According to data released by the Big Data Observatory of the Milan Polytechnic , in 2021, 78% of large Italian companies adopted data integration strategies , but, of these, only 18% were able to fully reap the benefits of these strategies , proving to be competent and proactive, not only in protecting and maintaining the integrity of such data, but also in knowing how to fully exploit the information assets . It is, in fact, precisely on this last aspect that the game of digital transformation and the enhancement of the customer experience
is played , which constitutes one of its founding pillars.
But, as we have seen from the data, it is not always simple: the integration and management of heterogeneous data, coming from multiple sources, is a daily challenge: it requires trained professionals, up-to-date technological solutions and management ready for change.
Data Integration: The Keystone to Omnichannel Marketing
The term “data integration” usually refers to the process of merging and integrating data from multiple sources .
It can involve different phases ranging from data collection, to their normalization and mapping, to processing through complex systems that aim to make such data easily understandable to those who access them.
The main advantage of a data integration strategy lies, therefore, in the possibility of building a 360° vision of the customer , complete, unique and updated, the starting point for effective marketing strategies aimed at personalising the customer experience from an omnichannel perspective .
Information from multiple sources, but which data specifically?
Typically, when talking about data integration, we usually refer to five different types of data:
machine to machine data : this includes data generated as a result of the interaction between electronic devices;
people-to-machine data : this is data generated by the interaction between people and electronic devices (an example of this is data relating to online purchases);
people-to-people data : this is information generated by the interaction between people and therefore concerns more specific channels such as social networks, blogs, forums;
public admin data : these include data present in public databases and therefore available without any restrictions;
enterprise data : these are those list of angola consumer email present in company databases and data warehouses .
Improving decision-making processes, developing strategies aimed at strengthening one's competitive advantage: data, if well exploited and analyzed, today represent a real gold mine for companies but it is necessary to adopt the right mindset .
Data lake and data warehouse : from silo model to integration
If once each department and company function collected data within distinct repositories that were difficult to connect to each other, today this approach seems outdated and many companies have shown signs of openness towards models that allow the integration of data in unique environments.
In the field of data integration, we usually refer to two distinct storage models and approaches that can easily coexist.
Let's analyze them in detail.
Data warehouse : These are storage systems for large amounts of data from multiple sources. Here, the data is structured and normalized in order to make it available to the various business functions through relational databases that allow rather complex queries and searches. However, in this case, the data is not updated in real time.
Data lake: in this second case, data is collected and stored, at least in the first phase, in its original format. Data lakes allow, precisely because they store data in its original format, to collect large quantities of it.
What if the focus was on the customer and their customer journey ?
