Mark Steinbacher

A Data Lake can be a highly valuable asset to any enterprise, and there is a myriad of technology solutions available for leveraging the processes to feed, maintain and retrieve information from the Lake. But all this technology is, if not worthless, significantly less valuable, if the environment is not well governed and managed. This […]

In my last blog, you may recall that we were discussing the value and the need for Standards and Templates for ensuring a consistent and efficient use of the Data Lake, both in its population (supplying) and in its retrieval (consuming) of information. To achieve this level of consistency and efficiency, as well as reliability, […]

In my previous blog, I described the concept of an “Information Catalog” and how it plays a vital role in ensuring communication between the Data Lake Aggregator and Suppliers and Consumers is efficient and effective due to the common language that it provides. I also included the following diagram as an example of how the […]

My previous blog talked about a Data Lake using a Supplier-Aggregator-Consumer analogy and talking about the roles each of these parties play. One factor that is critical to the success of this approach is the use of a common vocabulary that ensures efficiency and effectiveness in the interactions and collaborations between the parties. The implication […]

As you may recall, in my last blog I introduced the analogy of the Aggregator to describe utilizing a Data Lake as a Consolidator of information, and I mentioned the three key roles in this model: the Supplier, the Aggregator and the Consumer. In this post I will provide a little more detail on the […]

In my last blog, I introduced the concept of the Data Lake as a Consolidator and the critical success factor of applying robust Information Governance to this environment. In this post, I want to introduce an analogy to help visualize this environment and the parties involved. So, a Data Lake as Consolidator. What does that […]

Since my last post I’ve been working for a client that is actively engaged in establishing a Data Lake for the purpose of supporting their analytics efforts, but also looking to “re-architect” the way their systems collaborate by using this Data Lake environment to control and consolidate all information-sharing interactions within their environment. I was […]

As I have been continuing to work in the information governance area as it relates to healthcare, I recently came across an interesting development. Some of my previous blog posts have covered the difference between Information Governance and Data Governance and some of the players in the field, including the American Health Information Management Association […]

The explosion of data is something that executives across industry are trying to wrap their heads around. Healthcare is no different. In fact, healthcare data is expected to grow 99% – patient data, wearables, medical literature, scientific articles, etc. are adding to the explosion of healthcare information. This data deluge is a big challenge for […]

Of all the governance trends, none is more foundational and critical to the success of the governance program – indeed the organization itself – than the need for accurate, consistent, and relevant models that communicate the meaning, use, and residency of the information assets of the enterprise. Modeling not only addresses the integration and ingestion […]

Addressing the ongoing explosion of data sources and storage options requires establishing consistent metadata attributes and semantic models across the enterprise to effectively govern information as an enterprise asset. The primary objective of any enterprise governance program is to ensure consistent and timely data, so reaching consensus and agreement on a common understanding of concepts […]

The rise of Big Data, self-service, and more powerful and flexible end-user information visualization and preparation tools is impacting governance in a significant manner with regard to structure, decision rights, and accountabilities. End-users are gaining more control of data, including the ability to integrate and manipulate data for their own purposes, and being able to […]