Almost every business has taken advantage of a diverse assortment of data-driven tools, resources, and platforms. Businesses try to leverage the modern data stack to get the most out of their data, but this doesn’t always lead to actionable insights. For many businesses, all of this work and effort sometimes turns out to just be a data report card of sorts. The other glaring issue with data-driven solutions is the lack of critical data accessibility between teams. Nearly every business has an advertising team, a marketing team, and a data team, but certain teams can’t even access this data and stay on the same page. Thankfully, operational analytics is the answer to this burdensome problem. Follow along as we developed a guide to operation analytics where we’ll explain what is it, why you should use it, and more below.
What Are Operational Analytics?
Analytics has been around for centuries going as far back as the 17th century in London. This has become more advanced and evolved into traditional analytics for business. Traditional analytics brings data together into one central location where they are visualized, so they can be studied and analyzed. Traditional analytics give business leaders a 360-degree view of their customers and gain strategic insight. Operational analytics is the process of preparing, measuring, and using data as soon as it enters your data warehouse in real-time. This process helps you sync data from your data warehouse into popular tools such as Hubspot, Salesforce, or Twilio. Operational analytics empower your teams, increase data visibility, and establish more effective workflows. Anyone looking to take effective action from their data reports should embrace operational analytics.
Why Should You Use It?
There are a multitude of reasons for any data-driven business to use operational analytics. Operational analytics fuel action based on the latest insights, which can be used to move the needle forward within your organization. You’re able to keep your data fresh and make timely business decisions on a daily basis. Multiple teams can analyze trustworthy data from a central hub and gain a consistent picture of what’s going on. This also helps you reach your customers and fulfill their needs as well as their desires.
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How to Use It?
There are multiple methods used to accomplish operational analytics, but it depends on what works best for your business’ needs and goals. The easiest way to implement operational analytics is through the process of Extract, Load, Transform (ETL) in order to integrate your data from a wide array of sources. These sources can include Customer Relationship Management (CRM) software, Enterprise Resource Planning Software, and any other systems you use to collect data. You can always take advantage of ETL tools such as Fivetran, Hadoop, Stitch, or Hightouch to streamline this process as well.
You can enhance your data by using Business Intelligence (BI) platform in combination with an ETL tool to get the most out of your data. This can help your teams become more efficient and get on the same page by allowing you to model, analyze, share, and manage data models. BI platforms run off artificial intelligence and information technology models. You can use BI platforms such as Domo, Oracle, Tableau, or Dundas to accomplish this. To make your operational analytics more robust, you can implement decision services to automate certain processes for your business. They’re composed of predictive analytics, business rules, and optimization technologies. For example, if someone wants to file an insurance claim, you can use decision services to automate this process to save time and money.
Benefits
Operational analytics feature a large number of benefits that are useful for your teams, business leaders, and your customers. They help you streamline the areas of your business that have time-consuming processes in place. Your business can allocate time to other worthwhile tasks, and help your customers get what they need on a more frequent basis, which improves your bottom-line overtime. Another great benefit is the competitive advantage you gain. Cognitive computing helps you understand your data more thoroughly and stand out from the competition. Operational analytics aid in making more intelligent decisions and rely on data you can take action on. Your employees will become better engaged through the increased accessibility of data. Every team can work more efficiently and seamlessly as a unit rather than separate entities.
Conclusion
The modern data stack is beneficial for businesses, but can seem like a bunch of useless data points if there’s no action gained from insights reported. Operational analytics can help businesses take immediate action and get their teams on the same page. This is most easily accomplished through a combination of ETL tools and BI platforms. Operational analytics comes with a host of benefits including streamlining certain processes, making more intelligent decisions, keeping teams more engaged, and improving your bottom line. Operational analytics just might be the answer to your data needs, especially if you want to take your data to the next level and keep your customers happy.
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