Most companies have had to adjust to the big data push. Some have learned to fully leverage data to get a comprehensive view of their business and make long-term plans for their processes. However, it can be a long way from there to fueling minute-by-minute processes with quality data.

Operational analytics allows your company to be at its most effective on a real-time basis. How does operational analytics (also called continuous analytics) offer an advantage to your company and how do you implement it?

Table of Contents:

  1. What Is Operational Analytics?
  2. Implementing Operational Analytics
  3. Using Operational Analytics
  4. Operational Analytics Use Cases
  5. Operational Analytics with

What Is Operational Analytics?

Operational analytics is a decision maker's dream. It allows you to power every choice with data: prioritizing products, messages, clients, or events and helping employees to use their time in a way that benefits their company. This is in contrast to traditional analytics.

Traditional analytics allows companies to get an overarching view of their business and create new strategies based on the data. It is a long-term process and you can leverage it to get the big picture. Traditional analytics may not change the way most employees do their work from day to day, but it does influence how CEOs direct their businesses.

Operational analytics is a critical part of ERP (enterprise resource planning) and influences employee choices in real-time. It begins with streaming data ingestion (gathering data from various sources into one repository in real-time or nearly so) in order to study and sort the data, in many cases automatically. is a data integration solution that offers both ETL and data ingestion for any industry.

Different software solutions often offer different types of individualized data processing for differing industries' and companies' unique needs.

Implementing Operational Analytics

The implementation of operational analytics can be involved and time-consuming, not to mention expensive. What tools are necessary to implement this critical BI (business intelligence) process?

First of all, you need a comprehensive ETL (extract, transform, load) solution capable of integrating data from a variety of sources. has built-in connectors and easy low-code and no-code data pipeline creation, enabling you to quickly and easily gather data for closer scrutiny.

Sources may include CRM (customer relationship management) or ERP software solutions, which gather data through your company's interactions, choices, KPIs, etc., and present that data in a way that makes it usable.

Other useful tools could be various types of testing software and traditional BI platforms. Of course, you need a repository of some kind, whether it be a data warehouse or a data lake. You will also need tools to perform validation and modeling.

If you already have a data stack that includes these different elements, you have what you need to implement operational analytics. Operational analytics makes use of these to move actionable data from its source to where you need it most.

How exactly does operational analytics work to improve your daily business processes?

Using Operational Analytics

Operational analytics processes various types of information to help employees, CEOs, and data analysts make the best business choices at the moment.

For example, companies can use traditional analytics to choose the best pricing for their product during a particular financial quarter, but they can use operational analytics to look at product usage, ratings, other offerings, and more and choose or automate pricing changes based on these metrics.

Traditional analytics often goes to reporting dashboards that you can present at meetings or that those with authority in the company can examine. Operational analytics goes wherever you need the data, allowing for added flexibility and agility in all business dealings and processes.

Chances are that you may be relying heavily on your employees' abilities to sift through spreadsheets and data instead of leveraging tools already in your toolbox. Some companies offer consulting to help you reach your full potential with operational analytics.

What are some ways that people are using operational analytics right now to improve their processes?

Operational Analytics Use Cases

The operational analytics market is exploding, and according to one source, it may be close to $30 billion by 2027. Some of the best use cases for operational analytics include pricing, advertisement, support, and mobile development.

  • Pricing is complex and ever-changing. It can change based on a wide variety of factors like customer reviews, product purchase volumes, and material quality changes. In any of these cases, adjusting to the change may take months of effort or at least hours of employee work. A good data analysis system can enable you to perform operational analytics and adjust on the fly.
  • Advertisement plans work primarily based on traditional analytics, in which case your company will have overarching advertisement campaign plans for particular periods of time. You can also adjust advertising based on immediate metrics like click-throughs and product purchases. Having all of the data immediately available to your marketing team can give you an edge when adjusting your advertising campaign at the moment.
  • Support tickets and customer complaints can flood your employees with things that urgently need to be addressed. How do you prioritize them? Use software to prioritize tickets automatically based on different metrics or products.
  • Mobile development for applications involves constant adjustment as developers receive feedback from users and information about in-app purchasing. Get the data you need when you need it through operational analytics.

Is operational analytics easy to implement? No, but the rewards can be overwhelming.

Operational Analytics with fuels operational analytics with real-time data integration. You can centralize, transform and clean data securely and quickly, build data pipelines with little or no coding, and reduce the amount of time your employees spend managing data.

Prioritizing the needs of your employees and customers helps you grow your business the most. To get started in the right direction, you need the right tools.

To learn more about how can fuel data-driven operations throughout your business, contact us today for a 14-day pilot.