Data Strategy Unleashes Enterprise Data’s Potential
Data has the potential to drive smarter decision-making, reduce risk, increase productivity, and create new revenue streams. But that potential will remain untapped without a data strategy to guide it. A data strategy enables you to unlock the power of enterprise data, ensures you’re using resources efficiently, and assists with security and compliance. This article shares the benefits, goals, and key components of a data strategy.
What Is a Data Strategy?
A data strategy is the collection of tools, processes, and policies that define how an organization will collect, store, manage, analyze, and share its data. You can think of it as the foundational strategy that drives all the other strategies related to data, including data management and data governance frameworks.
Why Is Data Strategy So Important?
Your organization’s data strategy, ultimately, will support its business goals, enabling you to overcome challenges and take advantage of opportunities. A data strategy offers many benefits, but here are several of the most significant.
Manage the increasing volume of data
Today’s companies are generating more data than ever before, from SaaS applications, social media platforms, mobile devices, IoT, and more. The sheer volume of data that organizations must manage requires a data strategy that ensures data is both protected and available for use.
Get data into a useful form for analysis
According to EY, 81% of companies agree that data should drive all decision-making. But, as noted by Leftronic, most only analyze 12% of their data. Various types of data are coming from many different sources, and data wrangling can be challenging. A data strategy provides a roadmap for getting data into a form that business teams can use.
Improve collaboration
Smart decisions aren’t made in a vacuum. Teams must collaborate both within and outside the organization to ensure they have a full picture supported by a variety of perspectives. Your data strategy lays out a secure path to productive and efficient collaboration. For example, it will ensure data can be easily found by establishing rules for naming element data and by laying out a method for referencing and accessing metadata.
Inform data governance
An important component of a data strategy is data governance to address both data integrity and data security. Data governance defines who can take what action on what data, in what situations. It also outlines the processes, roles, policies, standards, and metrics for ensuring effective data management throughout the data life cycle.
Use resources efficiently
Because data strategy is organization-wide, it improves data management across the entire company. It helps ensure that all teams have access to the data sets they need in a centralized repository, that efforts aren’t being duplicated, and that teams can benefit from one another’s work.
4 Key Components of Data Strategy
While there’s no one right way to craft a data strategy, and each organization will have company-specific requirements, four broad categories cover the essential components.
1. Goals and objectives
Make sure the goals and objectives for your data strategy support your organization’s overall business strategy. For example, if your business goal is to have your domain experts use data in daily decision-making, your data strategy goals might include getting all data into a central location to serve as a single source of truth and using an extract, load, transform (ELT) process to ensure all data is available when a report is needed.
Consider both long-term goals that you’ll look at annually and short-term goals that you’ll review on a quarterly or monthly basis. This review process is critical to a data strategy that stays up to date and aligns with your overall business strategy.
2. Governance
Data governance addresses both compliance and data quality and is a critical component of a data strategy. Your data governance framework should establish internal policies for how data is managed as well as practices and plans for monitoring and enforcing those policies and practices. It will include the following:
Objective: What are your goals related to data quality, data security, and privacy?
Strategies: What are the systems, policies, and procedures you’ll use to address each objective?
Enforcement: How will you enforce your policies and procedures without creating bottlenecks?
Technologies: What tools and other resources do you need to implement data governance, and how will you use them?
Tracking and measurement: How will you track your activity and measure your progress?
As part of data governance, you’ll need to define roles and responsibilities for everyone who uses data, including who is responsible for storing, safeguarding, and interpreting each data set. You’ll also outline the process for sharing data.
3. Infrastructure, architecture, and tools
Mapping your data infrastructure, architecture, and tools will ensure nothing slips through the cracks of governance. It will also help everyone in the organization who deals with data know where assets are located. Creating data catalogs will help users find the data sets they need. Again, storing all your data in a single platform such as Snowflake will help you manage it more effectively. Also, consider your data pipeline tools. How are you ingesting data and replicating it? How are you analyzing it?
4. Iteration and improvement
Annually, as you’re reviewing your data strategy, look for areas to improve. Where have you fallen short of your goals? What bottlenecks need to be addressed? Where can processes be sped up? What are the weak points in the status quo? What opportunities remain untapped? Identify ways that you can iterate on your progress and improve further.
Snowflake as a Foundation for a Modern Data Strategy
Snowflake’s Data Cloud creates a strong foundation for an enterprise data strategy with built-in tools to simplify data management and governance. Last year, Snowflake launched a partnership with Deloitte to empower organizations to leverage Deloitte’s experience executing data-driven modernization and digital transformation projects, capitalizing on the benefits of Snowflake’s single, integrated platform in their preferred or multi-cloud environments.
Learn more about the Snowflake and Deloitte modern data strategy partnership.