tool. Elasticsearch is basically a NoSql based indexing solution that allows one to use Lucene indexes on top of massive data sets especially string based documents. This blog post is just a bunch of notes that I have compiled. What is Elasticsearch?
Elasticsearch is a document store with each document stored as an index in a cluster with multiple shards. Sharding is basically a concept of partitioning data based on some metric within the data:
Now Elasticsearch exposes an http based request-response to query the individual documents stored in the index.
In my case I created a 2 node cluster as shown in the following image:

After this step I created an index called imdb_search . Initially wanted to create a Graphing tool to showcase the connections that I had in facebook and the relations betwee…