Pathways to Flawless Data Integration
Data integration may seem simple at first glance, but a lot of IT professionals know that no matter how perfect the plan, it does not always turn out perfectly.
However, that does not mean you constantly have to deal with flawed results. Done properly, data integration can be concluded with minimal errors and therefore minimal correction necessary.
Some Tips To Know About Flawless Data Integration
If you are currently tackling this problem, following are this tips:
Small Sample Size
Choose a small sample size first where you can verify the validity of your data flow. Most IT professionals jump right into the whole collection of data, tackling 1 terabyte of information at a time. You will find that this not only increases the amount of waiting time, but it also amplifies the chances of error. Your best approach would be to test the data flow on that small sample size first. Does it work? If it does, then you can proceed with the next steps!
Trim the Data
Some data contents such as string manipulations are unnecessary and can only add weight to the process. You will find that trimming these down can speed up results without really affecting the accuracy of said results. No need to trim the complete data immediately: just do this on your sample size and observe.
Split Complex and Parallel Data Flows
Much like in mathematics, data flows should be seen as a group of small data rather than a large collection of information. When confronting complex and parallel data flows, you therefore have to split these into smaller and more manageable categories. The great thing about this is that you can run them independent of each other, therefore making it easier for you to catch problems. Keep in mind though that this might not always work so it’s best to have backup.
One important thing to keep in mind is that data integration is no longer as clear cut as it used to be. There are different categories of DI such as analytical, operational, and more. The good news is that there are numerous tools that can help organize all the information quickly, efficiently and accurately. As an added bonus point, most DI’s today rely on core values – which means that specific tools are no longer necessary for specific types. Simply choose software that works for you and run with it!
Be Careful When Joining
This cannot be stressed enough – you don’t want to join data haphazardly since one mistake can reverberate throughout the DI process. Also keep in mind that there are different types of joining and choosing the best one can improve or completely ruin dataflow. Be aware of the impact of merge, replicated, skewed, etc. joining before use.
It can be tough at first, but like all IT practices, data integration becomes more definite by following a specific protocol. Make sure to establish these habits for every task you make and perhaps add a few more as your expertise increases with the tax. Following the right steps, you’ll find yourself getting definite and usable results in the morning!
Image: Bob Mical via Flickr