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When it comes to analysing the success of a website, and the amount of traffic it is receiving, two of the best tools for the job are Google Analytics and Adobe Analytics. Both of these tools are ultimately used for the same purpose, however, both have their unique advantages. In the case of Adobe Analytics, many of the features are similar to those present in Google Analytics, however, there are a few which stand out. Adobe Analytics allows users to create very detailed and customised search filters on the statistics, such as viewing the amount of customers who bought a product within a certain time range. These statistics can then be exported to many external tools for analysis and business intelligence, such as Excel. Within Adobe Analytics, reporting is, on the whole, more flexible than Google Analytics, however, it is generally easier to get started with generating reports in Google Analytics. One of the best selling points of Adobe Analytics is that data appears to be unsampled by default, whereas this is only available in the premium version of Google Analytics. Similar to Google Analytics, Adobe Analytics differentiates between traffic originating from mobile or desktop browsers. Besides this, there are loads of filters available for zooming in on data, including originating countries and regions, age groups, gender and many others. It is also possible to view detailed information about when, how and where the website traffic originates from. The biggest issue in Adobe Analytics is that a number of features which must be paid for in Adobe Analytics, are available for free within Google Analytics. Adobe Analytics is also definitely not cheap. On the whole, Adobe Analytics has a tougher learning curve than Google Analytics, and it can take a while to truly make use of the product to its full potential. Furthermore, Integration with Google advertising tools such as AdSense and AdWords is of course very limited, and finally, HotJar style heatmaps are not available.
SAS (Statistical Analysis System) is one of the leaders in the statistical software industry. It offers various statistical functions and an amazing support but also charges a price for its features and service. It can be seamlessly integrated with other technologies like SQL and R by writing user defined functions called macros. This means one can easily transfer data to and fro from SAS to R or SQL. This is a great feature as it lets the organization to have the best of multiple technologies. For example, SQL is way better than SAS in extracting and manipulating large data while SAS is better in applying statistical functions. So, with the ability to connect with SQL, one can use SQL to fetch and maneuver the data and various statistical functions can be applied to the data by importing the data in SAS environment.
SAS is easy to learn for people who have a programming background in any language. It provides a SQL procedure PROC SQL which is very useful for people who know SQL and have to work in SAS environment for certain reasons. A lot of documentation, tutorials and support are available over the web to learn about SAS. It also has cloud offerings which make it easy for employees to access SAS over the web from any device without the tedious process of connecting through a VPN. The ability to have user defined functions called macros which can be reused is a great asset to SAS. SAS itself provides a large number of functions but at times, due to certain business requirements, one need to write their own functions which can be compiled and later used as an inbuilt SAS functions.
One of the major drawbacks I have faced with SAS is that various procedures cannot handle more than 20 Mn rows of data. One can argue that 20 Mn is a lot of data but for the industries like Retail and Insurance churn out that many rows are a normal phenomenon. It is very expensive as well and small organizations and startups cannot afford it.
Tuesday 20 March 2012
With an expanding global viewership and a large number of digital properties, obtaining a clear picture of how our content is being accessed is a daunting task,” said Francis Lavelle, director of analytics at Discovery Communications, in a statement. “Adobe Discover is enabling us to achieve critical insights quickly and accurately as we better understand our visitors across visits and time. Thanks to Discover, our digital analysts are leveraging better attribution models and advanced trending capabilities to more quickly see the best way forward as we respond to our customers’ content needs and appetites.More about Adobe Analytics
Monday 11 November 2013
One manager (who asked to remain anonymous) said his team was now fielding more requests to get data into SAS Visual Analytics than running down the questions. The tool makes it so easy to interact with the data and the managers are really exploring the data and asking for more. The organization is moving down the BI Maturity path.More about SAS Analytics Pro
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