By . Tracking Spreadsheet. At Friday, May 07th 2021, 13:02:55 PM.
With that in mind, lets look at some of the differences between these two different types of tools. For the purposes of this article, I selected six criteria by which to make the comparison. These were selected from the feedback of customers and prospects as well as learning what is important for the successful adoption and implementation of project tools within an organization. Data Mining Data mining is a huge part of project management tools. The whole reason for having a tool is to collect data, so that you can look intelligently at that data, make sure your processes are performing as advertised, and make good decisions. You need to know which projects and tasks are slipping through the cracks so that you again react. You need to know when you will not have enough resources to meet demand so that you can allocate them properly or manage the demand. You need to know which issues are lurking so that you can address them now before you lose the favor of a critical customer. And you need to see how your processes are working so that you can continuously improve your processes.
In todays economy, competitive landscape, and accountability standards you must have the data. Managers are getting blindsided because they do not know what is coming and what is going on. This is where the right project management software tool shines and spreadsheets fade. A good project management tool will be database-oriented and should allow for different types of ad hoc reporting across multiple projects. This enables the mining of all kinds of data. You simply cannot do this in a spreadsheet at the same level. If you really, really know what you are doing it is possible to tie spreadsheets together and generate some integrated data. But that is not the same thing. You simply cannot, on a whim, mine into the data represented in your multiple spreadsheets. And in todays environment, this is critically important. Gone are the days when not having the right data is acceptable.
For example, Gartner, Inc., the worlds leading IT research and advisory company, describes business intelligence platforms as having three core categories of functionality (integration, information delivery, and analysis) and 13 capabilities (infrastructure, metadata management, development tools, collaboration, reporting, dashboards, ad hoc queries, Microsoft Office integration, search-based, OLAP, interactive visualizations, predictive modeling and data mining, and scorecards. While the technology itself is complex, many modern BI platforms are easy to use and loaded with features. For example, cloud-based BI platforms require only a Web browser, making deploying the platform a simple matter of signing up for an account and logging in. Of course, theres more to it than that. This particular tool provides users with the ability to analyze data from disparate sources and "mash it up." These mashups allow for quick and easy visual analysis and ad hoc reporting tailored to the users specific needs.