Data Management Strategy: Everything You Wanted to Know

83% of businesses around the world see data as an integral part of their business strategy [1]. Despite this fact, many businesses struggle to manage it, with the average company losing up to 12% of its revenue due to low-quality data [2]. That’s where a data management[3] strategy comes in. With a good DM strategy, a business is better able to make good decisions and gain the necessary tools to efficiently address its operational challenges. What do you need to know about the data management strategy?

Unfortunately, there are numerous concepts and variables around data management, making it quite difficult to implement. This article will explore the key concepts in data management strategies, including some of its best practices of business intelligence services. Read on for more insight.

What is a data management strategy?

A data management strategy can simply be described as a business’s roadmap for using data to achieve its goals. It ensures that all activities surrounding data management, right from collection to collaboration, work effectively and efficiently. This way, they are more useful and easy to govern.

Source: tibco.com

 

By starting with a clearly defined objective, you are better able to understand the data your business needs to grow. The first step in identifying your objectives is identifying your business’s overall goals, the data needed to achieve the said goals, and finally, the insights needed to achieve them.

You can seek insights from various players in your organization and then use the data to build a long-term strategy that addresses specific needs in the organization.

Create sustainable data processes

Once you identify the type of data you want, you need to develop sustainable data processes for collecting, analyzing, storing, and distributing data. If your business handles data consistently, you need to ensure that these processes run smoothly and efficiently.

Clearly defined data processes can streamline your work, and ultimately act as a guideline toward your goals. The key to creating a successful data process is ensuring that all processes are user-friendly, timely, and have built-in automation wherever necessary.

Establish data governance

Data governance is a critical element of any data management strategy. As your business grows, the volume of data it handles also increases. Therefore, you need to plan on how you’re going to handle the data. Data governance enables you to handle data more effectively.

Source: imperva.com

A well-defined data governance strategy typically addresses data quality, privacy, security, ethics, transparency, access, and ownership. And a good data governance policy ensures that everyone in the organization uses data correctly. Once you implement a data governance policy, you should communicate it to everyone in the organization, not just the people involved in data management.

Adopt the right technology

You can’t implement an effective strategy without proper hardware and software. Technology is a critical component in a data management strategy because, without it, you wouldn’t be able to collect or analyze data.

When building a DM strategy, you must evaluate your technological needs for collecting, analyzing, and storing data. You also need a means for deriving useful insights from that data.

The right tech tools can streamline the flow of data through the aforementioned processes and ensure that all relevant parties get the information they need to drive business decisions.

Execute the data management strategy

Once you’ve collected all your data and have all the relevant infrastructure needed to analyze and store it, it’s time to execute your strategy. The key component of executing any DM strategy is identifying potential roadblocks. Once you identify them, the next step would be making necessary adjustments to overcome the roadblocks.

You also need to ensure your data management strategy is scalable to meet your organization’s growing needs.

Best practices for successful data management

Build a strong file naming and cataloging system

You can’t utilize data unless you find it. Similarly, you can’t measure it if you can’t manage it. Therefore, you should create a file system that is user-friendly and descriptive. Standardized files are generally easier to find, same as those with long filename formats.

Data storage

Even the most efficient data management strategy is useless without proper data storage infrastructure. For the best results, you need to find a data storage plan that works for your business. That said, data storage requires bespoke solutions since each business has unique needs. Here are a few data storage solutions to consider:

• Cloud storage
• Networked hard drives
• Optical storage
• Flash drives

You can also try the 3-2-1 methodology. It typically entails storing three copies of data on two types of storage media, with one copy stored offsite. This method allows convenient access to data and safeguards it from loss or damage.

Commitment to data culture

Being committed to data culture typically involves ensuring your business’s leadership prioritizes data analytics [7] and experimentation. This is especially vital when you need a clear strategy, budget, and time allocation to conduct proper training. Moreover, having lateral buy-ins and executive sponsorship ensures stronger collaboration across all teams in your organization.

Consider metadata for datasets

Metadata is descriptive information about the data you’re using. It includes information about the data’s structure, contents, and permissions. This makes it more discoverable for future use. If your metadata is not searchable, you might have a problem finding data a few years down the line.

You can catalog items as:

• Why the data was created
• When and why the data was created
• Description of fields
• What the data set contains

Cataloging your data in this manner enables you to establish a data linage, which then helps you to track data from its source to its destination. It also comes in handy when documenting data relationships and mapping relevant data.

Data quality, security and privacy

Now more than ever, you need a security management strategy committed to maintaining strong privacy standards. In order to build a trusting relationship with your clients, you must assure them that all their private data and information is protected. As such, you should implement secure data management processes that your employees understand.

Documentation

This is one of the most important yet overlooked aspects of data management. A well-structured documentation system [8] provides you with full context to why the data exists and how to utilize it more effectively.

The typical documentation levels in data management strategies include:

• File-level
• Project level
• Context, and
• Software used

Invest in high-quality data management software

The effectiveness of your DM strategy all boils down to the quality of the DM software you’re using. Accessing your data through manageable data management platforms enables you to find all the information you need more efficiently.

Data management platforms can also enable you to create the right data sets and data-extract scheduling that work towards your business goals. The best part about data management software is that it works with both internal and external data sets, thus enabling you to configure an effective governance plan.

With good data management software, you can also create a robust data analytics environment by leveraging the best data management strategies.

The bottom line

Data is at the core of all enterprises, regardless of size or business nature. But to fully tap into its potential and achieve business success, you should have a robust data management strategy in place. This will help you increase productivity, improve customer experience and generally make life easier for your employees.

If you need help with your data management strategy, see our business intelligence services. The Addepto team is at your service!