Regardless of the size of your company, you probably rely on data to fuel the decision-making process. However, dealing with as much digital information as the modern business world currently provides can get rather difficult.

Thus, to stay efficient, an organization should focus on developing and maintaining a comprehensive enterprise data management strategy. Having a coherent approach is just as important for companies that are only starting out with data management (EDM) as it is for those who have already implemented multiple intelligent tools.

That’s why, in today’s post, we’ll discuss what you should consider when creating a good enterprise management strategy and how to do it. For some, it’ll be a good refresher or a way to check if their approach is on track; for others, it will serve as a guideline to rely on when starting their own process. So, let’s get into it.

Types of Enterprise Data

Types of Enterprise Data

Broadly speaking, enterprise data can be any type of digital information your business works with. It may come from web platforms, mobile apps, CRM systems, and other software the company employs.

All this data can be categorized in three distinct kinds. In fact, it can probably be split up into more, but we’ll focus on the most popular groups — transactional, analytical, and master.

Transactional

Transactional data facilitates a company’s ongoing operations. It captures information pertaining to transactions like time, place, price, payment method, and use of discounts. In the context of insurance, transactional data may cover insurance claims, while in banking institutions, it might include information on deposits, withdrawals, or credit.

This type of data is typically stored within enterprise systems and helps automate data processing in sales, customer support, purchasing, and other departments that are focused on daily business activities.

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Analytical

Analytical data is all about values and metrics that deliver insightful business intelligence to improve decision-making. Typically, it is stored in enterprise repositories like data lakes or data warehouses, which allow for deployment of machine learning algorithms or for different types of data analysis to be carried out.

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Master

Finally, master data represents information about business entities and provides context for transactions and daily operations. Concretely, it can include details about products, customers, employees, or suppliers and partners.

Main Components of Enterprise Data Management

Main Components of Enterprise Data Management

Now that you know the different types of data that are out there, let’s move on to how it can all be managed. In simple terms, enterprise data management involves any processes that help define, govern, secure, and maintain the digital information your organization generates and works with.

Working with data can be tricky. Hence, when creating a comprehensive EDM strategy, you’ve got to consider a few key elements that will facilitate success.

Data Governance

Data governance essentially helps ensure that specific data-related activities have the right people responsible for them. It includes policies and processes that help maintain the integrity, quality, and security of a business’s digital information.

These documents should explicitly state an organization’s data guidelines as well as how, when, and by whom they are to be enforced. Overall data governance accomplishes the following:

  • Creates internal and external accountability
  • Protects user privacy
  • Helps adhere to rules and regulations
  • Encourages ethical responsibility

During the process of outlining your enterprise data management strategy, you’ll likely need to spend some time on establishing data governance. It’s definitely something that shouldn’t be overlooked.

Data Integration

In order to reap the rewards of enterprise data management solutions, it’s important to think about data integration. In essence, it means you’ve got to consolidate digital information from disparate sources and various formats in a unified repository so that it is accessible and can be leveraged.

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If you haven’t already, you might need to implement a data warehouse or another database in order to efficiently store and transform all of your data. However, this shouldn’t deter you because it is an important component of a successful EDM strategy.

Master Data Management

Master data management (MDM) sort of outpours from the integration component we discussed above. MDM is a process of ensuring that any decision-making within a company is based on the most current, “true” version of the data. It facilitates the uniformity, accuracy, and stewardship of an enterprise’s data.

Naturally, this is only possible when all the digital information is correctly integrated, duplicates are removed, and records are up to date.

Data Quality

Quality is of utmost importance when it comes to data. Incomplete or inaccurate digital information will damage the reliability of analytics and thus negatively affect your business. Moreover, it can slow down the implementation of enterprise data management software and cause project delays which only incur additional costs.

Hence, you ought to make sure any underlying quality problems are addressed when outlining your data management strategy. Concretely, your team might have to perform data cleansing, enrichment, integrity checks, and quality assurance activities.

Data Security

Finally, the last component of EDM we’ll discuss today is data security. With the regulatory landscape constantly changing and consumer demands for safety of personal data increasing, it’s crucial to ensure your systems are safeguarded well. Data must be protected at all points of the life cycle, whether it’s being stored or is in transit.

Hence, you need to consider which measures you will be implementing into your enterprise data management tools to prevent leaks, theft, or destruction. It might be worth starting with the basics like implementing encryption and two-factor authentication.

However, if you want to take it a step further, turning to innovative technologies like blockchain can also be an option. Specifically, as it allows firms to capitalize on its decentralization and cryptography aspects.

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