Data warehousing technique is growing popular nowadays. Business and corporate houses are going for data warehousing for overall business performance and productivity.

Data warehousing varies in different business set ups. Both amenities and technical hazards are associated with the practice of keeping the internal data in the online stores. It is one of the most acceptable ways of storing in-house data. Intranet is the sophisticated form of storing a company’s internal records for future assessments.

Point-of- Sales records and transactions are also preserved in this mechanism. There is more than one way of online marketing data warehousing. In these systems, web analytics are maintained in online stores for easy reference.

Of the prominent ways of storing online analytics through data warehousing, we have:

  • Data Mart data warehousing: Data warehousing through data marts is one design methodology. It focuses on giving up business objectives for specific departments in an organization and their development. Data marts emphasize the development of a business set up through dimension modeling locally.
  • Data warehousing area wise: Web analytics data warehousing can be carried out on specific areas of particular business. Web analytic data storage starts with the data available from the online store of records. The existing records can be enriched with external data input as and when needed. Sales and purchase transaction records can be maintained through Point-of-sale data storage.
  • Third Way data warehousing: In third way data warehousing, detailed business reports and needs of company set up, technical resources required for a company’s progress-their availability and applications are preserved. This methodology is derived from the combination of the two major web analytic design methodology. It also states the other requirements of a business set up.

Online Marketing data stores helps us carrying out instant searches at search engines through data mining. Internal data stores offer Click-Stream data and integrated detailed click-stream data feeds. Data warehousing by Omniture help businesses prepare re-marketing lists. The web analytics also help keeping a track on the online visitor’s nature, the inbound site traffic source and the online behavior of the site traffic. Data warehousing by Google Analytics and Omniture has a number of benefits to offer:

  • Data Archives: Online data warehousing helps in maintaining records in archives for ready reference. Websites can keep a record of all Web traffic leading to a particular web page and the leads generated to the Website.
  • Click-Stream Data on advanced search: With a simple click on the search engine, we receive click-streamed online data.
  • Data warehousing leads to data feeds: With advanced search queries, the leads generate inbound links to the data. This in turn lead to valuable data feed to the website.
  • Advanced segmentation of web analytics data: An advanced segmentation of the website leads to an easy availability of the relevant data. This can easily be done with the user-friendly drag and drop interface of the Google Analytics Report.
  • Unique Visitor IDs: Users receive respective visitor IDs with the personalized user accounts.
  • Re-marketing lists: E-commerce and Online Marketers can prepare re-marketing lists with the unique visitor IDs.
  • External data integration: Most of the web analytics applications allow analyst to correlate external data by integrating it with the click-stream data. It is usually done through uploading a mapping/data file that contains a unique index key, so that data could be mashed up.

Web Browsing on Google and MSN offer user privacy mode, which enables websites to track the nature of inbound traffic to the site. There are limitations with users clearing off PC cookies on a regular basis. This leads to the removal of files and data that might prove vital for web analytic metrics.

Data warehousing for web analytics can be easily done with the help of web tools. There are web tools like Software as a Service (SaaS) that are commonly used in preparing metric reports. These tools are widely used to collect information on site operations, nature of site traffic and to make a competitive analysis of the data gathered. Number and options of website vendor support has also grown higher than before.

Data warehousing are needed to keep a track of web analytics. Figures on client data and facts on a visitor account are preserved with online data stores. Visitor accounts – its different types, sizes of the accounts and balances are well preserved. Customer-care metrics and other statistical figures are also preserved in these internal stores of records. Preparing monthly metrics to submit reports and analysis via tools like Google Analytics are also done.

However, data warehousing has a number of limitations associated with it:

  • Time Constraint: Preparing Reports through Online data warehousing could be time consuming if it is running through a batch process. Any re-run would cause a delay in downstream data dependencies: For this purpose, data stored on the internal database might have to be modified.
  • Existing database modification: To bring in changes in the online data, the database may require modification. This in turn could raise the infrastructural cost and new software may be installed for bringing in changes.
  • Threat to internal data storage security: Though the mechanism is quite effective for practical use, there might be security concerns. The database might have confidential reports with limitations. In these cases, data accessibility may have restrictions to the top management.
  • Vigilance over Data warehousing: Accounting confidential reports and analyzing them with Google Analytics has its advantages. But business and corporate houses have to exercise authority on tracking the websites and modifications brought out on the internal data.

This is just a quick overview of what could be a possible pros and cons of web analytics from data warehousing stand point. It is definitely not limited to what is mentioned here in this article. This is another area of great opportunities and challenges for web analytics professionals.

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