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How to obtain value from big data

Business continue to get swamped by the ever growing amounts of data and it has become fundamental to create systems for data regulation, validation and storage to satisfy business demands. Our CEO Alberto Scavino discusses the subject in an interview with Business Community.

In which fields do you operate?

Irion operates in Enterprise Data Management from aggregation to integration of data, data, from quality to data implementation systems governance, even analytics and data reconciliation.

We strongly intend to contribute to the business side of things as we help clients draw value from the information they have, such as setting up reconciliation systems, define rules for data validation and certification, define a quality measurement scoring model, KPI – (performance) – and KRI (risk), Definition (performance), etc.

We have a lot expertise that enables us to help clients define and implement management reporting and sophisticated systems. From a business point of view – a reconciliation between accountancy and management data. Therefore, we have business expertise that we use as leverage to offer successful solutions to our clients.

Irion is well known in the financial sector. Are there other areas where your “know-how” can be applied?

We’ve been very successful working in the financial sector, but many of these issues are and will certainly continue affecting related fields where there are huge amounts of data to be managed. They are without a doubt industries where regulatory authorities impose very sophisticated monitoring where a few issues stand out such as GDPR, privacy, data processing and others.

We are seeing a lot of interest from others sectors, such as energy, utilities and pharma, with huge data volumes for which monitoring, navigation and analytics need to be setup. It’s not only a “trash in – trash out” but a certification and verification of data analyzed by analytics systems. The most beautiful analytics will prove to be useless if fed with non-certified and unreliable data.

What are today’s Enterprise Data Management challenges?

Today’s challenges are certainly putting together a series of data coming from very heterogeneous sources, expressed with different semantics and meaning, to aggregate and analyze it trying to give it value.

The idea is to introduce a series of competitive factors to Enterprise Data Management such as analytics by inserting model definition systems into the cycle to enable definition of models, statistics systems able to do market predictive analysis and create scoring system models rather than evaluation models.

Things are moving more and more towards Data governance and I strongly believe it very important to have a structure and complete governance system. Things are also moving towards huge date sources such as big data.

Certainly, the challenge is to have overall integrated governance of all this data that goes from common meaning definitions, metadata management, rule and certification definition, data quality policy definition and application and certification, even data publication suitable to data management.

What are the peculiarities of your platform?

Particularly, an integrated system that covers all data management system, from data creation to certificated data publication, going through transformation, organization and analytics. Usually this process is subdivided between different systems with different languages, integration problems, total data quality issues, and process accountability. When there are regulations someone would ask for proof they are being followed, therefore compliance in data management is an important topic.

Inside our platform, there are functionalities reaped from consolidated experiences in the financial sector, one of the most supervised sectors with documentation, traceability, reconciliation and natural language. These are all functionalities of our platform widely and satisfactorily used by our clients when facing regulatory controls.

Is it scalable for small businesses?

Ours is an Enterprise solution. Our target are medium size companies with an annual profit of at least 100 ml Euros. In a world where business are literally swamped by huge amounts of data, it is fundamental to create a system of rules to control, validate, store and derivative data to satisfy business demands.

Why is Market Data Validation important?

It is one of Irion’s application examples within a financial institution. Clearly, quality validation of market data used in portfolio translation, strategic decision processes or even tactical, it’s all fundamental. We are talking about evaluating and highlighting problems with supplied data from different market providers. It is sensible data to generate financial statements, with lots of profit and loss, therefore it must be certified as it is all data within the financial world.

After the US are you expanding somewhere else abroad?

Certainly, the US market is important. We also believe in the Anglo-Saxon and Luxembourg markets, the second one being a particular market territorially but also a market strongly investing on data and data infrastructure.