From Google to BAM and Business Intelligence: Exploring the Spectrum of Web Analytics
Data warehousing began with extraction and transformation of structured data from LOB apps for processing by BI tools. Now, analytics has evolved with departments using content, event, and web analytics.
In the early days of data warehousing, data integration tools were used to extract and transform structured data from traditional LOB operational applications, which were then loaded into a data warehouse for processing by BI reporting and analysis tools. However, the landscape of analytics has since evolved, with various departments now deploying analytics, including content analytics, event analytics, and web analytics. The development of collaborative and social computing tools will likely lead to the emergence of collaborative analytics.
Many of the individuals building these analytical solutions may lack knowledge of BI and data warehousing, and may not feel compelled to acquire such knowledge. It is therefore unrealistic for the BI group to assume that they can fully integrate this influx of information into a data warehousing environment. Web analytics provides a clear example of this issue, as it can be developed by the web, applications development, or BI groups.
What is the Purpose of Web Analytics?
According to the Web Analytics Association (WAA), web analytics refers to the process of collecting, measuring, analyzing, and reporting internet data to optimize web usage. The WAA also establishes standard metrics that web analytics products should ideally support, such as page views, visits, unique visitors, new visitors, returning visitors, clickthroughs, and conversions. These metrics are mainly used to identify website visitors, understand their behavior, and measure the success of their visits (e.g., purchasing a product or service).
Overall, web analytics provides valuable insights into website usage, visitor behavior, and online performance, which can help businesses optimize their online presence and improve customer engagement.
How do web analytics products function?
When purchasing a web analytics product, it is crucial to consider its ability to handle web pages with dynamic content that includes Rich Internet Applications (RIA) created with technologies such as Ajax and Adobe Flash. The capability to track RSS syndication readership and mobile users may also be essential for some organizations. Some vendors, such as SeeWhy, provide specific applications for web marketing. All of the products mentioned above support page tagging, while a few also support log file processing. The comparison table below highlights the differences between the tagging and log file approaches.
Log files can also serve as an ideal data source for a data warehousing environment, as they allow web data to be correlated with other types of enterprise data. Given the volume of data involved, some filtering and consolidation may be necessary before loading the log data into a data warehouse, which can be done using standard data integration tools that support flat files or using technologies like Hadoop MapReduce.
When real-time or near-real-time web analytics are required, there are two alternative approaches available from vendors. One is called business activity monitoring (BAM), which tracks and analyzes business transactions generated by web interactions as they pass through operational systems. BAM is useful for analyzing a continuous stream of business transactions and generating real-time reports and dashboards. For more complex processing of transaction and event streams, products that support complex event processing (CEP) can be used. CEP solutions can analyze and correlate multiple streams of current and historical data, identify patterns and trends, and predict potential outcomes. Examples of vendors in this area include Aleri, IBM (WebSphere Business Events, InfoSphere Streams), Oracle (Oracle CEP), Tibco (BusinessEvents), and Truviso. Note that some vendors use the term business event processing (BEP) instead of CEP, while others use terms such as continuous intelligence and continuous analytics.
To sum up, in today's fast-paced and ever-changing business environment, organizations need to monitor and analyze their web performance just as they would in a traditional business setting. Without reliable performance data, optimizing web operations and staying competitive is a challenging task. Various approaches and tools are available for producing web analytics, ranging from SaaS tools like Google Analytics to BAM, CEP, and data warehousing and BI offerings provided by enterprise software vendors. While SaaS solutions provide targeted web marketing solutions, enterprise solutions enable the merging of web data with other corporate data to provide a comprehensive view of web processing from an enterprise perspective.