🥇Data management platforms: from edge to cloud

Today, for most companies and organizations, data is one of their strategic assets. With the expansion of analytics capabilities, the value of the data collected and accumulated by companies is constantly increasing. It is often mentioned that there is an explosive, exponential growth in the volumes of generated corporate data. It is noted that 90% of all data was created in the last two years.

The growth in data volumes is accompanied by an increase in their value.

Data is created and utilized by big data analytics systems, the Internet of Things (IoT), artificial intelligence, and more. The data collected forms the basis for improving customer service, making decisions, supporting operational activities of companies, and for various research and development efforts.

90% of all data was created in the last two years.

According to IDC forecasts, the volume of stored data worldwide will double from 2018 to 2023, with the total storage capacity reaching 11.7 zettabytes, and enterprise databases will account for more than three-quarters of the total volume. Notably, while in 2018 the total capacity of shipped hard disk drives (HDD), which remain the main information carrier, was 869 exabytes, by 2023 this figure could exceed 2.6 zettabytes.

Data Management Platforms: What Are They For, and What Role Do They Play?

It is not surprising that data management issues are becoming a priority for enterprises, directly impacting their operations. To address these issues, it is sometimes necessary to overcome challenges such as system heterogeneity, data formats, methods of storage and usage, and management approaches in a 'zoo' of solutions that were implemented at different times.

The result of such a non-unified approach is the fragmentation of data arrays stored and processed in different systems, and varying data quality assurance procedures. These typical problems increase the labor and financial costs of working with data, for example, when obtaining statistics and reports or making management decisions.

The data management business model should be customized and tailored to the needs, tasks, and goals of the enterprise. There is no single automated system or data management platform that can cover all tasks. However, modern comprehensive, flexible, and scalable data management systems often serve as universal software for data management and storage. They include the necessary tools and services for effective data management.

The latest developments allow enterprises to rethink data management on an organizational scale, providing a clear view of what data is available, the policies associated with it, where and how long data is stored, and ultimately enabling timely delivery of the right information to the right people. These are solutions that empower enterprises to:

Manage files, objects, application data, databases, virtual and cloud environment data, and access different types of data.
Use orchestration and automation tools to move data to where its storage is most efficient — whether in primary, secondary storage infrastructure, the provider's data center, or the cloud.
Utilize comprehensive data protection features.
Ensure data integration.
Gain operational analytics from the data.

A data management platform can be built on multiple software products or represent a single unified system. A comprehensive platform ensures unified data management across the entire IT infrastructure, including backup, recovery, archiving, hardware snapshot management, and reporting.

Such a platform allows for the implementation of a multi-cloud strategy, extending the data center to the cloud environment, enabling rapid cloud migration, leveraging hardware replacement capabilities, and adopting the most cost-effective data storage options.

Some solutions can automatically archive data. With the help of artificial intelligence, they can detect when something goes wrong and either take corrective actions or notify the administrator, as well as identify and prevent various types of attacks. Service automation helps optimize IT operations, frees up IT staff, minimizes errors due to human factors, and reduces downtime.

What qualities should a modern data management platform possess, and where are such solutions applied in practice?

The one-size-fits-all approach does not work for data management platforms. Each company has its own data requirements that depend on the type of business, experience, and so on. A universal platform should, on the one hand, provide customization for data management in a specific enterprise, while on the other hand, be independent of the specifics of the applied industry, the application area of the product built on it, and its informational environment.

Practical areas of data management (source; CMMI Institute).

Here are some practical application areas for data management platforms:

Component
Application Area

Data Management Strategy
Goals and objectives of management, corporate culture of data management, defining data lifecycle requirements.

Data Management
Data and Metadata Management

Data Operations
Data Source Standards and Procedures

Data Quality
Quality assurance, data quality framework

Platform and Architecture
Architectural framework, platforms, and integration

Supporting Processes
Assessment and analysis, process management, quality assurance, risk management, configuration management

Moreover, such platforms play a crucial role in the process of transforming an organization into a 'data-driven' enterprise, which can be divided into several stages:

Changing data management in existing systems, implementing a role model with division of responsibilities and authorities. Data quality control, cross-checking data between systems, correcting inaccurate data.
Setting up processes for data extraction and collection, their transformation, and loading. Bringing data into a unified system without complicating data quality control and changing business processes.
Data integration. Automating the processes of delivering the necessary data to the right place at the right time.
Implementing comprehensive data quality control. Defining quality control parameters, developing a methodology for using automated systems.
Implementing tools for managing processes of data collection, verification, deduplication, and cleansing. As a result, this increases the quality, reliability, and unification of data across all enterprise systems.

Benefits of data management platforms

Companies that work efficiently with data tend to achieve greater success compared to their competitors, bring products and services to market faster, better understand the needs of their target audience, and can respond quickly to changes in demand. Data management platforms provide the ability to 'clean' data, obtain quality and relevant information, transform data, and strategically assess enterprise data.

An example of a universal platform for building corporate data management systems is the Russian 'Unidata', created based on open-source software. It offers tools for creating data models and means of enhancing functionality when integrated into various IT environments and third-party information systems: from managing material and technical resources to securely processing large volumes of personal data.

Architecture of the 'Unidata' platform by the same company.

This multifunctional platform ensures centralized data collection (inventory and resource accounting), standardization of information (normalization and enrichment), accounting for current and historical information (record version control, relevance periods of data), data quality, and statistics management. Automation of tasks such as data collection, accumulation, cleansing, matching, consolidation, quality checking, distribution of data, as well as tools for automating decision-making systems are provided.

Data Management Platforms (DMP) in Advertising and Marketing

In advertising and marketing, the term Data Management Platform (DMP) has a more specific meaning. It is a software platform that allows companies to define audience segments for targeted advertising to specific users and to contextualize advertising campaigns on the internet based on collected data. Such software can collect, process, and store any types of audience data and has the capability to utilize them across familiar media channels.

According to forecasts by Market Research Future (MRFR), the global market for Data Management Platforms (DMP) could reach $3 billion by the end of 2023, with a CAGR of 15%, and by 2025 its volume will exceed $3.5 billion.

DMP System:

Allows for the collection and structuring of all types of audience data; analyzes existing data; transmits data to any media space for targeted advertising placements.
Helps to collect, organize, and activate data from various sources and transform it into a useful form.
Organizes all data into categories based on business objectives and marketing models. The system analyzes data and generates audience segments that accurately represent the customer base across a wide range of channels based on various common characteristics.
Enables improved accuracy of online advertising targeting and facilitates personalized communications with relevant audiences. Based on the DMP, it is also possible to set up interaction chains with each target segment, ensuring that users receive relevant messages at the right time and place.

The increasing share of digital marketing significantly influences the growth of the Data Management Platform market. DMP systems can quickly unify data from various sources and categorize users into multiple segments based on their behavior patterns. Such capabilities enhance the demand for DMP among marketers.

The global market for Data Management Platforms features a number of leading players, as well as several new companies, including Lotame Solutions, KBM Group, Rocket Fuel, Krux Digital, Oracle, Neustar, SAS Institute, SAP, Adobe Systems, Cloudera, Turn, Informatica, and others.

An example of a Russian solution is the infrastructure product released by Mail.ru Group, which serves as a unified platform for data management and processing (Data Management Platform, DMP). This solution allows for the creation of detailed descriptions of audience segment profiles within the platform, integrated with marketing tools. The DMP combines Mail.ru Group's solutions and services in the realms of omnichannel marketing and audience engagement. Clients will be able to store, process, and structure their own anonymized data, as well as activate it in advertising communications, thereby enhancing business and marketing effectiveness.

Data Management in the Cloud Environment

Another category of data management solutions is cloud platforms. Specifically, utilizing modern solutions for data protection within cloud data management allows for the avoidance of potential issues, from security threats to data migration problems and performance degradation, as well as addressing the challenges of digital transformation facing the company. Of course, the functions of such systems are not limited to data protection.

The functions of cloud data management platforms as presented by Gartner include resource allocation, automation and orchestration; service request management; high-level management and policy compliance monitoring; monitoring and measuring parameters; support for multi-cloud environments; cost optimization and transparency; power and resource optimization; cloud migration and disaster recovery (DR); service level management; security and identity management; and configuration update automation.

Data management in the cloud environment must ensure a high level of data availability, control, and automation of data management in data centers, across the network perimeter, and in the cloud.

Cloud Data Management (CDM) is a platform that is used to manage enterprise data across various cloud environments, taking into account private, public, hybrid, and multi-cloud approaches.

An example of such a solution is the Veeam Cloud Data Management Platform. As the system developers claim, it helps organizations transform their approach to data management, provides intelligent automated data management, and ensures data availability across any applications or cloud infrastructure.

Cloud data management in Veeam is considered an integral part of intelligent data management, ensuring data accessibility for businesses from anywhere.

The Veeam Cloud Data Management Platform allows modernization of backup processes and the abandonment of outdated systems, accelerates hybrid cloud deployment and data migration, and automates data security and compliance.

The Veeam Cloud Data Management Platform is a "modern platform for data management that supports any cloud."

As can be seen, modern data management platforms represent a sufficiently broad and diverse class of solutions. They are united, perhaps, by one thing: a focus on effective management of corporate data and transforming a company or organization into a data-driven enterprise.

Data management platforms are a necessary evolution of traditional data management. More and more organizations are moving data to the cloud, and new challenges are arising in the growing number of various local and cloud configurations that need to be addressed in terms of data management. Cloud data management is an updated approach, a new paradigm that expands data management capabilities to support new platforms, applications, and use cases.

Furthermore, according to the 2019 Veeam Cloud Data Management Report, companies plan to integrate cloud technologies, hybrid cloud technologies, big data analytics, artificial intelligence, and the Internet of Things more deeply. The implementation of these digital initiatives is expected to bring significant benefits to companies.

Businesses are rapidly adopting data platform technologies and are ready to leverage the cloud for analytical workloads; however, many encounter challenges in utilizing all their data to achieve better business outcomes, according to analysts at 451 Research. The latest data management platforms will help businesses navigate complex processes of working with data across multiple clouds, utilize data management tools, and perform analyses regardless of where that data resides.

As we strive to keep pace with the times and focus on the wishes of our clients (both current and potential), we would like to ask the Habr community if you would like to see Veeam in our marketplace? Ответить можно в опросе ниже.