The art of database management can be tricky. Brandon Shopp, group vice president of product strategy at SolarWinds, gives come great advice in this blog post excerpt about using artificial intelligence and machine learning to enhance database performance across your entire Microsoft data estate.
In a world where 1.145 trillion MB of data is generated every day, the art of database management has become more important than ever. I use the word “art” because it captures a sense of the wizardry needed to effectively manage data. After all, our world is dominated by mobile devices and hybrid IT environments. Database migrations happen regularly, and data resides both on-premises and in the cloud.
All these things have brought a new complexity to database management. You need to be able to manage data wherever it is, understand database specialization spanning relational and NoSQL platforms, and more.
That’s certainly true if your agency is a Microsoft shop. Microsoft offers a wide variety of data management applications, including Microsoft Azure SQL Database, Microsoft SQL Server, and Microsoft Data Platform. Each functions a bit differently.
In this environment, you need to be able to monitor your databases in a similar manner to how you monitor your ever-expanding network. You must be alerted to potential problems before they turn into real issues that threaten productivity and good decision making, and you need accurate insights into where these problems are occurring, so you know where to target your remediation efforts.
Leveraging Artificial Intelligence and Machine Learning for Proactive Management
Artificial intelligence (AI) and machine learning have made this possible. In fact, these technologies are critical for optimizing the performance of your database because they allow you to anticipate issues before they occur.
A database management system equipped with AI and machine learning is essentially a database watchdog that gets smarter the more issues it detects. As the system collects more information about anomalies, it learns to better identify possible bottlenecks and why they may be occurring. As the system becomes smarter, it delivers intelligent recommendations on where to direct your efforts to mitigate these problems and improve performance. Eventually, the system can predict and identify potential issues, and you can examine those issues before they impact your applications.
This can be done across your entire infrastructure, ensuring your databases are optimized wherever they reside. You can map your database and applications as they move to and from the cloud and scan for performance issues throughout your Microsoft data ecosystem.
So, while database management has become more complex and trickier to handle, there are advanced tools and technologies to simplify the process. By providing their own type of magic, they keep you from having to try and juggle database performance optimization across on-premises and cloud environments. Instead, you can monitor everything holistically and, in the process, achieve breakthrough performance across your Microsoft data estate.
Read the full article in this Carahsoft blog post here.