Today, data impacts all sectors; all companies are confronted with data management challenges, in one way or another. In spite of these observations, most of them are still struggling to really transform their enterprises into data-driven organizations. One of the reasons why they do not succeed is that they are often faced with complex and time-consuming information systems, which represent a real obstacle for their digital transformation.
Indeed, few organizations are able to truly find their enterprise data, especially if their data ecosystem includes different formats, sizes, and varieties of data. Moreover, it is difficult to interpret them, or even to know if they are of quality when they are poorly, or simply not, documented.
In this article, we share some best practices so that companies can find the keys to start their digital transformation through data discovery.
Rethink your corporate IS
For many years, data and data management challenges were reserved for “Tech Giants”, such as GAFAM for example (Google, Apple, Facebook, Amazon, Microsoft). Being actors of the web and working mainly with digital resources, their IS and infrastructures were already thought and developed around data. It was therefore more difficult for other market players to implement new models and strategies: they were at a disadvantage!
These other organizations were confronted with technologies built on an accumulation over time. It is obvious that it is more complex to undertake digital transformation in this case.
A striking example can be found in the banking sector. While banks have been able to standardize data due to a succession of international directives, they have had to deal with new digital banks, offering much more agile and efficient services. In order to remain competitive, they realized that it is necessary to change their strategic model to stay in the digital race.
Another example can be found in the automotive sector. Buyer behaviors tend to gradually change over time, and these changes have not come unnoticed. The increased demand for “eco-friendly” travel through the use of bicycles, access to VTC services, or shared mobility with the increase in carpooling. These facts mainly show that the mobility market is changing. Demand is no longer based on the acquisition of new goods but rather on the mobility services made available to them. Thus, in order to remain competitive and meet the expectations of their users’ new behaviors, automotive market players must diversify.
Getting the right data solutions
In order to meet the needs of data users, it is essential to equip your data teams with the right solutions. This means answering the question: which cross-functional technologies across all the company’s silos need to be deployed in order to have an agile configuration? To do this, IT resources need to be organized to cover three main stages:
- data discovery,
- the preparation and transformation of these data,
- the consumption of these by the different departments of the company.
For more information on data discovery, here are detailed articles:
These three steps are essential to start its transformation to a data-driven enterprise.
On the one hand, they help implement appropriate security measures to prevent the loss of sensitive data and avoid devastating financial and reputational consequences for the company. On the other hand, it enables data teams to drill down into the data to identify the specific elements that reveal the answers and find ways to show the answers.
All this with a data catalog
At Zeenea, we define a data catalog as being:
“A detailed inventory of all data assets in an organization and their metadata, designed to help data professionals quickly find the most appropriate data for any analytical business purpose.”
With the help of a data catalog, both data teams and managers will be able to start their digital transformation based on their company’s data.
Choosing Zeenea is choosing:
- An overview of all of an enterprise’s data assets through our connectors,
- A Google-esque search engine that enables employees to intuitively search for a dataset, business term, or even a field from just a single keyword. Narrow your search with various personalized filters (reliability score, popularity, type of document, etc.).
- A collaborative application that allows enterprises to become acculturated to data thanks to collective knowledge, discussions, feeds, etc,
- Machine learning technology that notifies you and gives suggestions as to your catalogued data’s documentation,
- A dedicated user experience that allows data leaders to empower their data explorers to become autonomous in their data journeys.
Learn more about our data catalog
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