5 ultimate enterprise data management best practices

Enterprise Data Management System

Enterprises have access to a lot of data, which can be both good and bad. The data can give us remarkable insights that you can use to power business intelligence. If data isn’t managed well, it can become a wasteful expense that costs more to store and process.

Enterprise Data Management is the only way to stop this from happening and take charge of the data (EDM).

Modern data has become a solid base for building a successful business.

A prime example of this is that almost all Fortune 500 (98% of them) companies use data to enhance customer service and experience.

So it makes sense that they are on top.

And, it’s not enough to collect the data.

You need proper management to get the most out of it and ensure your business is constantly growing.

What is Enterprise Data Management (EDM)?

At first glance, EDM might seem like a way to manage all your business data. But in reality, EDM is also about managing the roles and responsibilities of the people in the business when it comes to the business’s data.

EDM is also about how your business controls, defines, stores, processes, and uses data to improve the business.

Today, data is essential because it can make or break a business.

There is much competition in industries and markets.

In these kinds of environments, businesses that do well are the ones that know how to manage their data well and use it to make better decisions and build business intelligence.

Why is Enterprise Data Management important?

Because it’s now a need for success.

EDM ensures all the data is in one safe place where employees can get to it to do their daily work.

It improves the quality of useless raw, unstructured data that can even become a liability.

But when you use tools and software to manage data and follow best practices, you improve the quality of the data.

So, it will have an even more significant positive effect on the business.

5 Ultimate Enterprise Data Management Best Practices

A. Data Governance Best Practice

Data governance is creating policies and guidelines to manage enterprise data.

It includes setting storage, access, usability, security, and management standards.

Data governance is often put in place to meet government or industry rules.

Many organizations have seen the benefits of data governance and are using it even when it’s not mandatory.

Set strategy and goals for your data.

Why do we need all this information? You need to know what you will do with the data and how it will help your business in the short and long term. Ask a few important ones, such as:

What is the actual worth of your information?
What information do you need now and soon?
What problems do you want data to help you solve?
Can your business use data to its advantage?
How do we get information, store it, and use it?

You will need a deep analysis to find the answers to these questions and have a clear plan for your goals and strategies.

Set up your metrics

Data that isn’t backed up by metrics is useless.

You only need to set up the best metrics that consider your organization’s goals. Choose the most important KPIs and work with experts to make sure the right metrics are ready.

Communicate to eliminate bureaucracy

Data governance feels a lot like red tape, but if you introduce effective communication channels, it removes bureaucracy’s pitfalls.

Define roles, responsibilities, and benefits to all involved. Define who will do what and what will be gained by everyone. Set goals that are reasonable. And make it a habit to communicate in a clear, concise way.

B. Data Stewardship Best Practice

Data stewardship is about core enterprise data management best practices and helps you use data as an enterprise resource.

It also talks about collecting, storing, processing, and managing data from a technical point of view.

Don’t limit data stewardship to IT

Companies often mistake limiting data stewardship to IT because of how technical it is.

The business should be at the center of data stewardship.

Don’t try to make IT better; try to make business better.

Well-defined goals

To improve data quality, data stewards must be given clear, attainable goals.

They need to have a say in the definition of metrics, progress goals, and how to get there.

Give data stewards a more prominent part to play.

Don’t think of data stewards as a means to an end.

Instead, give them the power to solve problems other than the one at hand and make them an essential part of the business’s goal.

Make good stewardship a way of life.

Even if data stewards have the right goals, true powers, and management support, they can fail if they see their work as a task.

By making stewardship a part of the culture, you give stewards the ability to see data as an essential tool for improving the business.

C. Best Practices for Good Data Quality

Quality of data means everything – There is a ton of data out there, but how good is it?

How much information can you use to help your business reach its goals?
How can your data help business intelligence?

You can’t move forward without making sure the data is good.

Data changes over time, so you must assess, watch, and report.

So you must monitor, evaluate, and report the changes.

Even a small change that goes unnoticed can cause a chain reaction that makes a massive amount of data useless. Make it a regular process to evaluate, monitor, and report data.

Create data parameters and metrics.

For your data stewards, analysts, and managers to be able to tell the difference between the quality of your data, the right metrics and parameters need to be in place.

This makes it easier and faster to judge quality.

Involve and educate the whole business.

Data is vital to almost every part of your business.

Why not teach everyone about quality?

Once they understand how important it is, you will see a big difference in the quality of the data they collect, process, and manage.

Choose good stewards.

The data quality will automatically improve if the right people get the right roles and responsibilities.

So, take the time to find and train good people to be data stewards.

D. Master Data Management best practices

Master Data Management (MDM) links an organization’s data to a master reference source. This eliminates wrong and different versions of the organization’s most important business data.

These practices are necessary when multiple enterprise data management platforms and systems exist.

Knowing the value of MDM

Data sources that don’t match up can cause big problems.

Even though an MDM project could solve this problem, you still have to give it value.

Assess its business value and project its return on investment (ROI) to give it real, quantifiable value.

Supplement with a sound IT strategy

The platform on which you will build the MDM project needs to be easy to use and very scalable.

So, you need the best IT solution for this.

Integration across platforms

Enterprises use different systems and platforms, and your MDM needs to work with them so that your employees can access the information.

Testing needs regulations.

Even though it starts simply, the MDM needs to grow and get more complicated as your business does.

So, you need to test the MDM to find ways to make it better.

It will also help your staff understand how to use the system.

E. Data Integration Best Practices

Data comes from many different places. Still, when we integrate it, we put it all on a single, uniform platform that can be used for analysis, processing, and management and is easy to access.

Integration is an integral part of EDM and is done with the help of many processes, tools, and software.

Make it part of your strategy

When making your EDM strategy, make sure that data integration is also taken into account because the whole EDM process is useless without proper integration strategies and their implementation.

Use technology to your advantage.

All modern technologies work well together.

You can also use these best technologies to integrate data for your business because they are the best and work the best.

End data silos

When data gets stuck in a silo, it can’t be shared, which hurts its quality and makes it harder to integrate.

So, make a list of all the data silos and end them.

Plan for the long run

Don’t think of data integration as a short-term project that will only help you in the short term.

Stay for the long haul.

Choose a tool to integrate data that can grow and change with your business.

Wrap Up

A sound enterprise data management system doesn’t have one thing that makes it suitable.

Instead, following these best practices will get closer and closer to making the perfect EDM.

These best practices have emerged after a lot of trial and error. They can help you make the most of your business’s data and turn your company into a data-driven business that thrives on business intelligence.