Pete Stiglich

A health insurance client of mine recently embarked on an initiative to truly have “trusted data” in its Enterprise Data Warehouse so that business leaders could make decisions based on accurate data. However, how can one truly know if your data is trustable?? In addition to having solid controls in place (e.g., unique indexes on […]

I was recently a panelist for a Dataversity webinar/discussion focused on the future of data modeling tools, functionality, and practice. Given the holiday season, the panelists discussed their wish list for modeling tools – from currently practical (but maybe not economically viable) to futuristic (e.g., using a 3D printer to print models for model reviews, […]

Instituting Data Governance is a major initiative providing a significant opportunity to leverage enterprise data assets more effectively. As such, there is sometimes concern about being seen as a roadblock or concerns about formulating new enterprise level organizations, such as a Data Governance board and Data Stewardship committees. To be sure, a proper balance between […]

With all of the interest in big data in healthcare, it’s easy to get drawn in by the excitement and not realize that it’s not a silver bullet that’s going to address all your data and infrastructure problems. Unless you are able to understand and integrate your data, throwing all the data onto a platform […]

The importance of data integration, whether for analytics, mergers/acquisitions, outsourcing arrangements, third party interfaces, etc., is easy to understand but extremely difficult to realize. The technical aspect of data integration is the (relatively) easy part. The hardest part is bridging the semantic divide and agreeing on business rules – i.e., communication. The Conceptual Data Model […]

Providers and payers need to exchange or source a lot of data, and the rate of this activity will only increase with implementation of Obamacare and other directives. Given the poor state of metadata management (which makes data sharing much more difficult), the decision to incorporate a new data set into an Enterprise Data Warehouse […]

Operational systems frequently have to have data archived (i.e., backed up and purged from the database) in order to maintain performance SLA’s. Historical data is frequently maintained for a much longer period in data warehouses, but as a data warehouse is intended for storing integrated, standardized, and historical (and perhaps current) data in order to […]

I participated in a webinar/panel discussion last week hosted by Dataversity on Data Modeling Governance, which was well attended and lively. The focus was on governance of Data Models and the Data Modeling environment (e.g., tools, model repositories, standards). Data Modeling Governance is supported by Data Governance – and Data Governance benefits significantly from Data […]

In the Big Data Stack below, security is a vertical activity touching upon all aspects of a Big Data architecture which must receive careful attention, especially in a healthcare environment when PHI may be involved. NoSQL technologies, which many Big Data platforms are built upon, are still maturing technologies where security is not as robust […]

If you are undertaking any significant data initiatives, such as MDM, Enterprise Data Warehousing, CRM, integration/migrations due to mergers or acquisitions, etc., where you have to work across business units and interface with numerous systems, one of the best investments you can make is to implement an Enterprise Business Glossary early on in your initiative. […]

In a previous blog posting, I introduced Perficient’s Big Data Stack in order to provide a framework for a Big Data architecture and environment. This article is the second in a series of articles (click here for the first article on the Application tier) focusing on a component of the Big Data Stack. The stack […]

In my last blog posting, I introduced Perficient’s Big Data Stack in order to provide a framework for a Big Data environment. The stack diagram below has two key vertical tiers – the application tier and the infrastructure tier. I will discuss the application tier in this article. Figure 1 – Perficient’s Big Data Stack […]