Recent Posts by Philippe Lions

Crafting machine learning algorithms is the first step toward automatically creating data models you can use to answer business questions. But being able to retrieve information from those machine learning models will help you save time and speed up your processes. Oracle Database offers powerful machine learning algorithms that enable data analysts to discover hidden patterns and insights. With Oracle Machine Learning (OML), you can build and apply predictive models inside the...

Is simple find-and-replace not enough for your data preparation needs? Face it, swapping out one word or character in millions of database entries can get tedious and repetitive. But now, Oracle Analytics Data Prepare features a Regular Expression Replace function that brings great new powerful abilities with pattern matching. We will see what it has got to offer in this blog. First, take a quick look at the video which explains briefly about this feature.     Oracle Analytics now...

The Oracle Analytics Repository stores server metadata. The metadata defines logical schemas, physical schemas, physical-to-logical mappings, aggregate table navigation, and other constructs. You can edit Oracle Analytics repositories using the Oracle Analytics Administration Tool. In this blog we will go through accessing the Oracle Analytics Cloud and Oracle Analytics Server repositories (noted with the .rpd file format, or just RPD) This can be data found in a live mode...

You can create a data flow from one or more data sources. Data flows are a way to produce a curated data source that you can use to easily and efficiently create meaningful data visualizations. But have you ever wondered exactly what is happening when you execute your Oracle Analytics data flow? How can you see the exact log of actions triggered by the dataflow you just executed? Most of us rely only on the system confirmation that an Oracle Analyticsdata-flow ran successfully...

Visualizing data using the Maps feature in Oracle Analytics is very compelling to any audience. It really speaks to our sense of "where" the action is happening, which is basic when it comes to information gathering or problem-solving. Let's look at how adding a map layer to a column in a data visualization gives the most rapid and relevant answer to the "where" question in a data story. The Maps Unfair Advantage Maps leverage the geographical concepts we have been exposed to...

It's the essential question of all businesses: How effective is our marketing campaign? The answer is not as complicated as you might think. By using Oracle Analytics data visualization feature and machine learning, we can gain some valuable insight into our marketing strategy where we can measure our key performance indicators. Then you can determine if your message gets to the right customers at the right time. Subscribe to the Oracle Analytics Advantage blog and get the latest...

Sharing a data analysis and visualizations with other team members in a safe and secure manner is a key requirement for any analytics solution. Oracle Analytics offers the capability for designers to completely control the way their projects are shared and leveraged with other users. Data-level security defines what rows or columns are returned to a user inside an analysis or data visualization project view. The same view, when run by two different users, can bring up...

When explaining the results of data analysis, it's easy to say, "80 percent of the losses came from 20 percent of the causes." But reinforcing this narrative with a data visualization can really send home that message.   The 80/20 rule or Pareto's principle developed by Vilfredo Pareto is often applied to represent the significant few versus the trivial many. Graphically, a Pareto diagram simply displays a bar chart distribution of a metric by a dimension sorted in...

Oracle Analytics allows you to easily create custom calculations in data visualization projects. It's a simple process to extend your analysis or datasets with any calculations and aggregations you may need right while you are building your visualizations, irrespective of the type of underlying data. You can build a custom calculation on a data visualization project directly, or you can build it in the dataset using the Data Prepare tab.But which one is the right one, since...