Data Management: how it works and 4 useful platforms

Do you know the meaning of Data Management? It refers to data management services through which companies, with their strategy, can simplify work.

In recent years, more and more “data-driven” processes and services are being developed for businesses. Today, data is the key asset of various organizations.

It is clear, therefore, how designing programs and procedures for the control, protection, and enhancement of information has become strategic, if not fundamental.

We have a vast amount of information available that, if not carefully selected and interpreted correctly, can be useless.

In this article, I will explain:

  • What is meant by data management?
  • The benefits it guarantees
  • Who uses Data Management and why?
  • How to create an effective information management process?

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What is Data Management

The definition of Data Management is literally, translating from English, data management. It is the practice of grouping, preserving, and using information securely, efficiently, and economically.

The data is an intangible asset from which organizations can benefit and derive value. In a world populated by data, it is crucial that everyone handling this information can use it correctly, following policies and regulations.

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Data Management systems are created for these purposes, they allow not only data protection, the true corporate capital but also its management, essential to get benefits.

The objective of Data Management is to optimize the use of personal and business data within the limits of policy and regulation so that effective decisions can be made and actions taken for the organization.

In general, one can speak of a real Data Strategy that includes procedures, processes, and policies useful for managing users, administrators, operating systems, platforms, and software, i.e., the “nodes” of the network through which information travels.

Who benefits from managing data?

Data Management is now fundamental to the processes of almost all companies and organizations, especially those that are more structured.

Collection, placement, and analysis of data are essential for the success and growth of businesses. The sectors where information management is crucial include:

  • The healthcare sector, where compliance with privacy regulations and the ability to share sensitive information from multiple sources and platforms are essential;
  • The banking sector, where data protection and reliability are indispensable requirements;
  • The Public Administration, where it is vital to protect the data of citizens and taxpayers from fraud;
  • Retail, SMEs (Small and Medium Enterprises), and manufacturing that base their activities on the analysis of business results.

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Advantages of the Data Management System

Thanks to data management systems, it is possible to enhance this asset as a crucial element for achieving business objectives.

Structured data governance brings multiple benefits such as:

  • Identification, monitoring, and prediction of security risks (privacy, information loss and theft, regulatory compliance);
  • Cost reduction through scalable data management;
  • Error reduction due to data reliability;
  • Improved productivity through rapid access to information;
  • Resource savings through automation;
  • Business decision support through predictive and accurate analysis.

Therefore, Data Management is very important and can truly provide a competitive advantage. For example, an efficient and updated CRM (Customer Relationship Management), a system for organizing and managing contacts. 

It allows for identifying customer needs and adapting and personalizing communication improving engagement and creating loyalty.

How Data Management works

Today, we no longer talk about simple data management but rather Big Data Management, which involves the administration of large masses of quickly collected computer data from various sources (social channels, websites, audio recordings, video cameras, etc.).

These are valuable sources of information that companies struggle to organize and manage.

This is why specialized Data Management platforms have been created for:

  • Integration: they retrieve different types of data and transform them for use.
  • Management: they archive and process data in a storage space.
  • Analysis: done using analytics and employing Machine Learning and Artificial Intelligence.

For organizations, it is crucial to adopt procedures and platforms for the continuous integration of data and information, their analysis, and access, monitoring, and utilization. It is time to explain what a Data Management process entails.


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Data preparation

Data preparation is one of the most delicate phases of the process and involves cleaning, selecting, and transforming data acquired from heterogeneous sources.

Crucial is the elimination of incomplete or non-useful data for analysis and their transformation into the appropriate format through reordering, aggregation, and elimination of unwanted features.

This is the longest phase of the entire process, fundamental for transforming data into outputs ready for analysis.

Data access

The heart of the Data Management process is data access, which includes all actions for retrieving information from various sources and different formats.

The logic of information access must be simple and at the same time structured so that only the requested information can be obtained through specific queries.

Data quality

As information comes from multiple sources, it is crucial to certify its quality. This step ensures that the data is accurate and usable for the intended analysis objectives.

data quality analysis

Through this process, data is monitored throughout its lifecycle in the company’s system, from database access to integration with existing data to its usage.

Data federation

When we talk about data federation, we refer to the virtual integration of data without using physical space. Essentially, the virtual database retrieves data from multiple sources and converts them into a common model.

It is an alternative to physically storing data that shortens the retrieval time when a search query is entered from a front-end as if searching in a single source.

Data governance

It refers to the set of policies and standards that ensure effective data use, enabling the organization to achieve its goals in line with corporate strategies and regulatory compliance.

Data governance establishes roles and responsibilities, determining who can and should do what, how, and in which situations.

Consider the implications of introducing GDPR (General Data Protection Regulation), for example, in the management of health data.

4 Data Management Platforms

There are various Data Management Platforms (DMP) used to manage information primarily for digital marketing purposes.

These can be classified into two primary divisions:

  • Those aimed at optimizing online advertising space purchases (Real Time Bidding).
  • Those used for other marketing activities and a more business-oriented customer database management.

Among the main ones, I highlight:

Lotame: a leader in digital data management, providing information from sources such as email, websites, social media, mobile applications, CRM, blogs, and more. Targeted at marketers, publishers, and digital agencies, Lotame is ideal for increasing engagement and unifying your data. This tool lacks live (audience) reporting and can be slow to load at times.

Oracle: you can create data-rich profiles and combine first and third-party information sources, such as social, ads, media, and mobile. Great for analyzing customer data based on cookies. The only drawback of this tool is that the interface is not always easy to navigate.

Mapp: excellent for monitoring campaign performance in real-time, optimizing data distribution to marketing platforms, and, of course, connecting with customers. This tool does not offer multi-user functionalities.


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Who deals with online data management?

The complex Data Management system is implemented and maintained by various professionals, including the Data Manager.

What does the Data Management professional do? Within an organization, they are responsible for developing and managing data systems, ensuring access, analysis, and storage.

Their responsibilities may include managing incoming information, maintaining databases, user management, creating procedures, and, most importantly, analyzing data, based on which business decisions will be made.

In more structured contexts, there is the function of Business Intelligence, which conducts strategic analysis of Big Data to guide business decisions.

Conclusion and free consultation

Data is an asset for companies and represents value, but only if managed. Today, organizations receive massive data flows. Processes and Data Management platforms are essential to clean, preserve, protect, and retrieve information, using it to maximize the competitive advantage that follows.

Data management offers companies many advantages, including greater security, efficiency, and accuracy for making more certain decisions. The use of software like CRM allows for storing data and profiling customers.

To fully leverage the potential of data management, the company must define procedures and roles to optimize the use of software like CRMs for automating marketing processes.

Data must be certified and reliable, databases need to be constantly fed and updated to simplify and support business growth.

Data Management can be strategic for all businesses, from small to large multinational corporations that can gain significant advantages. Want to know how to apply it to your company?

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