Migrating to Power BI from Legacy Systems: Challenges and Solutions

Businesses have a large flow of data and information that needs organization. Often, this is not something that manual bookkeeping can achieve on its own. This is where business integration and data modeling come in.

This is done by employing graphical representations, data modeling concepts, symbols, and texts to represent your data figures as your business decides how the information that flows in is used and when the BI solutions become an exercise in understanding and clarifying your data requirements. 

How do you migrate from legacy systems to a power BI model?

Power BI migration occurs when you transfer and integrate reports, data, storyboards, and dashboards from other places to Power BI platforms that use the Power BI environment for its data representation and visualization.

Power BI migration is necessary because it enables organizations to make the most of their business integration and data analytics processes. They choose the best-fit equipment and tools to meet what is required from the new work at hand. 

How are legacy systems decommissioned?

When you’re moving all the data and information from your previous model to your new Power BI, thorough preparation is necessary. This involves archiving any and all legacy reports and boards, removing unauthorized or redundant access to the previous BI platform, and being thorough with compliance or data preservation requirements. Informing your team about the decommissioning process is also crucial to make sure the team has adequate access to the craves of historical data and reports as and when necessary.

What data modeling techniques can be implemented instead of legacy systems?

It is safe to say that data modeling, though power BI, is not a singular process. Depending on the type of data and information that you’re dealing with, you could have to change the process of organizing said data. Let’s look into some of them:

Conceptual data modeling

This form of modeling explains the overarching hierarchies of your company and all the information that flows through it. This is mostly used for sorting through business ideas. 

For instance, if you have a customer, workers, and data about a product, each of these data buckets is termed an entity. Each entity enjoys a unique relationship with the other identities in its surroundings. This relationship is established through conceptual data modeling.

Logical data modeling

Once the conceptual data model is done, the logical model comes next. The aim of this type of power is to establish the connection between the individual attributes that each entity has. 

Physical data modeling

This involves taking the facts and information used in the logical data model for the purpose of database administration and development. It is developed for a highly specific database tool and storage technology. 

Wrapping Up

This brings us closer to some of the ways in which you can decommission legacy systems and overcome any challenges that come with migrating. These are the basis for organizing and saving all the data flow that occurs every day in any business.