Data is always at the core of every business and process, but data is not always perfect, and it can take time and effort to properly identify when something has gone wrong.
As working in the Cloud becomes more inevitable with every passing moment for businesses looking to grow, some features and services can benefit your business with considerable savings and ease implementation and maintenance times.
One such service is available through Azure with SQL PaaS (Platform as a Service), which takes all the heavy lifting out of managing a database, letting you focus directly on your data and the applications that interact with it.
But what about everything else that is involved with handling a database? You do not have to worry about anything else; Microsoft has you covered on this front so you can concentrate on what matters.
This includes patching and updating the back-end, additionally assisting in identifying, reporting, and taking actions on any potential threats to your business data and databases.
Azure SQL PaaS also allows you to grow as much as you need when you need it, at a fraction of the cost from your on-prem and so large it can easily handle big data without breaking the bank.
The added advantage to this model means that your data will always be available with minimal to no downtime for your applications to work at full speed, wherever you are, cutting the need to synchronize multiple databases around your business units.
One key feature for Azure SQL PaaS is the ability to use it to have it as a redundant backup for your in-house on-prem applications when moving them to the Cloud is not always feasible.
There is also the possibility of migrating all of your data through tools provided directly for Microsoft. There is no need to build special tools or perform complicated migrations that can take a large amount of manpower, money, and months to be completed.
Microsoft also ensures that backups are performed continuously, creating a robust redundancy to assist in rapid recoveries and storing them for extended periods in case you need to roll back through a considerable period of time.
Being part of the Azure services, there is an integration made available with the Azure AD, allowing for Single Sign On (SSO) and faster account handling, avoiding creating additional accounts or handling multiple user databases on-prem.
Are you interested in moving to the Cloud and moving your database information to Azure SQL PaaS? Contact us through the provided method below, and we will get back to you to assist with all your migration and integration needs.
Machine learning is a system of algorithms aimed at detecting patterns in big data and then learning from those patterns without being explicitly programmed by a human operator. These algorithms take a probabilistic, rather than a deterministic, approach to accomplishing goals. Let’s take a quick look at what that means by way of example:
Deterministic Approach
A human programs software in no uncertain terms to remind him to bring his umbrella to work if the chance of precipitation in his area is greater than 40%:
//Get the weather forecast
var chanceOfRain = myWeatherForecast().precipitationChance;
//Send the message
if(chanceOfRain > 40%){
sendEmail("Bring your umbrella to work!");
}
This approach is deterministic because the outcome is predetermined by the author of the code in no uncertain terms.
Probabilistic (Machine Learning) Approach
An algorithm crawls big datasets such as tweets about the weather, weather news, forecasts, umbrella sales, and supervised feedback (we’ll get to that later) such as, “did you bring an umbrella to work today?”: