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From data to knowledge capital - A helpful guide

You may be familiar with the concept of being aware of the potential of data but not having the time to do anything about it. You may have a project in mind, but as there is no actual goal it has never got past the initial stages. How do you get from ideas to results in this situation?

What do you want to achieve?

Every successful “data to knowledge capital” project must have a clearly specified goal. A loose analysis of data consumes time and resources and hardly ever leads anywhere.

Who owns the data?

Data should have an owner. Having an owner clarifies each project stage and makes it easier to efficiently use data in the long run. To ensure that the foundation of the data does not become an obstacle to reaching an optimal process, it is important to remember this rule: data must by recorded to the greatest possible detail.

Involve the users of data from the beginning

You can always view things from a theoretical perspective but to change processes and operating models by using data you need to involve those responsible for the everyday tasks from the very start of the project. This ensures that project managers and analysts and the people who will be using the results in their work all understand the goal and the results in the same way.

Choose the right tools

Analytics can be used to link data sources and to answer questions that arise when decisions need to be made. The success of a “data to knowledge capital” project requires close cooperation between business operations and the analytics team from the very start. This way you can be sure that you have the right tools before you start. It is also a good idea to ensure that the analysts have access to all the data sources that are needed.

Start bit by bit

To avoid biting off more than you can chew, the best way to get started is to break down the goal into subprojects that are easy to manage and can be worked on on a daily basis. This way you can quickly set off on the analysis journey in an agile way, producing results and keeping motivation high and without being overwhelmed by the whole thing.

Create a user-friendly view

Last but not least, ensure that the results of the “data to knowledge capital” project are easy to use. The goal is to ensure that the end-users find the data easy to use and that it generates clear added value for them. Whether it is views of results or efficient integration directly into your process, functionality and ease of use are the key criteria for the project’s success.

If the use of your data is about to proceed from the planning to the project stage, take a look at the proven CRISP-DM project model.

http://houston-analytics.com/en/analytics-page/crisp-dm-the-standard-model-for-analytics-progress/