What Is a Data Platform – and Why Do You Need One?

For decades, enterprises have maintained both systems of record and systems of engagement:

• Systems of record are foundational, mission-critical, sources of truth that are accessed primarily by internal programs and users to capture the details of undertaken business and its supporting collateral (contracts, advices, reports, statements, etc.).
• Systems of engagement are the digital interfaces with which customers and employees interact. They are useful for customer service interactions, online sales promotion, and the many interactions an organization has with its partners, prospects, and customers

In recent years, a third category of systems has emerged: systems of insight. Systems of insight are data-driven and use analytics to help organizations make better decisions. Organizations are increasingly turning to systems of insight to make decisions about everything from product development to marketing to customer service. In many cases, systems of insight are powered by artificial intelligence (AI) and machine learning (ML).

There are many benefits to using systems of insight, including the ability to:

• Make better decisions: Systems of insight can help organizations make better decisions by providing them with data-driven insights
• Improve customer experience: By understanding customer behavior and preferences, organizations can use systems of insight to improve the customer experience
• Increase operational efficiency: Systems of insight can help organizations increase their operational efficiency by identifying inefficiencies and areas for improvement
• Drive innovation: By understanding customer needs and trends, organizations can use systems of insight to drive innovation

Any high-fidelity data service needs to be able to address systems of record, engagement, and insight as a single unified data platform. This allows organizations to embrace all the information needed to gain a complete view of data on any subject chosen by any user – all within the constraints of organizational policy.

A data platform is an integrated set of technologies that collectively meet an organization’s end-to-end data needs across the spectrum of the systems discussed above. It enables the acquisition, management, storage, preparation, delivery, and governance of your data and is a security layer for users and applications. A data platform can be on-premises, in the cloud, or a hybrid of the two. Ideally it is a single-vendor solution, or it can be a combination of integrated best-of-breed technologies (although an integration-centric approach adds complexity).

The data platform can be differentiated by its ability to provide users with a complete view of the data and allow them to easily access and analyze the data. Additionally, the data platform must be able to scale to accommodate the needs of the organization as a whole.

There are many reasons to use a data platform. A data platform can help you collect, process, and analyze data. It can also help you share data with others between and across organizational boundaries.

Some common use cases of a data platform are:

• Develop data-driven contextually aware applications
• Store and manage data in all its varieties
• Analyze data across the spectrum of data types, using a single query interface
• Surface data via informed search-based applications
• Visualize data as a whole
• Report across data silos and organizational boundaries
• Monitor and manage data including its governance, security, lineage, provenance, and value
• Feed, augment, and ingest data from other data repositories, such as data warehouses, data lakes, data lakehouses in order to deliver on the mission of data quality and data security
• Clean and enrich data for use within AI-powered analytics
• Undertake object- and activity-based intelligence using what one knows about the data, rather than the data itself

The above cases are achievable if you don’t have a data platform. However, without a data platform you need to take an integration-centric approach over many different systems, which adds complexity, risk, and cost to achieve the same ends.

So, we can see the data platform as the backbone of the modern data-driven enterprise. It’s the foundation that supports all data-related activities, from data acquisition and data warehousing to data analysis and data visualization. It supports all data types, including structured, unstructured, and semi-structured data. It scales to support the needs of the enterprise, and it integrates with all the other systems in the enterprise.

The MarkLogic Data Platform

The MarkLogic data platform is a powerful and flexible single unified data resource for managing and analyzing data. Powered by a multi-model database, it offers a number of advantages over traditional single type databases, including the ability to:

• Handle complex data structures
• Index and search data in real-time
• Scale to meet the needs of large organizations

MarkLogic is also designed to be highly available and fault-tolerant, with built-in features to ensure that data is always available and consistent. In addition, the MarkLogic data platform includes features to help developers build applications quickly and easily, including an integrated development environment, a declarative programming model, and a rich set of application services.

Visit the MarkLogic Data Platform page for more information about its unique set of unified capabilities that simplify complex data and deliver data agility.