Questions Log:
Analyst Alert – Data Modeling is a Required Skill

The questions in this log were collected during the Senturus webinar Analyst Alert: Data Modeling is a Required Skill.

View the webinar recording and download the deck.

Q: Is a single fact structure good for reporting?
The simplest structure in data modeling is a single fact structure, meaning there is only one fact subject. The ideal structure of your data model will be determined by the scope of the reporting requirements for your project. For example, if you are only concerned about reporting on actual sales, you can design a single-fact schema. However, if you also need to look at returned items, inventory or forecasted sales, this schema would be insufficient, and you would need to edit your design to include those additional fact areas. This is an advanced modeling concept, so if you are interested in exploring more, please contact us at 888 601 6010 ext. 1. 

Q: Is it possible to use unstructured data for modeling or reporting?
Any type of data can be modeled and reported on; however, most traditional BI tools do not handle unstructured data well. The query language these systems are based on is SQL–Structured Query Language–so to deliver unstructured data through these tools, a significant amount of transformation or manipulation of the underlying data is required. There are other analytical tools and approaches for this type of unstructured or semi-structured data that we recommend you use, such as NO-SQL, Hadoop, text mining and R.

Q: Our reporting is slow due to the volume of data. What can we use to speed up reporting?  Will building multiple silos or cubes of data help? We already have a star schema.
We strongly believe in the star schema as a basis for design in relational environments.  There are a number of other techniques and tool-specific features in the modern RDBMS world that can significantly improve query performance such as columnar data storage, in-memory processing and aggressive caching. MOLAP cubes such as PowerCubes are still a good approach in many applications as well. We can conduct an architecture review for you. This investment will pay off many times with improved performance and user experience. please contact us at 888 601 6010 ext. 1 for more information.

Q: Do you think there is a difference between analytic reporting data modeling and operational reporting data modeling?
Operational and analytical reporting have meaningful differences; however, the underlying data models do not change much from a logical perspective. It is true that a semantic approach (how the underlying metadata is exposed) may diverge based on end users and whether they are more focused on operational versus analytical outputs, but it is rare that one application would have distinct data models for these two audiences.

Q: Are we able to review one-to-one and one-to-many cardinality?
Cardinality refers to the number of potential matching rows on each side of logical relationship. It is important for the query engine to have this information to create the proper query plan, especially in multi-fact queries. Cardinality is not expressed in SQL; however, query tools that generate SQL need this information to correctly prepare aggregation plans and optimization strategies.