Analytical Applications
Analytical applications include applications that process data extracted from source systems, varying from legacy systems to modern applications, from static data models to flexible ones. Applications provide custom or pre-built reports, cubes, and dashboards to multiple business functional areas across the breadth and width of industries.
In build-versus-buy decisions regarding the analytics scenario, the buy decision adds value by offering a quick start that can lead to shortened time to market and delivery.
There is a plethora of analytical applications available. However, there are multiple factors to examine to decide the right fit. The first question to ask is about the business goal. What are we trying to achieve? What would be the impact from the technological, infrastructural, and process prospectives? The results would come out of comparative calculations on direct and indirect costs, with the value coming out of the Implementation of Analytical applications.
While deciding the inhouse vs buy decision, compare cost and value of making fewer modification vs buy from vendor. following are the factors while making these decisions However, in absence of implementing right-fit features or missed ones all advantages to save time and money can get lost. Examine the following factors:
• Business requirements: focus on the problem
• Comparing the build-versus-buy analytical application
• Converting into specific features required to buy analytical application
• Comparing multiple features; which features are required?
• Considering skills and long-term total cost of ownership
How many source systems do we need to integrate? Fewer sources means a better fit. How much work is required to customize this? How many dashboards and reports and KPIs match? How much of the existing infrastructure matches, and what extra infrastructure is required?