Analytics are the bread and butter of your company. These numbers are what shows you how you’ve performed over a given period of time, whether it be in marketing, sales, or software development.
More than that, analytics are what allow you to predict what will happen next, either in the market or for your individual brand.
For instance, looking at your metrics for the past year, you should be able to predict what target audiences are going to continue performing well and which ones will fizzle out. You should also be able to see some notable trends in the broader market.
Practically every company in the world uses analytics of some sort. However, more companies nowadays are moving toward operational analytics.
This high-tech, automated form of data maximizes the efficiency of your company by making your analytics accurate, up-to-date, and easily accessible. There are several ways to operationalize your data, but some of the most common processes are ETL and reverse ETL.
With the process of ETL, or “extract, transform, load”, data is extracted from outside sources, transformed into a safe, compatible file, then loaded into a data warehouse. This keeps your data secure, organized, and easy to manage.
Reverse ETL is the same exact process, except backward. With reverse ETL, the data is extracted directly from the data warehouse, where it is transformed. Then, it can be loaded into a third party application such as Salesforce. This allows workers to access data in one centralized location and use SaaS tools to analyze this data.
Operational analytics can be described as the curation and inquiry of collected data to boost the overall efficiency of a business. Implementing this tool into your company’s workspace generally requires a large investment up front, due to the necessity of data analysts and engineers. However, it is a foolproof way of improving your bottom line.
This type of analytic is different from traditional analytics because it is immediately actionable. That means that any particular values that you or your company want will be input automatically.
This is done through advanced automation. Instead of spending hours digging through data manually, operational analytics point out important trends and patterns for you.
This technology can be used in a variety of ways. One common way it is used is to benefit the user experience for customers.
Operational analytics help IT firms predict how users will interact with their software. They can see which features are being used most and which ones are used least. They can see which pages are getting the most traction and which ones are getting the least.
With this information in mind, these tech specialists can make informed decisions on how to improve the user experience. Whenever there’s a dropoff in product usage, operational analytics are a great tool to figure out the cause.
Application monitoring cannot be done without operational analytics. Using this tool, developers are able to aggregate and compare real-time data from an application’s performance. Not only does this tell them how well the apps are running, it also tells them how users are engaging with the app.
Let’s give you a real-life example to illustrate how this works: imagine that your DevOps team has set an expected response time of 0.1 seconds for the software they created.
Application monitoring will allow them to record how fast the software is responding through a set period of time.
If there is a delay, they can go back in their logs to diagnose the issue. All of these perks are made possible with operational analytics.
Every application needs a database; and with that, every database needs proper monitoring.
Without proper management of your database, you are at risk of data loss or attacks from cybercriminals. With how important this information is to the success of your company, you want to make sure it’s absolutely safe.
With operational analytics, you are able to monitor your database and set alerts for any changes made to the files. You can also study how the memory space of an application is consumed, in order to predict how much space is needed for future growth.
Using these analytics, developers can measure the overall health of their software. If you want to check if your database is operating smoothly, you can do that. If you want to measure your response time, the numbers will show that to you.