Data Aggregation Project Preparation: 10 Best Networking Practices

With the vast amount of irrelevant data floating around behind the firewall and across the Web today, it is more important than ever to take a good look at the sources of the data collected. This will ensure the data analyzed is indeed relevant to the business.

Web data is growing at an extremely rapid pace. For example, social media and ad-sponsored sites are exploding with new data every day, but this growth does not mean there is a corresponding rise in quality of content. It is critical to identify a source that focuses on the quality of data, not quantity. If the underlying quality of data is low, it ultimately makes it useless to analyze.

There are two options when aggregating data, automating data extraction or doing so manually with organizational resources. A company with data that changes daily or is time-critical will have an entirely different need than a company needing static data only once in a while.

The volume of data and its frequency of change drive scalability and reliability requirements. It is one thing if a company needs to get a few data points once a year but a totally different system is needed to aggregate millions of records that are being updated daily.

There is no one-size-fits-all when it comes to format and structure of Web data, so determine the data delivery structure you require to truly be able to use the information gathered.

Test out several turnkey analytics applications that will fit best with the company’s needs. In-depth analysis of data will ultimately allow a company to make more strategic decisions. Companies that provide this include Acxiom, ChoicePoint, Connotate, IBM, Hewlett-Packard and others.

The amount and type of data being gathered will determine the architecture and network needed for optimal performance of various protocols.

Research each data aggregation application carefully to find a tool that provides data consistency and uniformity. These applications must be able to deliver structured data sets from disparate data sources, otherwise IT will be left with a big mess to sift through.

For example, it’s easy to create a blog or Website. If you are using content from outside sources on your site, analyze data from Web sources you trust that have reputable information in order to avoid a potential and costly mistake.

Data aggregation is a versatile process because a company is able to pick and choose the specific information they want to analyze. Being selective with reporting needs allows for the selected aggregation platform to extract the most beneficial data providing a quick ROI.