20 July 2020

data governance strategy

Driving Collaboration Through Agile Data Management

To meet the challenges of upcoming digitalization, it’s more important than ever to more effectively integrate the notions of collaborative web and agility into the professional tools used by project teams. These tools supply information for all organizations by revolutionizing working methods and emphasizing multidisciplinarity and transversality via collaborative platforms. Down with the silos, long live transversality!

Agility is on the rise

Higher levels of corporate collaboration leads to less fixed silos and increased agility, promoting transversality and ending verticality in organizations. The ultimate goal is increased efficiency, thanks to work that is no longer done successively, but iteratively and adaptively. The exchange thus authorized erases the desire to act alone or withhold information that could prove crucial for another department. In the end, it is a collective intelligence that emerges and develops that can benefit the entire organization.

IT developers have understood this for quite some time: They offer more and more collaborative platforms to manage projects and optimize the organization of tasks. At the same time, traditional tools are adapting to changes in the work of business and functional teams.

Making data management more flexible

However, there is one area that still resists this upcoming evolution: Data management. The lack of operational governance and the absence of data mapping shared by the teams continue to maintain the technical and business silose. In essence, the techs master the modeling, storage and loading of data; then the business teams use it for analysis and reporting purposes and define the rules for exploiting this data without understanding its technical implementation. These silos are watertight, hampering good communication and negatively impacting data usage.

It is more than ever to break down these silos to allow better sharing of data knowledge and to increased agility! It’s also important to give more autonomy to the business actors to discover and explore the structures and transformations permeated on data, as they know how to get the best out of data – via self-service applications, digestible and easy to handle for non-technical people to include them in the data transformation process. These changes, in turn, will increase productivity by limiting exchanges on technical issues, controlling the risk of errors, compensating for the potential incompatibility of exchanged data, and adapting more effectively to regulations through data governance.

Faced with volatile data, companies must implement agile collaborative platforms to improve their management, processing, sharing, and use. To this end, data management is a lever that enables collaboration among forces that are still too often locked in their historical silos and opens the door to an unsuspected source of collective intelligence that creates value.

Learn even more about creating an intuitive data catalog to fit your needs! Sign up for a demo of DataGalaxy’s Data Catalog 360°, an all-in-one Data Catalog that offers out-of-the-box actionability with fully-customizable attributes, powerful visualization tools, standarized business glossaries, and AI integration to help organizations easily document, link, and track all their metadata assets on one dynamic platform.

Comment structurer une organisation Data-Driven ?

Autres articles

Data Owner: Definition & responsibilities

Data Owner: Definition & responsibilities

Data Owner: Definition & Responsibilities In the ever-expanding universe of data, every byte of information holds value. But who truly holds the reins over this data, determining its usage, access, and trajectory? This responsibility rests upon the shoulders of...