What is Data Strategy? From Vision to Value


Summary: Data strategy is how a business chooses to leverage data to meet business objectives including data architecture, data governance, quality management, and data integration methods, as well as the goals and objectives as they pertain to data and business intelligence, and the tools and systems in place to support data science functions such as analysis and reporting.

How can your organization accomplish your business goals more effectively through better managing, analyzing, and utilizing your data? The answer to that question is your data strategy. A comprehensive data strategy includes policies, processes, and tools for effective data management and usage. A functional data strategy is essential for informed, data-driven decision making in your business.

You can utilize your data strategy to help you leverage data for a competitive advantage, boosted innovation, efficiency, visibility, and growth. Data—and the strategy that defines how you use it—underpins the success of many of some of the most effective businesses on the planet. Data strategy is now important for both big and small businesses at all stages of their journey.

Key Elements of Data Strategy

Data Governance

For data to be high-quality, reliable, and trustworthy, some form of data governance must be in place. Data governance establishes policies and procedures for data access, usage, and security, and helps ensure compliance (such as with GDPR), accountability, and data integrity.

Data Architecture

Data architecture is the design of data storage and access systems. Data architecture dictates how and where data is stored, retrieved, and organized in order to maintain efficient accessibility. Data architecture often spans data warehouses, data lakes, and cloud storage solutions (such as AWS).

Data Integration

For data to have the most impact, it must be able to move—to be accessed and utilized in a variety of ways and from a variety of applications and systems. Data integration is the process of connecting data together to break down data silos for a deep visibility within a unified view, ultimately enhancing the utility of all of the data within the system. Extract, Transform, Load (ETL) processes, APIs, and other middleware assist in integrating data.

Data Quality Management

Poor quality data leads to poor quality insights. It is essential to ensure data accuracy and reliability through some format of systemization. Data quality management is often upheld via data cleansing, validation, and data enrichment processes. High quality data is then used for accurate analytics and reliable, timely decision-making support.

Developing an Effective Data Strategy

Assess Data Capabilities and Needs

To develop an effective data strategy, the first step is to assess current data capabilities and needs. Generally, data strategies will evolve over time as a business grows. It is much easier to see trends emerge from customer buying habits when you have 5M customers than it is when you have 50. That is not to say that even the smallest businesses won’t benefit from an effective data strategy—they will, especially as artificial intelligence becomes increasingly affordable and accessible. It is never too soon to begin laying the foundation for an effective data strategy to support your business intelligence efforts.

In assessing your data capabilities, it’s also important to look at the culture of your business. Is your business culture willing and accepting of using data to drive decisions and success? VisionWrights can help you develop a data-driven business culture that enhances your investment in data and business intelligence. 

Set Clear Goals and Objectives

The next step in developing an effective data strategy is to set clear objectives and goals. This can guide efforts and make it clear which facets of data strategy will be most beneficial—whether gaining additional data sources, structuring existing data, breaking down silos, etc.

Choose the Right Tools & Technology

After, choose the right tools and technologies to support your goals and objectives and with an understanding of the data available to you. Factors to consider include scalability, compatibility, and ease of use. The right tools will make a substantial impact on the efficacy of your data strategy. Not sure which tools to use? Reach out to VisionWrights for a consultation.

Hire the Right Data Team

Lastly, as you get further along in your data journey, there will be a time to build a skilled data team. Whether you hire an internal data science team or outsource to experts, finding the right mix of talent is an important step in reaching your business goals through the power of data. See how we can help you with your data goals—schedule a call with VisionWrights.

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