Thoughts from Informatica World 2016
Filed under: Business Intelligence, Data Governance, Data Integration, Data Profiling, Data Protection
This past May I had the opportunity to visit Informatica’s annual conference, Informatica World, and now that some time has passed, I thought it would be worth reflecting on three aspects of the experience. First I had the opportunity to share a presentation with Robert Shields about the criticality of data protection, and in particular I was able to convey the message about the importance of integrating data protection techniques within the framework of data governance and data stewardship. In fact, I have summarized some of those same points in an article I later wrote for TechTarget searchCompliance.
Second, I attended an executive briefing in which the new senior executives shared their thoughts and expectations for Informatica’s progress over the next year. As Informatica has recently been taken private by a private equity firm, it was good to have some visibility into their plans for how they intend to continue developing products and services that enable data utilization, especially beyond the enterprise’s firewall, as we see more organizations extending their application framework into the cloud.
Lastly, I had a brief opportunity to chat with Informatica CEO Anil Chakravarthy. It is refreshing to see a C-Level manager so directly engaged in both driving the corporate product landscape and setting high-level direction for the global organization. Overall, it was also interesting to see how the company is realigning its messaging with the big data and analytics communities. Clearly, the information economy is growing as more organizations are adopting newer data management and computation technologies like Hadoop, yet in our upcoming survey report on Hadoop productionalization, individuals at all types of companies still see Hadoop integration with established enterprise componentry as well as the enterprise data architecture to be challenging, if not very challenging. As a result, we suggest that vendors providing data management technologies continue to expand their product catalog to include tools that can simplify big data application development, and I see that Informatica’s trajectory is aligned with that sentiment.
Scoping the Information Management Practice
Filed under: Business Intelligence, Data Analysis, Data Governance, Data Integration, information strategy, Metadata
Even if in reality the dividing lines for data management are not always well-defined, it is possible to organize different aspects of information management within a virtual stack that suggests the interfaces and dependencies across different functional layers, which we will examine from the bottom – up. 
Business Considerations: Using Data Replication for Operational Synchronization
Continuing dependence on system interoperability for data synchronization, coupled with rapid acceleration of data volume growth combine to create growing challenges associated with data consistency, accuracy, and reliability. Without a strategy for enabling operational synchronization, your organization risks not having the ability to support those critical real-time activities that business processes increasingly demand. Read more
Use Cases for Operational Synchronization
Filed under: Data Integration, Metrics, Performance Measures, Replication
In my last post, I introduced the need for operational synchronization, focusing on the characteristics necessary for a reasonable methodology for implementation. In this post, it is worth examining some example use cases that demonstrate the utility of operational synchronization in a more concrete way. Read more
The Need for Operational Synchronization
Filed under: Business Intelligence, Data Analysis, Data Integration, Metadata, Recommendations, Replication
Over time, organizations have employed a variety of strategies for managing data assets in accordance with the specific needs of the different business applications in operation. For the most part, applications were designed to achieve specific objectives within each business function. Correspondingly, any data necessary for the business function would be managed locally, while any data deemed critical to the organization would be subsumed into a centralized repository.
Yet this approach to centralizing data has come under scrutiny. Read more
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