We are currently living in the information age. Several devices, (mobile) applications and computer programs are generating and collecting lots of data. A lot of decisions are made based on a “gut feeling“. In a lot of cases, this will not be any problem. If you cannot trust your gut, who or what can you trust? Still, I think that your gut is based on several years of experience. Why not use data to validate your gut? It will improve your decision-making process. You do not only have your gut, which might be difficult to understand for others, but you have the figures to prove it. Sounds easy, right? Just report some figures and you are done. The real added value to the decision-making process comes when you are able to really understand the data.
Lately, we have seen several examples of not being able to put data into the right context. The public was absolutely sure that Brexit was not going to happen. Who would have thought that Trump would be the next US President? A lot of data about these matters has been collected. Still, it was not possible to predict the outcome. Some important questions can be asked. How was the complete data set constructed? Was the data set representative for the total population involved?
“A picture says more than a thousand words“. This sounds like a true statement. Our brains are better suited to process images than they are able to make sense of a table of figures. But what does a certain visual tell you? What does it exactly mean if we see a decrease in sales for the year 2016? It is not enough to make decisions solely based on the output of a chart. It is the story behind the chart that counts. If we had known the weather was bad in June 2016, we might have been able to explain the drop in ice cream sales in that same month. Being able to visualize the data is one thing. Applying context to the visual is key to make the right decisions.
“Drive change by converting Data into Insight”
If we want to stay ahead of our competition, we need to do things differently. This means the organisation has to change, as in doing things differently and better. Better than last time and better than the competition. Change can be driven by converting data into insight. This whole process consists of a few different steps. First, you have to capture the data. Think about data sources already present within the organisation. Sometimes, it can be valuable to add additional data sources. It might be good to add data about the weather to predict or clarify ice cream sales for a certain period. After the data is captured it needs to be processed. Different data sources need to be combined and some attributes and / or measures might need some additional formatting. If the data sets are ready to be presented, it’s time to think about the best way to visualize data. Not all visualizations are equally suitable to present figures. It makes no sense to present time series in a pie chart. Also the choice of colors can have a huge impact on the interpretation of a visual.
Traditional BI is really focused on answering known questions. How were sales in 2016? Who achieved the highest revenue in 2016? These questions can be modeled upfront in a BI system. The answers to these questions can lead to new questions: why were sales so low in the month of June in 2016? These questions may require new data sources. These data sources can be combined with existing (modeled) data sources. A combination of data sources might yield different insights. This is the process of data discovery. Adding data about the weather or adding information about visitors to a city or a store can give valuable additional information. This additional information adds more value and makes the insights more complete. It gives the possibility to identify interesting patterns, opportunities and previously unknown trends.
Eventually the insights can be shared among other people like your colleagues. A story can be told based on the different insights as a result of the data discovery.
“See the Signals”
The Oracle Business Analytics philosophy is to support both traditional BI as well as data discovery. Traditional BI is a process, which is supported by IT. In a traditional BI environment, the IT department guarantees the validity and availability of the data. This data can be traced all the way back from the presentation to the source. Although one can really trust on this data, these environments are not as flexible as the business would like them to be. Sometimes, the business wants to play around with some other data. They want to explore data, which is not yet modeled and governed by the IT department. This data discovery needs to be a self-service process. Waiting for an IT department is not an option. The business wants to be able to visualize their data when they need it.
Oracle’s answer to self-service BI is Oracle Data Visualization (DV). Oracle DV offers the opportunity to add different data sources. With some lightweight ETL capabilities, Oracle DV is able to support the combination of different data sources and the manipulations of the different columns within these data sources. Like the name of the tool tells us, Oracle Data Visualization is a tool to visualize various sources of data in an easy way. This means that complex data sets can be turned into easy to digest and supporting insights. These insights can be shared in separate visual, which allows you to both visualize the data as well as telling the story behind the data.
Oracle Data Visualization is available both on-premise as well as in the Cloud. Moreover, Oracle DV is available as part of a platform (OBIEE and / or BICS) and stand-alone (Oracle DVCS). If you have acquired a license for Oracle DVD, you are allowed to use the Oracle Data Visualization Desktop (DVD) tool. Oracle DVD cannot be licensed separately. It comes with an Oracle DV license. Using Oracle DV allows you to “See the Signals” on any device. Desktop, tablet or browser, it does not matter.
Oracle DV uses the same platform whether you use it in the Cloud or on-premise. This means that you can start very small. If you start with an Oracle Data Visualization Cloud Service, you can start with a subscription of 5 users for as little as $75 per user per month. If Oracle DVCS proves its value, you can easily choose to move to e.g. the Oracle BI Cloud Service (BICS) without the need to start all over.
The Quistor Business Analytics and Big Data practice is specialized in the Oracle Business Analytics offer. If we need to put the offer into more context, we are happy to help you out. Although Oracle Data Visualization is designed to be easily executed by the business, you might need some help to get started. Again, we are happy to put you on the right track.
Please get in contact with me, so we can start telling the story behind your figures.
This article was originally written for the 4th edition of the Quistor QPulse.