Welcome back to our PAW Pro Tips blog series. In the first blog in this series, we reviewed how to use targeted (asymmetric) selections to hide unwanted data in the PAW cube viewer. In this blog, we’ll look at how to create interactive map visualizations in PAW.
You may have heard about Planning Analytics Workspace (PAW), the “new” web-based interface for IBM Planning Analytics (PA). PAW is only available on PA 2.0 or greater – if you are still on TM1 10.2 or prior, we hope you consider upgrading and getting access both PAW and the new Excel add-in, Planning Analytics for Excel (stay tuned for an upcoming blog on this!).
If you know TM1 you already know it is great at aggregating lots of data and doing complex calculations in real time. But did you realize that those same capabilities make it an excellent tool for financial consolidation? As accountants well know, consolidation is more than simple summation. It requires the additional steps of currency translation (with all its subtleties including calculating the cumulative translation adjustment due to certain balances being kept at historic exchange rates and the income statement being converted at the average rate for the period), and other consolidation adjustments such as inter-company eliminations, and eliminating minority interests. All this needs to be done under tight controls and with waterproof audit trails.
Most of us can probably agree that detecting issues behind how the TurboIntgrator (TI) process is loading or calculating data is a very time consuming and tedious task. In order to have visibility into what is being processed, developers would usually resort to using ASCIIOUPUT() statements in their code, which would then produce CSV/TEXT files.
When IBM announced the termination of support for Cognos Business Intelligence 10.2.x as of April 2018, the logical consideration followed to potentially upgrade to Cognos Analytics 11. Doing nothing is not an option, as once Cognos 10.2.X reaches end-of-life, your organization would risk downtime with no options for support.
Besides spending time with my family, my two biggest passions are working in the analytics software industry and road cycling. I typically spend my time riding my bike very early in the morning, and then transition into the analytics world for the remainder of the day at work. What’s really cool is that the exercise cloud application STRAVA allows me to make this transition between riding and working. Why?....because while I love the time I spend on the bike, whether it’s an easy ride or a sufferfest , I also really enjoy analyzing my ride for 10-15 minutes after I take off the helmet. Furthermore, the analytics after the ride helps me adjust future rides as needed to make improvements.
Applications like STRAVA have revolutionized the way many of us exercise. During rides many of use a bike computer such as a Garmin to analyze distance, speed, cadence, heart rate, elevation gain, wattage etc. After the ride these statistics can be uploaded to an exercise application such as STRAVA (there are others on the market). As with any analytics project in the business world the success of a project begins with the ability to access and centralize the necessary data. With the use of the bike computer this is made really easy, and then it just comes down to providing the application to make sense of the data (in this case STRAVA).
What does STRAVA allow me to do? One, it allows for me to analyze each of my rides and my progress over time. For instance, it’s very easy for me to go back a year or two and look at the rides one year ago to see what my average wattage, speed, heart rate, and cadence was. I can then compare those stats to rides this year. It pretty easy to conclude whether I am weaker or stronger than one year ago. Second, if you are competitive like I am then you will also want to analyze how you stack up against other athletes who are riding on the same routes and segments. STRAVA allows for individuals to create routes and segments, and then every time an athlete rides that route/segment it records their speed and wattage and then ranks them. Therefore, after completing a ride if there were 10 recorded segments along the way then you can look to see if you are the KOM (King of the Mountains) or whether you have a lot of work to do in order to reach the top 10.
Finally, like any business analytics application it’s important for business users to collaborate and discuss the numbers. STRAVA allows for riders (if riders make their rides public) to collaborate on rides through 'likes' and comments. Its hard to know where you stack up against the competition if you do not know what the competition is doing. This application allows me to see how I am performing against other athletes while it allows for riders to comment on each other’s rides.
As most of us know, there is no way to improve the performance of our businesses without using analytics to understand where we have come from and what we need to do in order to improve. If we cannot understand the numbers behind our businesses then we are flying blind. If we do not know how we compare to the competition in the market then we cannot differentiate and sell unique value. I have spent my career selling and implementing the benefits of various types of Analytics Solutions in the business world, and I have watched companies transform themselves by adopting best analytics practices. Now, I know for a fact that using analytics on and off the bike has helped me become a smarter and stronger rider.
Long story short, Analytics is everywhere. It’s becoming more pervasive as it is required in the business world, and now it’s becoming easier every day to use analytics in our personal lives. Are you using Analytics in both your business and personal lives? If you are a rider, see you on STRAVA soon!!!
If you want to ride look me up on STRAVA. If you need help with Analytics at your company contact me at QueBIT (email@example.com) or contact QueBIT Consulting (www.queBIT.com or 1-800-QueBIT1).
When we build applications for our clients, we always strive for client self-sufficiency. Self-sufficient clients get more out of their applications, have more engaged users, and tend to “do more” with the application, so it’s a worthy goal for all concerned.
In this blog post we’ll discuss how you can take advantage of Multi-Threading to take your TM1 Model performance from a Prius to a Tesla Model S.
In this blog post we’ll share some of the highlights from this year’s IBM Vision conference, including a look ahead to some of the things that are either coming soon or are even available today from IBM and QueBIT.