Data + Intelligence

I was reading an article about “Amazon using its MultiDimensional Datasets”. The news never gets old to me that Amazon Retail leveraging its Big Data Ecosystem to access 1,000,000,000 GB of data on more than 1,400,000 servers to increase sales through predictive analytics does personalized recommendations, price optimization, and anticipatory predictions on what the customer […]

As a digital marketer or technologist, Adobe’s technologies offer tremendous potential and impressive capabilities. But, with all the different names, teams and viewpoints from Adobe, much less the partner ecosystem, how do you keep it all straight? This post is intended to be your introduction to the Adobe Experience Cloud solutions. Whether you are just […]

What will the future hold for data science and machine learning platforms? Most of you already saw Gartner’s perspective in their latest Magic Quadrant on the evolution of data science that was released at the beginning of 2018 and are familiar with the outcome. However, did you ever ask yourself why SAS, KNIME, RapidMiner, and H2O.ai became […]

Imagine a spreadsheet has been replicated thousands of times across a vast network of computers. Now, imagine that these computers, within the network, regularly update this spreadsheet. This is the most basic form of understanding a blockchain. Blockchain is the underlying technology in bitcoin and other cryptocurrencies. Information contained and stored within a blockchain will […]

Oracle Cloud BI solutions have been available for a few years now and have evolved significantly over the past couple years. If you have been using OBIEE or OBIA (Oracle BI Applications), you are in a pretty good position to start migrating to Oracle Analytics Cloud (OAC). The reason: OAC relies on a similar underlying […]

At IBM Think 2018, Shantenu Agarwal, Lead Offering Manager for Visual Recognition and Donna Dillenburger, IBM Fellow, spoke on using AI for Good, Addressing Global Challenges with Visual Recognition. They highlighted a variety of ways in which IBM teams use visual recognition to combat issues around sustainability and fraud. AI and Social Good Statistic: 1.2 […]

At IBM Think (#think2018), David McBride, director of Product Management, Watson Customer Experience Analytics at IBM, and Sharon Nei, senior product manager at IBM Customer Experience Analytics, spoke in the session, “Watson Customer Experience Analytics: Know Your Customers Better Than They Know Themselves.” The program and offering managers gave insight into what’s coming with Watson Customer Experience […]

Everything is data and everyone is data! Everybody says we live in the technology age, the age of the internet, the age of space and cosmos, the age of the digital world etc. But all of these developments and advancements have been made possible by the Holy Grail called Data. We learned how to store […]

Healthcare breakthroughs are happening on a daily occurrence in 2018. Dominant companies of business are developing new and advanced strategies for optimal patient care and diagnosis. Google has stepped into the light and released a new eye artificial intelligence algorithm, in the early stages of development, which can detect patient health problems. The new state […]

In the world of Big Data, Data engineers always strive to find a way or method to analyze, process, and compute the Volume, Velocity, and Variety of data, and to provide Data scientists with a resilient backbone to conduct their analysis. Before the introduction of the cloud platforms, all the big data processing and managing […]

What do I want to watch tonight? What is the next book I might want to read? Those types of questions are usually answered through the suggestions that are embedded into your screen when you’re about to make your selections either on your phone, computer, tablet, or television. Initially, or as I recall, these recommendations were […]

Why do I give my precedence to build the model as Proof of Concept (POC) instead of following established methodologies such as CRISP-DM, SEMMA, AIE, MAD Skills, etc.? Even though most of the Data scientists will say that they are two different things and used for different purposes; one is a methodology or a step […]