If you have already used a tool such as Power Bi and struggled to extract significant reports from your databases, you will know the frustration of having a well-designed system for certain tasks but not flexible enough to do everything you need.
You know that your system contains the desired data. All you want to do is extract it. Why should this be so hard? This usually comes back to the way your database has been designed.
The typical database design is optimized to avoid duplication and optimize data integrity. This is a great way to produce a compact and high integrity database that works quickly and reliably.
The problem is that this configuration does not lend itself to the report. And although this may not be a problem at the beginning of the early stages of your database, it will become once your system matures.
As for most companies, you probably collect more data all the time, which has an ever-increasing challenge: if your systems are not oriented for effective reports now (and they are probably not because they have been optimized. With a different objective differently) So, how will they face when you try to report on 10 × or 100 × data in the future?
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The short answer is that you will not be able not to think about remodeling the data in a way that supports a better statement.
When we help customers report projects, we will "impregnate" their databases to reveal views of the underlying data.
But popular report tools such as Power Bi are not constructed to do this untired. When confronted with a complex database with highly standardized form, bi power and similar tools are likely to fight.
As with most things, when a task - like data extraction for the declaration - seems particularly difficult, it is often a sign that you use the wrong tool.
This does not mean that there is something wrong with the bi power as such, only that it is not designed to do the heavy lifting it would need to make good relationships from bases highly standardized data.
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Although the design of a database would aim to avoid duplication of data (as is ineffective for operating purposes), these double duplicate import from a statement.Our approach to the best declaration
So, how do we manipulate things when the objectives of the original database design are not aligned with what is optimal for the declaration? The answer is that we make it easier to report by going up the data.
This means that we put in place data pipelines to extract the data, then use a modern evolutionary data warehouse to support data reports and analyses to make sense of this data.
In an ideal world, we would do it as soon as possible. In practice, we are often introduced when an application has already been built and our client wants to start executing reports.
As mentioned above, the declaration does not generally constitute one of the main considerations when the first creation of applications and databases. Customers who think of such early requirements tend to have fewer headaches with reports than their mature systems.
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If you have trouble extracting data from your systems to perform the reports you need for your business, we can help you. get in touch to talk about how our approach to modern data reports and analyzes can give a better overview of your business.