Design thinking continues to be all the rage amongst organizations of all kinds – from academia to startups, to agencies and consultancies, or large enterprises. The concept is popular today not because it’s new per se, but its approach to problem-solving fits well with the digital transformation that companies are

Digital transformation dominates most CIO priority lists pertaining to questions such as:  How will digital transformation affect IT infrastructure? Will technology live on-premise or in the cloud? Depending on where that data lives, an organization requires different skill sets. If you’re building these resources in-house, then you need an infrastructure

The advent of the emerging sector of Big Data has brought with it the promise of highly scalable databases to handle terabytes of data at a time. Dealing with colossal datasets will attest to have difficulty for manipulating, storing and retrieving information in bulk quantities to determine if the cache

Here is how Big Data can help you in your growth strategies in ecommerce Ecommerce is taking a bigger slice of the global retail pie. In the US, for example, ecommerce currently accounts for approximately 10% of all retail sales, a number that’s projected to swell to nearly 18% by

Big Data and AI can help with the growing care provider shortage. Here is how and why. One percent of the global population possesses 40-percent of all the world’s wealth, a persistent issue for which economists and politicians have debated about for some time. Economic inequality is a problem that’s

Here is why Data Scientists need to think like a behavioural economist or psychologist when they communicate or story tell their insights. This helps companies to take concrete and bias-free decisions to acquire customers, retain employees and deal with managers within the organization. Picture this scenario: There are two investment

Disasters are dangerous, but Big Data can help improve disaster relief and preparedness to cut back on lives lost and community damage. Historically, public policies have proved ineffective in providing adequate help for disaster-stricken citizens. A year after hurricane Harvey in 2017, for example, residents are still in the midst

How do you merge the perspectives of the data scientists, entrepreneurs, investors, student and CTO’s under one roof when it comes to data-driven decisions? How do you bring together the likes of Google and IBM with academics and universities to find answers to the most relevant questions in the world

Last year, we set up a prediction model on crime in London. We had established the model already, grounded in open data, but updated it to make predictions about 2017. We took the data provided by the police in the greater London area, and by enriching this data with Points

Organizations yearn order and simplicity over chaos and confusion, but the data-driven era we live in challenges these desires on a daily basis. Seemingly every day, massive amounts of transactional and streaming data is being introduced into enterprises. This data must be collected, deciphered, shared, and acted upon. Cloud-native technologies