Integrating Data in the Age of SaaS and Mobile Apps

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Back in the 1980s, there was a vision that there would be an all-encompassing enterprise resource planning system. There would be a one-stop destination for all things IT and business-related. These monolithic systems were going to be able to maintain a single place with all the critical data, and reporting could become centralized. This was the way of the future, and it looked like it was coming true in the 1990s and 2000s when cloud data storage and the internet became a thing. However, things started to change, and today this once dream is far from a reality.

The Rise of SaaS and Mobile Apps

Today it is all about SaaS and mobile apps. These were interesting for corporations because they allowed them to have fast solutions to problems while allowing businesses to use the SaaS model. The SaaS model allows businesses to use a month to month contract, and there is no need for IT people. This type of system eventually leads to a significant increase in the number of apps a business was using.

In today’s business market, a majority of businesses have become SaaS driven while almost a quarter of businesses use just SaaS apps. This has become a problem because a majority of the companies do not realize that they are using so many apps. This problem has become worse because the business’s SaaS app ecosystem is always changing. Most SaaS subscriptions have no owners and are still being billed or have been duplicated within the business. This causes a majority of companies to have apps that overlap and are not being used to their full potential.

Are Monoliths Still Relevant?

This has led many to wonder where these monoliths of the 1980s go and if they are still around today. When it comes to business applications, these monoliths are struggling to stay relevant in the ever-changing business world of today. However, when it comes to HR management and customer management, these monoliths have been able to stay relevant. Part of the reason they have stayed relevant is they are paired with data-driven business insights.

Unifying Data and Systems With ETL or ELT

Today, businesses are trying to have a uniform picture that includes all the apps and different systems they are using. This starts with extract, transform, and load (ETL) as a potential fix to unifying data. These have tried to become a collection of technologies, processes, and rules that businesses should follow to consolidate, integrate, and harmonize the data. However, because businesses live in a fast-changing environment, the traditional home-grown ETL processes have become hard to run. These have become hard to run for several reasons, starting with there has been an explosion in the number of sources that data can come from. These platforms have also been moved to the cloud. These home-grown ETL’s have the potential to create bottlenecks when it comes to gaining insights from the data.

There have been efforts from major tech companies such as Amazon, Google, and Microsoft to make analytic based databases to centralize all of this information. There has been some good with these efforts because they have brought improved performance. However, due to the many apps in companies’ ecosystems, there is still engineering work that has to be done. While these tech giants try to figure this out, there have been smaller firms that have been using new tools and approaches to tackle these problems. These small firms have been able to make scalable data flows that can make business intelligence at almost real-time, and they can cost significantly less than the home-gown ETL’s. This has lead to companies asking more questions about when they should make the transition from in-house to third party services and what your is your companies team’s time worth.

The Cost of Developing In-House Vs. Third-Party

The first place to look at when it comes to finding the cost associated with your team’s time is to look at what it would cost for a data engineer or data warehouse expert. It may cost some businesses $150,000 when you include their salary and benefits. If these people work 2,080 hours in a year, this can cost your businesses $72 an hour for the labor of internal data development and management. For most companies, they would need to append 100 hours on managing, monitoring, and troubleshooting the individual integrations. This means it can cost around $7,200 for these connections, and if you are taking data from several applications, the cost can start to add up. This may prove to become too costly for some companies to keep everything in-house. However, some solutions can perform similar tasks, and they operate at a fraction of the cost. Lo and behold, we are one of them. Enabling our clients to run full featured Business Intelligence solution with Data Warehouse, ETL, API Integrations and Data Reporting suite, we save out clients over 250,000/year in what would have cost to run a similar system in house. And we remove headaches for our clients before they become major headaches of dealing with infrastructure issues. Few click of a button is all it takes to launch!

Reach out to us to give it a shot!

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