Principles of Data Strategy

According to TechEela, data strategy is a method defined for an organization about how it will store, collect, use, and manage data gathered from various sources so that the data becomes valuable and gives insights about business trends that can influence future business-related decisions.

Since data strategy is crucially important to any organization nowadays, some principles needs to be followed for a successful enterprise data strategy. 

The seven important data strategy principles are as follows:

  1. Data collection and sharing

A defined data strategy helps ease the collection of data and share it ahead with the organization’s other departments. When you have a proper procedure in place, you can gather more and more data easily, efficiently and effectively. The data thus collected will also be of higher quality as it will be more organized and well-structured. This will make the usage of that data a little easier for the data engineers and data scientists.

  • Data sharing made easy

The unstructured and raw data is very much used, but only when it is transformed into a readable format. Since data is obtained from many distinct sources, so it becomes impossible to use the data as it is. Hence, it becomes essential to convert and transform the data consistently to make use of it. Doing this practice consistently will lessen the work the employees need to do to fetch the data for their use, and it becomes easy to share the data within the organization.

  • Deleting data silos

When you delete data silos, it makes accessing data easier and enables collaboration among various departments of the organization. One aim of the data strategy is to integrate the whole company’s data into a single system so that it accessible for use all across the organization. This will smoothen the process of accessing data by employees of the company and help initiate new data-driven projects.

  •  Data Accessibility

The data strategy should also include a measure to make the data available in the organization to be accessible by every employee of the organization. The way you store data is very significant for accessing data. Data storage should be done in such a way that people find it convenient to access the data easily and can use the information they need without making multiple data copies.

  • Setting up data governance processes 

Data governance is the setting up of policies and regulations about how the organization’s people will manage the data of the organization. When these policies are in place, developers do not have to decide individually how to process, share or manipulate the data whenever they start with a project. In such case, they can make use of the rules set by data governance to make decisions. Data governance’s goal is to make data accessible, shareable and usable.  

  • Data analysis guidelines

The data strategy aims to define specific guidelines for employees about usage and analysis of data. This can be addressed by data governance, and the way you interpret or apply your data is known by your business goals. However, it might take a little while for developers to get familiar with the new policies, but many long-term benefits can initially cover this learning curve.

  • Defining targets for Data management

Defining clear goals for the use of data and data management is a very significant to a successful data strategy. The goals will lead the data strategy and its components and the way you manage your data. You must set both short and long-term goals as short-term goals to keep a tab on your performance and progress, whereas long-term goals will help you form a vision that will guide you with your actions. You can match your targets with the components of data strategy and collection, usage, sharing and storage of data.

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