A few years ago I was working on configuring a test for comparing data transformation and loading into a variety of target platforms. Essentially I was hoping to assess the comparative performance of different data management schemes (open source relational databases, enterprise versions of relational databases, columnar data stores, and other NoSQL-style schemes). But to do this, I had two constraints that I needed to overcome. The first was the need for a data set that was massive enough to really push the envelope when it came to evaluating different aspects of performance. The second was a little subtler: I needed the data set to exhibit certain data error and inconsistency characteristics that simulated a real-life scenario.
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.
Filed under: Data Governance, information strategy, Recommendations
Data governance is a practice for ensuring that policies about information acquisition, use, protection, and disposition are defined, approved, and importantly, observed across the organization. Information policies are defined in relation to business policies and must be aligned with the corporate mission. Read more
I am assembling some presentations for a client on information strategy and thought it it might be interesting to share some of those thoughts as I develop my materials. This post provides a framing definition of information strategy.
A strategy is a plan and set of policies intended to help achieve specific objectives. An information strategy elucidates the way that principles for information use across the organization will help the organization achieve its intended goals. Read more
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