Proposing a business-oriented data strategy

180729711In my two prior posts, I discussed the process of developing a business justification for a data strategy and for assessing an organization's level of maturity with key data management processes and operational procedures. The business justification phase can be used to speculate about the future state of data management required to meet existing and potential future needs. The assessment phase establishes where your organization is in terms of data management practices.

The gaps between where your organization wants to be in the future and where it is today can be formulated into the first cut of a laundry list of desired outcomes. In turn, a data strategy must suggest how introducing new data management practices, improving existing practices, and socializing the necessary changes in the ways that individuals consider, treat and manage data will not only alleviate the noted gaps, but will also deliver quantifiable value. Concretely, this means devising an information environment of the future. That is, an environment with the capacity, performance and functionality to meet existing and anticipated business needs, and to demonstrably lead to value creation or improvement. Correspondingly, the data strategy layers the implementation of data management practices on top of the proposed environment in ways that are directly tied to business objectives. Read More »

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The missing link in your data strategy – Part 2

chain with broken linkIn my last post, we touched on the importance of data migration in an overall data strategy. The reason I wanted to do this is because so many organizations see the migration of data as a technical challenge that can be outsourced and largely ignored by their internal teams. I contend that organizations have witnessed huge failures with data migration projects in the past, largely because they devolve responsibility and ignore the need for a robust approach.

The last article ended with a promise to examine how a typical data migration can feed into your data strategy. I believe there are several critical areas where data migration supports data strategy.

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Assessing your data management capabilities

business meetingIn my last post, I discussed some practical steps you can take to collect the right information for justifying why your business should design and implement a data strategy. Having identified weaknesses in your environment that could impede business success, your next step is to drill down deeper to determine where there may be opportunities to impose best practices in data management. Doing this will require you to assess your current state of data management capabilities and maturity in relation to the capabilities needed to support ongoing business needs.

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Top 5 characteristics of a strong data strategy

With data now impacting nearly every business activity, there should no longer be any doubt that data needs to be managed as a strategic corporate asset. This post examines the top five characteristics of a strong data strategy.

Existence

contemplative manAs I previously blogged, in today’s fast-moving business world now often takes priority over later. This means operational and tactical priorities often trump strategy. Some organizations use this as an excuse for why a formal data strategy does not exist. But organizations that are too focused on today cannot capitalize on tomorrow’s opportunities. So the first and foremost characteristic of a strong data strategy is that it exists. Read More »

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Who owns the enterprise data? Part 2: Business

open handWhile setting up meetings with business consumers developing a data warehouse environment, I was involved in some very interesting conversations. Following are some of the assumptions that were made during these conversations, as well as a few observations. To get a well-rounded view of this topic, read my earlier post that focuses on the IT perspective. Read More »

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Where does Hadoop fit into an effective data strategy?

elephantIn the previous post, I described how, at least to some extent, organizations can use data to build moats around their competition. I focused on the business side of the table, although I did touch upon the need to adopt new tools to make sense of what we affectionately call big data.

Today, I'll get a bit more technical.

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Business motivations for the data strategy

Puzzled business manPeople often seek out our company for guidance related to master data management, data governance and data quality. But I see a frequent pattern, where the customer presumes that they need a particular data management solution – even if there is no specific data management problem. This approach is often triggered in reaction to some management directive at the company, like “Move everything to Hadoop,” or “We need to be doing analytics.” It leads to the initiation of a series of projects for designing and building components or infrastructure (such as a master data management system, a data governance council or a metadata repository). Read More »

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Who owns the enterprise data? Part 1: IT

IT guy questioningThe other day I was in a meeting with a client and there was an argument about who owns the data. Those arguing were IT people. In this scenario, the assumption was that data from source systems would flow into and integrate with a data warehouse.

I found the discussion very interesting. Here are some of the assumptions I noted during the debate, followed by a few observations. Read More »

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