Home SAAS Four simple steps to maximise worth from SaaS app information

Four simple steps to maximise worth from SaaS app information

4 easy steps to maximize value from SaaS app data

Learn how to make your cloud app data available for reuse in the apps and systems your users want.

Almost every company today is dependent on cloud or SaaS applications. From CRM and ERP to e-commerce and marketing automation apps, this is where business takes place and decisions are made. So it might come as no surprise that 97% of companies are using SaaS applications, according to Gartner, or that business users want to leverage SaaS data in their own systems for analytics, machine learning and AI training datasets, customer support, or product development.

This explains why companies are increasingly aligning their SaaS application data to be ingested and integrated into their entire DataOps ecosystems. However, doing this in an efficient and effective way can be difficult and costly, especially if you are using APIs to access data stored in the vendor’s app. Fortunately, there are concrete ways to make it a lot easier and cheaper.

Started

Before you can extract value from your data, you need to figure out which downstream users want to use which data. With a hyper-converged app like Salesforce, there is customer support, marketing, fulfillment, business intelligence, IT, product teams, and others who want to use that data in their organizations. Create a data usage map in your company to send the right data to the right users. Then add frequency requirements for each type of data consumer. This indicates how detailed the data should be.

For example, system administrators may need to take snapshots of data at 60-minute intervals for disaster recovery, while fulfillment teams may want to add subsets of the same data to their supply chain system every 15 minutes. Product development teams may want a real-time stream of historical data from which to run their apps.

The SaaS data value maturity curve

Now that you know what data needs to be collected, for whom, and how often, you can start integrating it into your data ecosystem for downstream consumption. For most businesses, this is a phased, four-step process.

Step 1: Back up your data

To ensure that the data your business needs is always available, you need to be in complete control of it. More and more companies are doing this by using a data lake strategy: Backing up data directly from their SaaS app in their AWS, Azure or GCP data lake. (Note: Although many people don’t know that SaaS providers store their data in their apps, most of them either don’t back up that data or offer only rudimentary functionality.)

It is much more efficient to run analysis on data in your own data lake than to use APIs to query cloud apps. Imagine plugging your data consumers into a watering hole that regularly saves a full copy of the data rather than aligning it with the API spigot. Of course, remember to capture any data that your users may need to access as often as they need it.

Step 2: archive your data

Businesses are turning to the cost and performance of apps. As the data generated and stored in your SaaS app increases, app performance decreases. To counter this, you will need to buy more memory. This works well until you hit the new capacity limit again and have to buy more.

To break out of this never-ending cycle and maintain app performance, companies can archive this data in their own Cloud Data Lake environments. This costs significantly less than the SaaS providers charge for storage. You can make this archived data available wherever it is needed for further processing without having to suffer the pain that the data is actually stored in the memory of your SaaS app. Talk about having your cake and eating it too!

Step 3: observe and navigate data changes

In this phase you begin to derive new insights from your data. To understand what your SaaS app data is telling you, you need to be able to observe and navigate changes that have occurred over time. Since you collect all your historical data in your own cloud infrastructure, you can come back at any point in time to identify trends and compare and contrast differences. You can also examine the data for corruption and other issues by monitoring abnormal deletions or overwrites and insertions.

Step 4: use your data again

Here comes the big payoff for DataOps and business acceleration. In this step, you make your cloud app data available for reuse in the apps and systems your users want. With users not tapping the data in your SaaS apps, you don’t have to worry about hitting the API limits and affecting app performance. Instead, the native cloud app data residing in your data lake is streamed directly to other systems such as your data warehouse or your ERP app. used to train AI algorithms; or added to analytics dashboards and reports. Using tokenization, you can aggregate data from various sources to get a 360-degree profile of the entity. As you analyze this picture over time, you will get new insights into patterns and opportunities, and take new actions to move your business forward.

One last word

The best news is that getting to the SaaS data value doesn’t have to be a lengthy, heavy lift. There are tools that make it easy to move from backup to reuse without burdening your IT teams or breaking your budget.

About the author

Joe Gaska is the CEO and founder of GRAX. Under Joe’s leadership, GRAX has grown into a rapidly growing application in Salesforce history. It was featured on the main Dreamforce stage and has won numerous awards, including the Salesforce Innovation Award. Prior to founding GRAX, Joe built Ionia Corporation and successfully sold it to LogMein (Xively), which is now part of the Google IoT Cloud. Joe holds a BA in Applied Mathematics and Computer Science from the University of Maine at Farmington.

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