Praetura Asset Finance (PAF) offers tailored funding options such as asset-based finance, hire purchase, finance leasing and refinancing. Always ahead of the technology curve, Daryl Johnson, Deputy Managing Director, decided to deploy SAP Analytics Cloud and this is his step-by-step guide of their experience when reviewing, installing and using the solution.
The purpose of this blog is to detail the process PAF went through to review, install and use SAP Analytics Cloud (SAC).
SAC is a web-based SaaS product and operates ‘out-of-the-box’. The signup process is a simple one requiring just a name and email address to set up. Once the information is keyed in, an email is sent to the email address entered, requesting the user to activate the software by clicking on a link. Once done a second email is sent confirming activation. This contains a “Log In” link.
The user is then taken to the home screen where you can log in. The home screen shows various panels including one that guides you through setting up your first connection and model. Also at the top of the screen is your ID in the format of AAANN, e.g. ABC12.
The 30-day evaluation does not allow users to connect to ‘on-site’ data sources, e.g. universes or other databases. This requires the full version and other software to be installed. In PAF’s case this was the SAPCP Cloud Connector, and the SAP Analytics Cloud Agent. It does however allow you to connect to .csv and Excel files, including a sample one provided.
There is extensive online help to enable you to get started with the software as well as very descriptive sections on each aspect of SAC. All very impressive.
Although SAP has a great training library, my method of learning is to have a book in front of me.
I only managed to find one book on SAP Analytics Cloud on Amazon: Learning Sap Analytics Cloud, Riaz Ahmed, Packt, 2017, ISBN 978-1-78829-088-3.
The book is essentially a self-learn book with examples throughout based upon downloadable files. I downloaded the Bocage.xlsx file and started following the instructions in the book.
Creating the initial model was straightforward. I imported the file from the downloaded set of files and waited whilst the program loaded the data. I was then told by the software that it had loaded a sample of the data for me to view and change. All data showed as dimensions, mmm, odd.
The first thing to do was to convert the date column from text to a date. Now the fun began. On clicking the dropdown to change the text to a date, the date option was greyed out. I tried different columns and the same issue. Couldn’t change a dimension to a measure. STUCK!
I then tried a different approach and clicked on the Date column header. From here I was able to convert the column to a date format. Note: the dropdown of available date formats is very extensive, covering most, if not all, required formats.
I decided to re-import the data and this time had no issues as SAC converted the various data types almost perfectly. Only a date field in the format YYYYMM stumped it. I couldn’t really blame it for that!!!
Although I don’t have any latitude/longitude data, the geo-mapping function looks really interesting; I plan to geo map some of my data and have a play with this.
If you are using ‘on-site’ data, e.g. a universe, you need to download and install two pieces of software to allow communication between your data and SAC. In PAF’s case this was SAPCP Cloud Connector, and SAP Analytics Cloud Agent. As this required both technical skills and admin access, I asked my IT support company to do this for me. [Note: the connectors had to be installed on a separate server to the SAP BusinessObjects system].
Once the connectors are installed and the link tested, the serious work of creating a Story can begin.
The first step was to create a Model; “A model is a representation of the business data of an organisation.” It is a high-level design that exposes the analytical requirements of the end users. In SAP Lumira this would be the dataset created from the universe, Excel, or other input data. This is where you identify the columns of data you need to query, i.e. measures and dimensions.
There are two types of model: planning and analytical. The planning model comes with preconfigured time and categories dimensions for actual, budget, planning, forecast, and rolling forecast. Analytical models are simpler but more flexible general-purpose BI models with no pre-configured categories for budget or forecast data. The £15 per month version of SAC only comes with the analytical modelling tool. The planning modelling tool costs in excess of £100 per month. At this point in time I decided to work only with the analytical version.
I tested SAC using the Learning SAP Analytics Cloud book. This used both the sample files included with SAC and files that could be downloaded from the book site.
I followed the instructions in the book and had only minor problems where the screen layout had changed since the book was published.
Whilst import of the data happens, SAC puts messages on the screen telling where it is with the import of data. It is quite clever with the data in that it tries to determine whether something is a dimension, a measure, a date, etc. This was quite a time-saver and required me to just changes things that SAC was unsure of.
Once the model and any extra calculations were created, I then moved on to creating a Story, which is where you create the ‘canvas’ for the charts. Again, this was a very straight forward process and I had little problem in quickly creating charts of different types. Adding measures and dimensions to the charts is much easier and faster than in SAP Lumira, and there was no time lag as there is in SAP Lumira, where you are left wondering if it is actually doing anything.
In summary SAC is a much improved and better thought out piece of software than SAP Lumira. It is more stable, more feature rich, and more intuitive. I will be moving all existing SAP Lumira infographics into SAC and will develop all future needs through it. All in all a very positive experience!