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Data Management and Governance: Your Path to Informed Decision-Making

By: SEI Team


Your data holds the secrets to your business’s success — uncover them with a strong data management and governance strategy.

Data drives business — it’s what provides insights into inefficiencies, keeps decision-makers informed about the state of operations, and offers a glimpse into the overall success of an organization. Yet only 37% of businesses have a strategy to effectively manage the data they collect. Without transparency into your organization’s pain points, strengths, and vulnerabilities, your business can’t achieve its full potential.

Data analytics, or the process of extracting meaningful insights from data, enables organizations to evolve, adapt, and grow amidst market shifts. But it involves more than filtering through logs of information; it’s about developing an effective data governance strategy that accounts for data quality, compliance, and security, and implementing a data management strategy that systematically collects, stores, and uses this data efficiently. Let’s explore how to unlock the secrets that lie within your data to transform it into an asset that can shape the future of your business.

Unlocking the Secrets of Data Management and Governance

Data management is the process of ensuring that organizational data remains accurate and secure throughout its entire lifecycle. This encompasses everything from collecting and verifying data to transforming, storing, retrieving, and, when necessary, disposing of it. Effective data management grants business leaders the power to make informed decisions, enhance operational efficiency, and gain profound insights into customer behavior. By excelling in data management, organizations position themselves to adapt swiftly to industry demands, maintain a competitive edge, and drive innovation.

However, a data management strategy shouldn’t be implemented without a data governance plan to support it. The interplay between data governance vs data management is crucial: data governance keeps data accurate, consistent, and valuable through a framework of policies, procedures, and standards. Without data governance, businesses may not be able to fully trust their data, which can lead to regulatory compliance issues and a greater risk of data misuse or breaches down the line.

Typically, a robust data governance strategy will include several key components:

  1. Stewardship: Individuals or teams are delegated responsibilities to maintain data quality and compliance.
  2. Policies: Rules and guidelines surrounding data handling and usage are clearly defined.
  3. Quality Management: Processes to monitor and improve data quality are implemented.
  4. Security: Sensitive data is safeguarded from unauthorized access or breaches.

The type of data you use is just as important as how you use it. Data governance distinguishes valuable, real-time data from dated and inaccurate information, and without it, data management efforts can become fragmented and ineffective. When data governance and management work hand in hand, organizations can confidently rely on their data for critical or quick decision-making, fostering a culture of data-driven excellence.

What is Data Analytics?

You have your data governance and management strategies all fleshed out — now what? How do you actually use the pools of data that your organization collects through every transaction, every customer interaction, and every operational task? You invest in data analytics to break down the patterns and trends of your data in real-time. Whether through statistical analysis, machine learning, or data visualization, data analytics tools help uncover hidden insights within datasets, which for an international organization, can become far too overwhelming to do manually.

Data analytics is strongly dependent on a great data management strategy. Excellent data management ensures that information is well-organized, accurate, and readily accessible, providing a solid foundation for data analytics. Data analytics, in turn, leverages well-managed data to derive valuable insights, enhancing business performance and innovation. Without proper data management, data analytics efforts may encounter issues with data quality and reliability, hindering the ability to derive meaningful conclusions.

7 Steps for Developing a Robust Data Management Strategy

A well-crafted data security management strategy is the key to building resilience and growing your business. But where do you start? Here’s a step-by-step guide to developing a data management strategy that aligns with your organizational goals and is flexible enough to modify during volatile market conditions.

Group of people looking at data on screen

1. Assess Current Data Capabilities

Evaluate your existing data infrastructure and capabilities by thoroughly examining your organization’s current data landscape, including data sources, storage systems, and data processing tools. By doing so, you can identify weaknesses and areas for improvement, which are crucial for informed decision-making.

You should also complete a data maturity assessment, which allows you to gauge how effectively your organization manages data and where improvements are needed. The U.S. Department of Labor offers a model you can use as a starting point, or you can use an outside source, such as SEI, specializing in data management and governance assessments for a comprehensive evaluation tailored to your specific needs. Either way, the goal is to know where your business lies in terms of data management.

2. Set Goals and Objectives

Once you’ve assessed your current data capabilities, the next step is determining what your organization wants to achieve with its data. This involves defining clear and specific objectives that align with your broader business goals. By explicitly stating what you aim to accomplish with data management, you ensure that every effort contributes to your organization’s success.

Moreover, establishing short-term and long-term milestones provides a roadmap for your data management journey. These milestones help track progress and guide decision-making along the way, ensuring that your data management strategy remains agile and adaptable to changing business dynamics.

3. Incorporate Big Data and Advanced Analytics

Big data, where vast volumes of information are pulled from various sources, presents an opportunity to gain a substantial competitive edge. By effectively integrating big data management and analytics into your data management processes, you can unlock insights that were previously hidden within the sheer volume of data your business generates.

However, the real value of big data lies not just in descriptive analytics, where you understand what has happened, but also in predictive analytics and decision-making. By harnessing advanced analytics techniques such as machine learning and artificial intelligence, you can unveil intricate patterns and trends that aren’t obvious at first glance. 

4. Use Data Governance as a Foundation

As mentioned, data governance cleans up and verifies your data so that the insights you gain are accurate and reliable. To ensure information integrity, practice data hygiene. Deploy automation tools that can help delete duplicate or irrelevant data, organize information based on predetermined criteria, and flag data that doesn’t comply with legal regulations.

Additionally, you should clearly determine who is accountable for keeping data safe and how, and grant varying access permissions to admins and general users. Regular audits and assessments should also be conducted to monitor the effectiveness of data governance practices and make necessary adjustments.

5. Consider Data Architecture and Technologies

Choosing the right technology and tools for data storage, processing, and analysis is a pivotal aspect of data management. Your data management strategy should align with your chosen technology stack, enabling seamless data operations. Explore cutting-edge tools like Snowflake — a cloud-based data management platform that offers comprehensive oversight, scalability, and intelligent automation capabilities.

You should also look into solutions that help you build and update your data architecture with ease. It needs to be well-thought-out and meticulously designed to support your data management strategy’s long-term goals. Scalability is also a key consideration here. Your data infrastructure should be capable of accommodating future growth and evolving data needs without encountering bottlenecks or hindrances.

6. Cultivate a Data-Driven Culture

A successful data management strategy isn’t just about processes and technology — it’s about people too. Make sure that all internal teams from the top down know how to understand the data they encounter. You should encourage your teams to understand the value of data and how it can drive business success.

Likewise, break down silos and foster a culture of collaboration, where departments work together to leverage data for mutual benefit. Training staff and stakeholders on data management best practices and data literacy is vital to ensure that everyone understands their role in maintaining data quality and security.

7. Measure Success and Make Adjustments

Set up Key Performance Indicators (KPIs) to measure success. These KPIs should be carefully aligned with your data management objectives and offer quantifiable metrics to track your progress. Some examples include data accuracy rates, processing times, duplication rates, consistency, and more.

But success is an ongoing journey. Just because you’ve hit all of your KPI benchmarks doesn’t mean your data management and government strategies have been perfected. In business, things can change in the blink of an eye. Regularly review and adjust your strategies as organizational needs evolve, technology advances, and trends change to keep pace with leads and refine your approach for sustainable long-term success.

Harness the Power of Your Data with SEI

Person performs data management on tablet

All businesses have data, but very few know how to utilize it to their advantage. At SEI, we specialize in helping organizations transform into industry powerhouses by reinventing how they use data. Our experienced consultants are well-versed in data & analytics, and are dedicated to providing expert guidance and solutions to transform your data into a strategic asset.

If you’re ready to harness the power of your data and take your business to the next level, get in touch — let’s explore how SEI can tailor a data management and analytics strategy that aligns with your unique needs and goals.

Talk to our consultants today and dig deeper into your data.