GitHub maintains a list of all DMCA takedown notices along with counteractions and retractions if any.
Analysing all the notices from 2011, it seems that the takedown notices are on the rise.
Year View : Notice the sharp increase in 2014
Quarterly view : Now looking at the quarterly breakup, seems like the takedowns are cooling off in the later quarters.
So who is issuing these DMCA takedowns?
Here is the complete list of all companies who issued DMCA takedowns
NOTE: The names were extracted from the description text
And here are the counteractions and retractions
So the important question is “Why the DMCA takedown notices have increased?”
One important thing to note is sites like Stackoverflow encourage to replicate the content of the web page from where the original idea/algorithm or source code is copied from. To be honest it is a good thing because lot of times these referring sites become zombies and you don’t want to lose this knowledge. But could it be the case that such non-referenceable source codes end up in GitHub and hence causing the increase in the takedown notices as companies start discovering them?
Let us move on from Grass Eating Sauropods and talk about who’s who in the analytic space.
For every dime there are dozen analytic companies. Everybody who provides a freaking dashboard is an analytic company. Anybody that merely mentions Google, Facebook, Hadoop etc in the same sentence is somehow into BigData. Haven’t you stumbled across company pages where they claim to be expert in analytics and big data but they want you to schedule a call with them. They don’t have any products or solutions to show case yet they are Big Data/analytics folks.
So to make things easy, Mattermark released this highly curated list of 100 analytic companies. No offense to BigData, but small datasets like these are always juicy.
Mattermakr ranks each company using their own algorithm and calls it “Mattermark Score”. After loading it up, we came up with these visualizations
InfoCaptor : Analytics & dashboards
For each funding stage, it shows the listing of companies by Mattermark score.
Some interesting questions
1. How many companies by funding stage?
2. What is the funding by location and stage?
InfoCaptor : Analytics & dashboards
We thought the above visual would tell us what kind of logic did Mattermark used to rank the companies. As suspected, apparently we cannot reverse engineer it without some additional information about the companies.
First we asked what is the top most program (duh!!) but by how much and who are next in the list and so on.
Like most Data scientists who believe in the power of simple bar graphs we used our first “chart weapon” of choice and here it is what it rendered.
Y Combinator is freaking huge like a dinasaur, infact very much resembles the grass eating Sauropods. In fact we had to create a chart that was 3000 pixels wide just to accommodate all.
See the resemblance between the chart and the Sauropod?
To get better perspective we rendered it in a Treemap as shown
Looking at the treemap, Y Combinator occupies more than the sum total of all the remaining accelerators. That is super amazing but the problem our charts were not coming up beautiful. YC is clearly the outlier and was causing us difficulty to understand the remainder startup ecosystem.
We said, lets cut off the head to dig deeper.
The moment we filtered out YC from our analysis, all of the regions became colorful and that was certainly a visual treat.
Now we could clearly see what are the other accelerators/programs that are roughly the same size.
TechStars Boulder and AngelPad are roughly the same
TechStars NYC, TechStars Boston and 500Startups are in the same club
Similarly DreamIT, fbFund and Mucker Lab share the same color.
Now let us try to see from the location angle
So we re-established that YC is freaking huge and having them on a chart with other accelerators does not create beautiful visualizations.
Digging into the Boston public Dataset can reveal interesting and juicy facts.
Even though there is nothing juicy about Bed bugs but the data about Boston open cases for Bed bugs is quite interesting and worth looking at.
We uploaded the entire 50 mb data dump which is around 500K rows into the Data Visualizer and filtered the category for Bed Bugs. Splitting the date into its date hierarchy components we then plotted the month on the Y axis.
It seems that the City of Boston started collecting this data around 2011 and has only partial data for that year.
Interestingly, the number of Bed bug cases seem to rise during the summer months.
Now if we break the lines into Quarters (we just add the quarter hierarchy to the mix)
Recently, here at InfoCaptor we started a small research on the subject of flags. We wanted to answer certain questions like what are the most frequently used colors across all country flags, what are the different patterns etc.
The innovation engine in the field of Business Intelligence and Data visualization tools , is certainly cranked up. Qlikview, Tableau and Tibco Spotfire introduced new category of Data Visualization term in the field of Business Intelligence.
Now every vendor offers some form of Data Discovery. Oracle is also working on something similar adding to their confusing mix of OBIEE stack.
With the launch of new InfoCaptor, you can perform ad-hoc data visualizations and build dashboards all within the browser. Now that is refreshing. The browser is the key here. Once you deploy on the server, users can simply login, upload their datasets or point to existing database connection. Before you know users are already slicing and dicing their datasets and swimming in the world of beautiful visualizations. Yes, the visualizations are absolutely stunning and why shouldn’t they be. It is based on the excellent d3js.org library.
The key here is that the browser is your canvas and it is pretty huge, for e.g the detfault size for the visuals takes up my entire browser screen real estate. I like big visuals and if I am producing a Trellis chart then I can simply drag the corners and resize it. The visualization library is very comprehensive and offers around 30 visuals. It provides the bullet graph as well for KPI tracking.
Here are some screenshots from the website
InfoCaptor is also available on the cloud as a service and based on that there are few live analysis to try out without login or installing anything.
I would say with this release small business owners have truly found their Tableau or Qlikview alternative.
Go check out the new InfoCaptor Data Visualizer