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Recognize the Importance of Data

Learning Objectives

After completing this unit, you’ll be able to:

  • Explain the importance of data in today’s technological landscape.
  • Describe key data capabilities that have an impact on your business.
  • Identify ways to keep data relevant and valuable.

Data Is Increasingly Important in Today’s Technological Landscape

The discovery of oil fueled the 19th-century industrial revolution. Similarly, the 21st-century digital transformation is fueled by data. Data plays a critical role in delivering exceptional customer and employee experiences. As companies embrace AI, customer-centric models, and other technological innovations, it’s increasingly important that data be accurate and available in a timely manner.

While data has traditionally been structured and maintained in enterprise resource planning (ERP) systems, the recent influx of new devices, applications, and cloud technologies has resulted in unstructured data being distributed across various locations and geographies. Integrating data with such a variety of formats and availability is addressed in the next unit. But first, let’s look at why data is important to your business.

Importance of Data and Strong Data Practices

Her are some benefits of good data and how it benefits your enterprise.

  • Decision-making: High-quality, trusted data combined with good data practices help organizations make fact-based decisions instead of feeling-based decisions.
  • Reduced Costs: Secure and compliant data ensures reduction in costs due to data breaches, non-compliance penalties, and inefficient processes.
  • Enhanced Compliance: Sound data management fosters compliance with relevant regulations, such as GDPR and HIPAA, by ensuring that data is handled in accordance with compliance requirements and standards.
  • Increased Efficiency: Good data and data practices result in more time conducting business and less time troubleshooting and chasing down the right data.
  • Improved Customer Satisfaction: With improved and timely data, organizations can provide more personalized and better customer interactions, which ultimately leads to improved customer satisfaction.

Key Data Capabilities

Legendary baseball player Joe DiMaggio said “If you take care of the fundamentals, the results take care of themselves.” This same principle applies to data and data management. If you take care of the fundamentals (for example, data lifecycle, data governance, and so on), results such as improved customer satisfaction and enhanced compliance follow suit.

Look at the data capabilities below to see how they can help manage data in your organization.

Data Capability

Description

Why does it matter?

Data Strategy

Outlining a plan to collect, store, manage, and use data to achieve your company’s business objectives.

It serves as a roadmap to use data as a strategic asset, guide decision-making, improve operational efficiency, and drive innovation.

Data Governance

Coordinating the effective development, management, compliance, and use of data assets and sharing data best practices, policies, and processes.

It strives to bring consistent standards and practices for effective and efficient management of data, leading to reduced risks and improved compliance.

Data Lifecycle Management

Creating a systematic and managed process of managing data throughout its entire existence, from cradle to grave.

It ensures that data is managed effectively throughout its entire lifespan, leading to improved data quality, reduced costs, and improved compliance.

Analytics

Processing and examining data to discover patterns and insights to support data-driven decision-making

It enables businesses to derive meaningful and accurate insights through data visualization and reporting to provide improved customer satisfaction.

Data Intergration

Combining data from various sources in a timely and secure manner to produce a unified view of data spread across the enterprise and beyond.

It provides a comprehensive view of data that otherwise was available in siloed systems—thus ensuring a well-informed business to provide enhanced customer experience.

Data Quality Management

Ensuring that data is accurate, complete, and consistent by implementing processes and tools to identify, correct, and prevent data errors.

It ensures data is corrected where it’s wrong, and it stays corrected to prevent expensive and poor outcomes, thus negatively impacting the enterprise.

Security & Privacy

Protecting enterprise data from unauthorized access, use, disclosure, disruption, modification, or destruction through the adoption of technical standards and user access controls.

It’s crucial to protect sensitive information, prevent data breaches and ensure compliance with government and industry regulations to protect the company and customer’s information.

Retention & Business Continuity

Through policies and procedures, managing the storage, access, and retention of data while ensuring critical business operations can operate with minimal to no disruption caused by data issues.

It ensures that organizations can recover from disruptions and that data is available in pristine form to continue business operations.

The above capabilities serve as guardrails as you define your data strategy. They ensure that you’re making the best use of data through all stages of data management, including inception, sourcing, management, consuming, and retiring. Chances are some capabilities are more important than others for your company and upcoming initiatives. Your goal should be to work with stakeholders to prioritize these capabilities and dive deeper into the ones that have the highest impact on your enterprise.

Keep Data in Context

While having data is good, it has to be of value to the company. Just having lots of data isn’t enough. Instead, data has to be timely and relevant for it to be valuable to the company and its customers. Here are three key strategies that can be used to keep data in context.

  • Frequent updates: There’s always be a question about how often data should be updated and made available across the company. Do it too often, and it causes a strain on your applications and integrations. Do it too infrequently and it makes data obsolete or irrelevant. The key is to strike a balance fit for your company and the use-case—and adopt relevant integration patterns to be efficient with the data updates. You learn more about this in the next unit.
  • Contextualization: Data needs to be tied together to understand the big picture. This means linking data across different applications, business units, and so on. For example, you should be able to link orders, customers, issues, invoices, and other things to provide a valuable experience to the customer. This requires building a holistic customer view.
  • Visualization: Data has to be ready to be consumed by the person accessing it. That means using the right visualization techniques and tools so that it becomes easy to understand and act on the data. To get started with data visualization, check out the Get Started with Data Visualization in Tableau Desktop trail.

Now that you understand the importance of data, key data capabilities, and the benefit it provides, let’s dive into the importance of integrations.

Resources

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