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Data Management 101 | Data Handbook Part 2/3

Data management 101 - A deep dive into data management, its importance, and its challenges for businesses.


With the tremendous explosion of raw data available across the globe, managing data silos and its complex IT challenges are more important than ever. Today, companies are capturing and saving larger data in unprecedented quantities. In order to combat these greater volumes and disparate data sources, organizations must prioritize implementing an effective data management system to gain the maximum value from their data.

What Is Data Management?

Data management is a continuous process of collecting, storing, organizing, validating and protecting data. In essence, this process manages the end-to-end data lifecycle - from inception to execution - and the progression of data to and from each stage of the lifecycle. The goal of data management is to put organizations in control of their business data regardless of where it resides.

Managing data effectively involves a broad range of tasks, policies, procedures, and practices. The practice of data management involves many interconnected factors, including:

  1. Data governance
  2. Data architecture
  3. Data modelling and design
  4. Data security
  5. Data reference
  6. Data integration
  7. Metabase management
  8. Database and storage management
  9. Data warehousing and business intelligence management
  10. Data quality management
  11. Data operations management
  12. Master data management
Data management practices

The Importance of Data Management


Having a robust data management strategy is essential to the contribution of organizational agility and growth. For IT teams, well-managed data is a crucial piece for deploying IT systems that run business applications. For corporate executives, business managers and other end-users, data serves as a valuable asset in enabling informed decision-making and strategic planning.

A lack of proper data management can hinder systems, processes, and functions within an organization. With incompatible data silos, data sets, and data quality problems come with the inability to properly run business intelligence and analytics applications and optimize the use of data. If not managed well, data can prove to be an impractical and even harmful asset to a scaling enterprise.


Data is an incredibly valuable asset in the age of data-driven business. For this reason, it should be treated as such. Take a look at the following benefits derived from executing a well-planned data management strategy:

Data Quality

An effective data management strategy streamlines consistent and accurate data, bolstering the productivity of business processes that rely on the data for their daily tasks. Effective data management also gathers and governs data sources from multiple locations, eliminating bad data and reducing the likelihood of potential mistakes, such as copy-paste, drag and drop, and linking of documents. As a result, proper data management is crucial in protecting a business's most valuable asset for usability and efficiency purposes.


Data management offers a holistic vision and better control over the organization's data. It helps aggregate data while maximizing productivity by removing the data cleaning step prior to data consolidation. With this cumbersome step removed, valuable resources are freed up, such as IT teams who are typically tied down to iterative data provisioning tasks. By having data properly managed and accessible on-demand, organizations can share high-value data to respective business departments and accommodate to change requests without major disruptions.


Another benefit of proper data management involves time- and cost-efficiencies. As an organization's data volume increases, the process of manually processing, consolidating and editing data becomes less efficient. The likelihood of data becoming inaccurate, mismanaged and error-prone also increases, which can waste tremendous time and generate unnecessary costs. With an effective data management implementation, data becomes properly managed, updated and accessible.

Security Risks

Data is a driving force in any business operation, making the protection of data incredibly important. Data security is a vital part of data management, ensuring that key data components and sources are secured within the organization. It also protects employees and companies from data losses, thefts, and breaches.

Data Compliance

With the increasing number of data privacy and protection laws emerging, it is critical that an organization's data management strategy adhere to these set of rules and regulations. Data compliance offers the highest value opportunity and efficiency, reducing the risk of penalties, loss of reputation and impact on long-term growth.

Common Pain Points and Challenges

According to the International Data Corporation (IDC), the Global Datasphere is estimated to grow to 175 Zettabytes by 2025. Most of the challenges in data management today stem from this massive influx of data. While many businesses possess the potential to extract valuable and insightful data, most are very limited in their usability and understanding. Some of the top challenges organizations face include the following:

Sheer Volume of Data

The data-driven world we live in is continuously creating, capturing, and replicating data into our business workflows. This leaves organizations with the challenge of effectively aggregating, managing and creating value from data. However, with the right data management system, more volume means more intelligence. Companies can leverage data to improve customer experiences, enhance internal processes and create new sources of competitive advantage.

Unknown Data

The never-ending expansion of data presents a major pain point for organizations. If organizations are unaware of what data they possess, where it is located, and how to use it, they fail to capitalize on their data's full potential. Collecting data itself doesn't provide any value if organizations fail to understand how to process it. This knowledge gap leads to organizational challenges in regards to repurposing data to put it to new use cases.

Lack of Integrated Processes and Systems

When data is extracted from disparate databases, applications, and operational systems, organizations face the challenge of data inconsistencies. This is due to a lack of internal processes which helps streamline the process. In addition to data quality, the gathered data must meet the organization's internal system requirements. A lack of an integrated system can pose the ultimate challenge for organizations when migrating to a data management vendor.

Constantly Changing Compliance Requirements

Compliance regulations are complex and dynamic, requiring organizations to keep up with the pace of these regulatory issues. Organizations need to have a data management system in place that allows them to easily access and modify any data that falls under strict global privacy regulations, particularly personally identifiable information (PII). If organizations fail to protect this data, data breaches can lead to extensive costs and reputation damage.

Optimal Database Performance at All Times

As organizations continue to create, capture, store and use data, it is often easy to overlook database health. However, it is important that organizations conduct regular database checks in order to ensure optimal performance levels and prevent any setbacks in business operations.


And there you have it! A deep dive into the complexities of effectively managing data in a continuously evolving environment. As the amount of data that each consumer generates grows, so does the potential to extract valuable insights and advance organizational goals. Organizations need to be able to turn every touchpoint of the consumer journey into intelligence, especially in the data-driven world we live in today. The only way to capture these large volumes of data and unlock its benefits is through implementing effective data management practices and processes.

Make sure to check out the following parts to our complete 3-layer handbook:

Insights and updates from the Dropbase team.
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