Utilizing Collaborative Working For Data Modelling
As many have said before, and will no doubt be repeated many times in the future, there has been a monumental increase in the amounts of data being handled by business, making correct management a critical requirement. Yet as we have seen it can be increasingly easier to fall into the trap of operating independently, a problem that has only worsened in the recent months.
Collaborative working joins individuals together into a functional team, producing a unit greater than the sum of the parts.
As new data is accumulated and used across a multitude of departments it is easy to end up with data silos, used by just a select few, neutralising any potential benefits gained form enterprise-wide data sharing. But through an organised inter-department team using centralised storage and processes, and aided by accessible communications channels, true collaboration can be achieved.
But what does this mean? Well with true collaboration, business teams can take advantage of a multitude of benefits, including:
- Consistency of models and reports.
- Everyone on the same page (no more “I haven’t seen it” excuses).
- Standardised formatting made easy.
- Reduced risk of redundancy.
Of course, this is all well and good for those who are making the models, but what about teams’ leaders and managers? Where do they fit it to all of this? Through the right tools (you can see the common theme here) inter-operability can be extended to multiple levels of operation, further increasing the scope for collaboration.
With team leads able to effectively track progress in both their team and in others, joint tasks become much easier to handle and much more scalable. Building a new application? Explore the current repository to see if the building blocks are already there and communicate with the modelers to discuss how it can be utilised to avoid developing the model from scratch, reducing the risk of adding further complications to your data processes.
See the latest version of erwin Data Modeler in our upcoming webinar and have the chance to raise any data modeling pain points, including those around collaboration.