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Tips For Creating Your Perfect Data Strategy

Peter Bernard's picture
Chief Executive Officer Datagration

Peter Bernard serves as Chariman and CEO at Houston-based Datagration. He is a multi-decade veteran of the oil and gas industry, having served in various executive roles prior to joining...

  • Member since 2022
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  • Sep 27, 2022
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Any great business begins with strategy, whether you're a large enterprise or a small, family-run company. In today’s world, any firm, no matter how large or little, in any industry requires a robust data plan. There are countless ways in which data science may benefit a firm. Nevertheless, if you wish to use data, you must always begin with a data plan. Let’s look at what constitutes a solid data strategy. 

Company Strategy 

A successful data plan should not be developed in isolation; rather, it should be guided by your entire company plan. As a result, the initial step in developing a data plan is to think about your organization’s strategic aims and critical business questions and objectives. Only then will you explore how you may utilize data to assist you in meeting those goals and answering business issues. 

Priorities for Short-Term Adoption 

Since large strategic data goals might take time to achieve and generate value, it is useful to identify a few quick; hopefully low-cost methods for you to offer value and show return on capital from data, which can help you win buy-in for more visible data use cases. You could, for example, conduct a customer churn study to assist in preventing or decreasing client turnover. 

Data Requirements 

Consider what data you will require to fulfill your objectives and where that data will originate from. This includes the following: 

  • Do you require organized, unstructured, or (preferably) a blend of the two data types? 
  • Is it possible to reach your goal with only internal data, or would you need to enhance your corporate data with external information? 

Data Management and Governance 

Data science may provide huge benefits, but it could also be a severe liability if data security is not properly implemented. This stage prompts you to consider data quality, data protection, privacy and ownership concerns, transparency, and ethical data usage. Important factors to consider include: 

  •  How will you ensure that the data is securely stored? 
  • What is your data classification strategy? 
  • Who is in charge of ensuring that the data is correct, complete, and updated? 
  • What permissions are required to access, collect and utilize the data? 

Capacity and skills 

The greatest impediment to organizations getting much out of data is the shortage of data knowledge and skills. As a result, this is a vital component of your data plan. Consider the following: 

  •  Do you possess the necessary abilities to meet your data requirements? 
  • If not, could you teach existing employees, outsource resources, or do you have to acquire new people? 

While there are several components to a data plan, it must start with an awareness of the fundamental problem(s) that must be solved. Too often companies with small teams try to replicate what works at large-scale data teams like Google. Understanding where your organization is allows you to select the right platforms and tools to set reasonable goals and expectations. With this critical insight, you will be better positioned to maximize the value data science can give to your organization.

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