Big Data for Restaurants: 3 Challenges Developers Face Today
Every single day, thousands of developers use cloud computing to build hundreds of new services and applications. And every second, hundreds of millions of people use these services to operate, collaborate and connect in their personal and professional lives. Yet, there are still whole industries that haven’t cracked the code. Restaurants included. There’s good reason […]
Every single day, thousands of developers use cloud computing to build hundreds of new services and applications. And every second, hundreds of millions of people use these services to operate, collaborate and connect in their personal and professional lives.
Yet, there are still whole industries that haven’t cracked the code. Restaurants included.
There’s good reason for the slower innovation. The restaurant industry and the systems, the requirements, tight deadlines, and even tinier teams haven’t been equipped to complete a project of that magnitude. And if they have done it, the cost was likely in the millions of dollars.
Developer Challenge #1:
High Cost of Entry
Traditionally, collecting, storing and using big data has been accomplished using popular platforms like Azure, Google Cloud and Amazon Web Services. This is an expensive approach. Operations that use these services – which are typically enterprise level – tend to do all the heavy lifting, developing their own software, building out giant internal databases and hiring teams to manage the infrastructure.
The problem is, developers in the small to midsize range have little choice but to either shell out big amounts of money on middleware (software that is used to connect different systems), build in-house systems that are not as efficient as required, or stay out of the game altogether.
Developer Challenge #2:
Data is Scattered in Silos
Developers often struggle to integrate data from various systems, which isn’t all that surprising considering most of it is siloed in systems that don’t talk to each other. So far, IT departments have relied on open API integrations or even big company movements to standardize data across the store.
Which is why, as we mentioned above, CIOs shell out the money on middleware. Unfortunately, middleware charge for connections to their API and collect fees based on the amount of data that is passing through – this is commonly referred to as an API call. The bottom line is that while middleware is on the table, an operation is sacrificing something-either incomplete data (because they settle on siloed systems) or expensive middleware).
Developer Challenge #3:
Need to Acquire New Skills
It seems like there is an infinite number of platforms and code languages to keep developers busy learning for a lifetime. Most developers enjoy a good challenge to learn something new, but for a business, too many code lines and languages can wreak havoc on the business. For one thing, it would cost an arm and a leg to employ a diverse department of developers and engineers.
In fact, it’s not uncommon for the first attempt to flop because of these roadblocks. The result is slow adoption, and an IT department that’s learning language on the fly, leading to delays and errors across the organization. Today’s big data platforms eliminate the need to use multiple programming languages so that developers can start building on a single platform that is consistent across all systems.
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