We observe many BI Project Sponsors clearly asking for an Analytics Package implementation to meet business needs; the benefit is that it saves time. By deciding on an analytics package we can get the application up quickly and comes with all typical benefits of a ‘buy’ solution against a ‘build’ solution.
So what are the key parameters that we need to look for in choosing an Analytics Package. The following would be the points to consider in choosing an Analytics Package, in the order of importance.
1.The effort to arrive at the right data model for a BI system is huge and as well quite tedious, so a comprehensive ‘Data Model & Metrics, Calculations’ from the package is very important.
2.The flexibility and the openness in managing Data Model is also very critical, some of tools to manage the data model elements that can be looked for are
- Ability to browse the data elements and its definitions
- Support for customization of the data model without getting back to the database syntax
- Auto Source System profiling and field mapping from the source systems to the data model
- Enabling validation of data type, data length of the data model against the source system field definitions
- Means to ensure that customization of the data model in terms of field addition doesn’t happen when a similar element exists
- Availability of standard code data as applicable to the functional area
- Supporting country specific needs in terms of data representation
3. ETL process for a BI system is also a major effort. Though the absolute effort of pulling the data and making it available for the package in the required format cannot be avoided, availability of plug-ins that can understand the data structure from typical systems like ERP would save good amount of effort.
4. Availability of ETL process for typical data validation as part of ETL is also a must; integration with any data quality product would be valuable
5. Ability to support audit and compliance requirements for data usage and reporting
6. Integration of the package with industry specific research data from vendors like D&B, IMS etc to enable benchmarking the performance metrics against industry peers/competitors
7. Customizable Security Framework
8. Semantic layer definition with formulas, hierarchies etc
9. Ready to use Score Cards and dashboard layouts
10. Pre built reports and portal
Often all the pre delivered reports under go changes and are almost completely customized when implemented. So availability of a larger list of reports itself doesn’t mean a lot since most of the reports would be minor variations from one other. Certain compliance reports would be useful when it comes along with the package; these would be published industry standard report formats.
Definitely an evaluation phase to test the Analytics products capability on a sample of the data before choosing it is a must, the above ten points would the evaluation criteria during this exercise.