Loading Qonnections 2015 Instagram Posts Into Qlik Sense (Or QlikView)

In this post we will demonstrate using the new Web Edition of QVSource to load data from Instagram into Qlik Sense Desktop.

The QVSource Web Edition is currently in private beta but should be available for general (beta) download in June 2015. We are also currently hosting an invite only cloud hosted instance of QVSource Web Edition which a number of users are already testing out the new version with. If you would like to be considered for access to this please fill out this form.

NOTE: You can also try this out using the current QVSource Desktop Edition. Whichever version of QVSource you are using, when using Qlik Sense just remember that at present you will first need to make this minor config change in order to allow load requests from arbitrary URLs.

First of all we fire up QVSource and open the Instagram connector. We ensure we are authenticated with Instagram and then select the SearchForTags table and enter ‘qonnections’ in the Tag field. There are (at time of writing) 303 results for ‘qonnections’:

We can see that there are a few Instagram tags being used in relation to Qonnections, the most popular one being simply 'qonnections'. We can now go to the MediaByTag table and make sure that this tag name is entered as the tag to find Instagrams for and then run the table.

We then select the Qlik Sense tab and copy the script to the clipboard:

Now we fire up Qlik Sense Desktop, create a new app and open the data load editor:

We paste in the script, and click load data:

And run the reload:

Note that we do not necessarily get back as many results as suggested in the earlier table as the SearchForTags table above shows counts including images which are private or might have subsequently been deleted.

We then return to the app overview and create a new sheet:

We edit the sheet and drag a bar chart in:

Then add the dimension username:

...and a measure of count(id):

We then limit to the top 10:

...and complete the edit, giving us the top 10 posters:

We now create a new sheet and add a table with dimensions for user name and link; and a measure for sum(likes count):

We can then sort by likes (descending) to see the most liked posts and poster:

We click ‘done’ to view the results:

Now we create a new sheet and add a bar chart with create time (utc qlik date) as dimension and count(id) as measure. This can be sorted by the dimension (date) first and saved, showing the peaks in posting media around the annual Qonnections conference:

This demonstrates just how easy it is to pull data from instagram and quickly extract meaningful patterns and trends. This is just a simple example, in a real world example we might want to write QlikView/Qlik Sense load script to loop through a number of different tags which were used during the event. We could also extract a great deal more data such as comments and likes using the many other tables which the connector supports.

You will find a more complete example for QlikView over on our GitHub Page - note that although this is for QlikView the load script should also work fine in Qlik Sense giving you the same data model to build your user interface on top of.

You can request a fully functional free trial of QVSource from our and try out the 35+ Connectors it supports with QlikView or Qlik Sense.

Will Big Data Analytics Change The Competitive Landscape In The Next Year?

An interesting tweet caught my eye recently, but it’s taken me a little while to finally put pen to paper

It was a Qlik tweet that read “84% Of Enterprises See #BigData #Analytics Changing Their Competitive Landscapes In The Next Year: http://onforb.es/1FSCcDe via @forbes”.

The reason that this was of particular interest to me, is that this tweet hit on two things that are very dear to us: 1) data and 2) analytics. 

It’s very simple. There’s a HUGE amount of data out there that holds really important information on your business, and your company’s performance would benefit from accessing and understanding it.

The QVSource team believes that the more data we can help our customers gain access to, the more comprehensive their analytics will be, and the better their decision making will be, and the more successful they will become.

And it’s reassuring to read that 84% of enterprises agree with us. It’s certainly substantiated in the speed at which new customers and partners are buying into the concept of the QVSource data connectors. We are seeing an unprecedented number of organisations, from all industries and all corners of the globe, seeking access to new data sources via the QVSource connectors. QVSource helps companies mine data from a growing number (30+) of online data sources, and pumps vast amounts of new data into Qlik's Business Discovery solutions, in near real-time, ready for analysis. Our technology is changing the speed at which companies are able to react to data analysis, making decisions based on a larger and more comprehensive set of data more quickly than ever before.

Another statistic that was cited in the study was that “89% believe that companies that do not adopt a Big Data analytics strategy in the next year risk losing market share and momentum.” We agree! Data analysis gives companies an understanding of their business performance that leads to intelligent decisions being made, based on factual evidence. This is their competitive edge. Companies that don’t have that strategic insight, comprehensive understanding, and 360 degree view of their business, will have no chance of succeeding in an increasingly ruthless marketplace.

Finally, at the end of the report is an interesting chart asking companies to rank the challenges to implement Big Data. In our opinion these challenges are the same if you’re looking at any kind of new data to include in your analytics, whether it’s defined as Big Data or not. 29% of respondents rated as one of their top 3 challenges, (13% said it was their main challenge) the “consolidation of disparate data and being able to use the resulting data store are difficult”. QVSource is ideally suited to reduce this risk as it reaches out to various platforms and presents it as a single point of call to QlikView or Qlik Sense in a consistent, timely manner. Similarly, QVSource can help reduce the pain point for the 20% who rated as one of their top 3 challenges, “Reliance on multiple vendors-no integrated solutions”, as it integrates nicely into QlikView and Qlik Sense.

We're proud that QVSource is one of the technology companies that are fuelling this revolution. So if you want to get a more complete view of your business in Qlik, by drawing new data sets in from online sources, to make strategic business decisions in real-time based on fact, then come and talk to us. 

QVSource 1.5.3 Now Available

We have just released version 1.5.3 of QVSource - The QlikView API Connector. This blog posts outlines the main changes

As always, we would also recommend you read the notes on the "Change Log" tab of any connectors you are using for a comprehensive overview of changes.

New Connectors

  • Dropbox Connector: We have a brand new connector (beta) for Dropbox which allows you to list your files and folders, download file contents directly to QlikView as well as upload files to Dropbox via your QlikView load script.
  • Google BigQuery Connector: We have a brand new (beta) connector for Google BigQuery.
  • Sentiment Analysis & Text Analytics Connector:  We have added a new Regular Expression option to this Connector which allows you to perform RegEx analysis on any textual data in your QlikView application - you can see some examples here. Note that this is implemented locally in QVSource (it doesn't go via a Web API) so is very fast.

Updated Connectors

  • Twingly (Blog Search) Connector: We have an updated version of our Twingly Connector which allows searching for results from millions of blogs from around the world. With the new version you now get a small number of free API calls whilst trialling the connector and a larger number as a commercial user and there is no longer any need to contact Twingly separately for an API key.
  • Google Drive Connector: This now has a new table to return the contents of a file as XML (useful for example if you are hosting a QVD file on Google Drive).
  • Twitter Connector:  The Tweet Lookup table uses a new feature of the Twitter REST API which means it can now lookup up the data for up to 100 comma separated Tweet IDs per request (and 60 of these requests can be made per 15 minutes meaning ). We have also added the following trend related tables: TrendingLocations, TrendsForPlace, LocationsWithTrends. Finally, we have fixed a bug in the UserSearch table which was returning duplicated rows in some instances.
  • File Transfer (FTP/SFTP) Connector: FTPDownloadAndList and SFTPDownloadAndList tables have been added which list which files were downloaded and a FileCount column has been added to the simpler FTPDownloadFile/SFTPDownloadFile tables.
  • Sentiment Analysis & Text Analytics Connector:  We have added tables to support the new semantic API features from Repustate (Themes, Entities and Expansions). Please note also the old V1 of this connector is now deprecated and all users should move to the new version.
  • POP3/IMAP Mailbox Connector: We have added a new ImapMessageHeaders to allow you to access the emails headers.

Connector Fixes

Connectors Out Of Beta 

We've a few connectors that are moving out of beta, as such, if you're a customer and using these, please get in touch as they are now on our price list. 

Download Latest

Where do I find this new release? If you are a QVSource customer or have requested a trial in the past you should see this new release at the personalised download link we should have sent you via email.

If you are new to QVSource you can download a fully functional free trial from our website.

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