Democratization of Data in Relationship-Oriented Data Analytics

In relationship-oriented data analytics — the most modern data analysis approach — the democratization of data enables the very users who run business processes to obtain insights from connected data.

Data science is a field that develops by the day. Perhaps the most important challenge to overcome in this process is making data accessible not only to data specialists and IT units, but to all users. This transformation, defined as data democratization, is largely successful with self-service analysis and business intelligence systems. But does the same “democratization” of data apply to methods defined as more “complex”?

At Datateam, one of our main goals throughout the development of all our products and solutions is that the system can be used easily by the unit staff themselves, whatever purpose it is designed for. This is not only true of our reporting and business intelligence systems. We adopt the same approach in our relationship-oriented analysis systems, which offer effective solutions for detecting unusual patterns. In this way we aim for every relevant user to combine their own experience with technology using minimal technical knowledge and support, and to reach far more valuable insights. With this approach we aim to put the most up-to-date technologies directly into the hands of the business users involved in the processes.

Relationship-oriented data analysis systems need to be able to analyse data from different sources in a connected way in order to capture hidden insights. This in turn requires a powerful technological infrastructure. Consequently these systems, perceived as “complex” by users, tend to remain in the hands of analysts and IT specialists. Having observed that enabling the business user actively involved in the process to benefit from this technology directly, and to combine their experience with it, brings great success, we allow these users to reach conclusions from connected data with Datactive.

So, How Do We Ensure “Democratization”?

Easy Access to Data

With Datactive, which queries structured and unstructured data at its source and thereby allows data management processes to be resolved in the simplest way, data becomes ready for the relevant user to evaluate. Able to connect directly to many data sources including web services, Datactive queries data across distributed systems in a relationship-oriented way with a single click and lets the user see the points of detail all at once.

Zero-Code Approach

With the zero-code approach, the user can flex the system to their needs dynamically without writing code. Users can easily add the entities and attributes whose connections they want to uncover to the system from the management panel. This process, which would normally be long and laborious, can be handled by the user in a very short time thanks to the DQL query language we developed ourselves.

User-Friendly Interface

Even though it houses many different capabilities, the user’s ability to reach the feature they need easily was one of the details considered most carefully during Datactive’s development. The advanced relationship (network) visualisation screen, and the way it lets users explore data with a single click, forms an important detail in the democratization of data. In this way many different sectors, from law enforcement to financial institutions, can readily benefit from relationship-oriented data analysis technology to detect suspicious patterns and interpret connected data.

Relationship-Oriented Data Analysis and the Democratization of Data in Criminal Investigation

The democratization of data in relationship-oriented data analytics, and opening it up to the relevant specialists, has been a turning point in its own right for crime detection. Law enforcement staff who are active in the field and highly familiar with field dynamics can combine these capabilities with powerful software to conduct far more comprehensive investigations. In this way specialists can analyse the highly varied, high-volume data they hold in a relationship-oriented way, instantly reveal hidden connections, and achieve excellent results in detecting crime.

Relationship-Oriented Data Analysis and the Democratization of Data in Financial Crime Detection

Acting through indirect routes so as not to attract attention forms the basic strategy of criminals in financial crime methods. There is therefore a shift towards relationship-oriented data analysis, the most current approach, instead of rule-based systems that fall short in detecting hidden connections. In detecting financial crimes such as money laundering, for which the compliance units of banks are responsible, the specialists of the relevant unit benefiting from these systems themselves makes end-to-end management of the process possible. To this end, Datactive RegTech Solution minimises false positives by enabling the integrated analysis of data arriving from different sources. Compliance staff can test their own experience and theories directly through the system.

In summary, we help the business user reach the most effective results with connected data in the shortest possible time. We bring the most modern data analytics approach together with the users who play an active role in, and run, the relevant business processes.