In my first post, I talked about the hell of using Excel for all your data needs; in my second post, I covered the building blocks and initial first steps that will lead you to a future proof data strategy. Now let’s zoom in on the three domains that underpin
Imagine your company's analytics environment is like an old apartment building, with each unit having its own air conditioner. Each air conditioning unit has to be individually maintained and repaired by the building landlord or "super." The air conditioning units come from different manufactures and are of varying ages. It can be challenging, to
Times have changed. As the oil industry shutters and sheds investments that made sense during the two-year period in which oil rode comfortably above $90, the market is establishing a new equilibrium at $40/barrel. This despite the fact that the Baker Hughes domestic rig count is down 64 percent. It’s
You could argue that it’s misguided for someone like me to say data science doesn't have to be difficult. After all, I’ve been in the industry for many years and should have a few tricks up my sleeve for dealing with data. But with the latest data visualisation technology –
As consumers have moved to digital channels and digital interactions, competition for the hotel consumer has increased dramatically. Now, hotels not only compete with each other, but also with third-party online distributors, and even new disruptors from the sharing economy like AirBnB. However, hotels have one advantage that these other
In my previous post, I discussed some of the challenges and costs organizations face when they’re stuck in Excel hell with no real data strategy. Now that we’ve discussed the problem, let’s dive into the solution. Every organization needs a data strategy with these building blocks: Your top priority is
The holiday season is a festive time of the year. But it can also be a nail biter for retailers. Months of planning can be sidetracked by fickle consumers or aggressive pricing from competitors. Paying attention to even a little bit of data can work wonders. In October, SAS conducted
Know your data. Do a needs analysis. Organize for success. Empower users. These are four best practices for data and analytics that you'll want to hear more about. In my first three posts in the Analytics in Real Life blog series, we learned how higher education customers are using SAS and why
I brushed aside some sawdust on the workbench and set my laptop down. It wasn’t really mine. SAS Library Services had kindly lent me a new laptop for the “Making Sense of Sensor Data” workshop at UNC’s BEaM Makerspace. I had just set the laptop down…in sawdust. Like any normal
This summer, I had several interesting sessions with customers and prospects. Much to my surprise, two of them, both multinational organizations, were doing most of their data related tasks in Excel. This happens every now and then -- I come across organizations (like yours?) where people are manipulating and ‘analysing’
