Business decisions are easier to make when you have the data insights to back them up. Unfortunately, setting up a new analytics project to extract these insights from your data can be expensive. Hiring analytics staff, setting up a data warehouse, and determining your requirements ahead of time can all be particularly costly.
In the second part of our new blog series,
Data Hurdles [read
part one], we run through some of these costs and how SAP Data Warehouse Cloud can save you money.
I WANT TO MAKE BETTER DECISIONS
It makes sense that you'd want to see the latest data before you decide where to invest next quarter's marketing budget. For most companies, it shouldn't be a problem to find basic information like the cost of each marketing channel compared to last year. However, when you want to dive a little deeper and start combining data from different departments, like sales or product development, things can get tricky.
How is social media affecting your sales, and why isn't this product performing as well as you thought it would in a specific demographic? With these questions, you'll need data from multiple departments, it will need to be visualized, and it needs to be predictive. In the end, you want a complete picture of your business, now and in the future.
So why isn't this information readily available? Most companies are collecting the right data, and they are accumulating a lot of it. With some estimates saying that there will be
175 trillion gigabytes of data being created and collected by 2025. The thing is, collecting data isn't very difficult or costly, but managing it and extracting insights can be.
WHY IS IT SO EXPENSIVE?
Historically, starting a new analytics project was expensive. You needed skilled employees like data scientists, modelers, analysts, and of course, IT to set it all up. The cost of these qualified employees has only increased because companies are collecting an incredible amount of data, and they need people to analyze it.
Once you have the staff, then there is the cost of setup and maintenance for the on-prem data warehouse itself. The high upfront cost, since everything is installed locally, means you will have to invest time to understand your storage requirements before you start the project. To calculate your computing needs, consultants will come in to estimate, often months in advance, what your new project will require. If you miscalculate your initial storage and computing resources, it can be quite costly to upgrade later on. Then if you want to add new features, like analytics and visualization tools, you need to pay more.
Finally, you might need to pay several different vendors for each aspect of the data journey from mining, cleanup, loading, management, to analysis.
HOW DOES SAP SAVE ME MONEY?
SAP Data Warehouse Cloud cuts the cost of setting up a new analytics project in a few ways:
First, SAP Data Warehouse Cloud is a cloud SaaS product [read
On-prem or cloud for more information]. This means it doesn't require setup or installation, and SAP, as your SaaS provider, will take care of updates and maintenance. The cloud gives you the elasticity to distribute computing resources efficiently to save money as needed. If your computing or storage needs change, the cloud can be quickly scaled up, down, or even suspend.
Second, SAP Data Warehouse Cloud is an end-to-end data product with built-in analytics, so it spans the entire data lifecycle. So you don't need other products or vendors. It is, however, a flexible product. It works with any data source, and although it comes with analytics built into it, you can use any tool you wish.
Third, you can save staff resources by empowering business users to do more themselves. SAP Data Warehouse Cloud is an enterprise-grade product. In other words, IT and business can both use it. Business users will be able to connect, model, and visualize data themselves with the native SAP Analytics Cloud integration. At the same time, IT users get robust security and governance functionalities. IT can make sure everyone gets the memory and computing power they need with simple resource management.
