Anastasio Molano, Senior VP Europe and Middle East at Denodo, about Process Mining and Data Virtualization
Anastasio Molano, Senior VP Europe & Middle East at Denodo
Anastasio holds a PhD in Telecommunications Engineering and is an expert in data virtualization.
Anastasio Molano (Denodo):
First of all, thank you for inviting us to participate in this interview, we are happy to collaborate with technology companies of Spanish origin and also of university origins.
InVerbis: Anastasio, not many executives outside the IT areas are familiar with what data virtualization is and its advantages.
We are here to break down silos, to solve data fragmentation in companies. Data virtualization with Denodo allows us to add a logical layer to the business in a way that gives access to any data, in any format, with any degree of latency, in any location, either on-premises or in the cloud. In addition, data governance is facilitated, providing a single view of the data and a catalogue to facilitate consumption by business users.
We say the data is “virtual” because we are not storing anything, we do not move the data to a new data-lake or data-warehouse repository: instead, we connect to the repositories when users need the data.
So we always have the latest updated data, and we can manage access to that data even if there are changes to the structure of the original databases. This simplifies a lot of things, such as facilitating system migrations, regulatory compliance requiring traceability of historical data… And even being able to turn the data generated into a new source of revenue!
If all these are not obvious advantages in themselves, there is one more that seems essential to us: the time required to provide valid information to the business.
Our customers demonstrate that data integration and transformation time is reduced by 67%. InVerbis and any process mining practitioner will find this really attractive. I think it is safe to say that in an emerging discipline like process mining, data virtualization will allow it to develop at full speed.
This is certainly an argument that should, at the very least, reduce organisations’ reluctance to get started. In the same vein, one of the barriers to adoption of process mining is that it requires retrieving the digital footprint of a process that may be spread across multiple systems, so why does data virtualization, and especially Denodo, allow this problem to be solved?
As we have mentioned before, data virtualization allows the incorporation of what we can call the enterprise data fabric, a kind of layer that allows access to all data in a unified way no matter where it is located and without having to store it because we go to the last update of the data when it is needed.
Therefore, when building actionable datasets with process mining techniques, the analyst will be able to select the data he needs wherever it is and enrich it with all the necessary data that is distributed among the different systems, what you call attributes. It’s like cherry-picking what you need (which is obviously in the databases). You create a view representing the value chain you want to extract and move the data to the processing tool, while solving the problem of unifying the trace identifiers.
With two more advantages: you can update the data and incorporate it into the dataset in real time, and you have one hundred and fifty connectors covering everything the corporate market uses, including SAP, Salesforce and all kinds of enterprise solutions. And we will continue to add more connectors as the market demands them.
Denodo is a leader in its category and is in Gartner’s magic quadrant. It cannot be said that there are many companies of Spanish and Galician origin that can stand out in this way in the international environment. This, we believe, gives you a privileged position to understand the evolution of data processing and management in all types of organisations. How can you summarise the main trends?
Trends are, of course, related to the value that organisations can extract from data. In this sense, a clear trend is the concept of Data Fabric, offering agile data integration and a unified view of data as a single source of truth, improving data governance and facilitating consumption by business users regardless of their format and location, which I would say are fundamental aspects of data management today. I would also add providing greater intelligence in data management itself through machine learning and machine learning techniques to, for example, improve data access performance or provide automatic recommendations of interesting datasets to business users.
An effective data strategy allows quick and easy access to the data needed for decision making and operational prioritisation. It also reduces information access risks and lowers data management costs. And all this is achieved thanks to data virtualization and thanks to Denodo.