02 Jul 2013

Google Analytics, Google Big Query and Digital Analytics

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Recent developments in the digital analytics market show a clear trend. The fields of business intelligence and digital marketing analytics are growing closer and closer together. For the people that have missed the news Google Analytics has announced that Google Analytics premium data will soon become available in Google Big Query. In the same month Tableau announced a cooperation with Datasift where they will make Social Data sources as Google Plus, Twitter Firehose, Facebook data and more available in Tableau through Google Big Query. It is exciting times for people that are working with Google Analytics and products as QlikView and Tableau.

So what is Big Query?

Google Big Query is a web service that lets you do interactive analysis of massive datasets—up to billions of rows, scalable and easy to use. BigQuery lets developers and businesses tap into powerful on demand data analytics with no up-front investments. You can easily upload data within seconds and use the powerful Google Infrastructure and cloud capacity to query hundreds of millions of rows of data with seconds of performance. When using Google Big Query you do not have to worry about the underlying technology and infrastructure (big data, map reduce, columnar storage etc). You can start using this technology in seconds rather than weeks, without having to go through the complex process of setting up hardware or software infrastructures.

What is so exiting about using Google Big Query with Tableau and QlikView?

Tools as Tableau and QlikView make it very easy to analyze vast amounts of data using a drag and drop interface. Data can be imported from different sources like databases, CRM, Excel, Logistic System etc. The power is to be able to cross combine the data to see how you are performing across the organization. The trend that companies as Google are using cloud infrastructure to start making datasets available for enterprises opens up a whole new range of possibilities. No more round trips of API programming and storing data into local data warehouses, but easy and direct on demand access to raw data through natural connections from BI tools. Also the amount of data that can be analyzed increases significantly as not all data has to be loaded in memory anymore. With the possibility of running queries on potentially gigantic data sources and pre-aggregate data into the desired format, you can query vast amounts of data within seconds directly from within your favorite BI tool.

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29 Jun 2012

From Digital Analyst to Big Data Expert

No Comments BI, Dashboards, QlikView, Web Analytics

This post is a reply to the post called “Big Data – What is Means for The Digital Analyst” by Stephane Hamel which provides an excellent overview of big data as a trend or hype and the key technologies involved. Stephane starts his post by mentioning that when he “Googled “Big Data” he got 19,600,000 results… Where there was virtually nothing about big data two years ago there is now unprecedented hype”. The digital marketing community, formerly called web analytics community, seems to be struggling with the key concepts behind big data and implications for digital marketing analytics. At the end of his post Stephane poses the question:

what should a digital marketing analyst do to bridge the knowledge gap between “digital marketing” and “big data”?

Having made the switch from web analytics to business intelligence I have some thoughts on this area.

source online-behavior.com

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25 Aug 2011

Twitter Analytics in QlikView

No Comments BI, Dashboards, QlikView, Social Media, Twitter Analytics

Social Media BI and Social Media Analytics are hot trends in the BI industry. As Microstrategy, IBM, SAP and other BI Vendors are investing in social media analytics it is a good time to show the possibilities with QlikView. It has been pretty quiet from QlikTech’s site in the social media analytics sphere so this is a great opportunity to showcase the possibilities developed by QlikTech partners. In the first blog post of this series “Twitter Analytics in QlikView” I will introduce you to Twitter and Twitter Analytics. I will start from the beginning by helping you set-up a Twitter account and learn some of the Twitter basics, before moving to the second part of this series called “Twitter Analytics – Finding Top Influencers”. Here we will introduce you to Twitter Analytics by showing how to find the top influencers in an industry and measure two important social media KPI’s: the number of brand “Promoters” and “Detractors”. If you would like to run the examples in this post with your own company or client’s data, simply download the Twitter Analytics Dashboard and follow the instructions on the QVSource Wiki. Make sure to download and run the latest version of QVSource before reloading the Twitter Analytics Dashboard.

Twitter is a great way to promote your brand, share thoughts and keep updated about the latest trends and insights in the BI industry. It can be a valuable source of traffic for your site and a good way of getting in touch with other Qlikview Professionals. The goal of this series is to show how easy it is to get started with Twitter analytics in QlikView, by providing easy to follow steps. After reading this series you should be well on your way of becoming a true Twitter BI expert.

Part 1 - Introduction to Twitter for QlikView
Part 2 - Twitter Analytics in QlikView – Finding Top Influencers

25 Aug 2011

Part 1: Introduction to Twitter for QlikView

2 Comments BI, Dashboards, QlikView, Social Media, Twitter Analytics

In this first blogposts in the series “Twitter Analytics in QlikView” I will introduce you to some of the Twitter basics. A basic working knowledge of Twitter will be required before starting with the more advanced part of this series called “Twitter Analytics in QlikView - Finding Top Influencers“. In the follow up post I will show you how to analyze Twitter data, find top influencers in an industry and measure two important Twitter KPI’s: brand “Promoters” and “Detractors”. But first let’s dive into some Twitter fundamentals for QlikView professionals.

Setting up a Twitter account

The first thing you will need to do is create a Twitter account though this link. Simply fill in your name, e-mail address and choose a nice Twitter name. The name can be changed afterwards so don’t worry too much about this at this stage. In the second part of the signup process you will be asked to fill in some additional information and create a profile description. Make sure to include some words you would like to be found on, like “QlikView”, “Business Intelligence” or “Business Discovery”. Adding these words will make it easier for like minded people to find you when searching for new profiles.
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25 Aug 2011

Part 2: Twitter analytics – Finding Top Influencers

3 Comments BI, Dashboards, QlikView, Social Media, Twitter Analytics

In this second blogpost in this series called “Twitter Analytics in QlikView” I will show how to use QlikView to find the top influencers in your industry and measure two important social media KPI’s: the number of brand “Promoters” and “Detractors”. For people new to Twitter I recommend reading the first blog post in this series called Introduction to Twitter for QlikView, where I introduced some of the Twitter basics and helped setting up a Twitter account. In this second part we will start analysing Twitter data using the “QlikView Twitter Analytics dashboard” developed by QVSource. If you would like to run the examples in this post with your own company or client’s data, simply download the Twitter Analytics Dashboard and follow the instructions on the QVSource Wiki. Make sure to download and run the latest version of QVSource before reloading the Twitter Analytics Dashboard.

The main focus areas of this post will be:

• Finding top influencers
• Measuring a person’s Influence with “Klout” scores
• Measuring brand “Promoters” and “Detractors” trends
• A list of influential people to add on Twitter

To analyse influence we will use the influence tab on the QlikView Twitter Analytics dashboard as shown in the screenshot below. If you click on the dashboard you can see the top brand “Promoters” and “Detractors”, plus influencer’s trends for the BI industry based on two weeks of data collected from Twitter. We will discuss the details of the graphs in the following sections.

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18 Jul 2011

Top 9 Best QlikView Examples

1 Comment BI, Dashboards, QlikView, Web Analytics

In this blog post I would like to share my favourite QlikView Dashboard examples. QlikView is an awesome Dashboard and/or data visualization tool that has been able to revolutionize the BI market. It is fun, intuitive and really easy to learn. All the examples below are available for download from QlikView or QVSource and can be tested at home, using the QlikView Personal Edition. I have been working with QlikView for a little over a year now and thought it would be nice to share my personal favourite Dashboards. Some are innovative, some useful and others are great for learning purposes. Enjoy the read!

Facebook Friends Analyser

QlikView Example Facebook Friend Analyser Dashboard

The Facebook Friend Analyser Dashboard can be downloaded from QVSource. This is a really great dashboard allowing you to analyse Facebook friends in ways you didn’t knew was possible. You can analyse “Friends”, “Groups”, “Likes”, “Sentiment”, “Check-ins” and cross segment the data using dimensions as “Relationship”, “Gender” and more. What makes this dashboard truly unique is that it offers some really good learning opportunities for advanced techniques such as integrating Google MapsSocial Media MeasurementSentiment Analysis and Geocoding in QlikView Dashboards. The code behind the file is easy to understand and with some minor modifications you can start applying these techniques to your own dashboards. At the time of writing the latest version includes a Google map which uses friend “locations” that are converted to latitude/longitude with the Yahoo Placemaker API. To run these examples make sure to run the latest version of QVSource and follow the instructions on their Wiki.

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26 Jun 2011

Merging Google Analytics with QlikView

6 Comments Dashboards, Google Analytics, QlikView, Web Analytics

Recently I read an interesting blog-post about how to merge Google Analytics data with a Data Warehouse. Integrating data from your website with Data Warehouse data opens up a whole new range of optimization possibilities. It allows you to add customer data, purchase data or demographic data  from your organisation to your website data. Another example could be measuring offline sales generated through your website. In my previous post I showed how easy it is to pull Google Analytics data in Qlikview. This post I will dedicate on showing how to create a key between website and website data, allowing you to associate Google Analytics with offline data in QlikView.

Setting up the primary key.

In the example above you see a Qlikview Dashboard pulling data through two different sources, Google Analytics and CRM data. In order to produce this type of holistic view of our channels we first need to create a (primary) key between the different data sets. Once the key exists Qlikview will automatically associate the data.

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12 Jun 2011

Google Analytics – Online & Offline Data Integration with QlikView

1 Comment Dashboards, Google Analytics, QlikView, Web Analytics

This is my first video in a series called Google Analytics offline online data integration. In this post we will be building a dashboard where we pull in Google Analytics data and plot it on a Google Maps. The video above will show you how to build this application!

The goal of the first video is to introduce you to QlikView as a business intelligence and data visualisation tool. In the next video we will go one step further and start adding sales data from a back-office application. This will allow us to create a holistic view of our data, for example measuring sales from a keyword to an offline purchase.

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