Ready to kickstart your plans for 2019? Spark ideas by reading a few of our best data science blogs. Add a new perspective to it and discover how it can impact your business.
Stay tuned in 2019! We’ve got a lot more insights, best practices and inspiration coming your way to help you grow into or advance as a data-driven organization and achieve better results.
3 Upcoming Challenges Your Data Science Team Will Face
by Erica D’Acunto
Data science has been increasing in popularity the past 5 years. Most – if not all – companies are busy finding ways to optimize the potential of their data by building machine learning models and moving towards Artificial Intelligence (AI). From traditional demand forecasting to dynamic pricing, from targeted advertising to predictive maintenance, the AI wave is changing the decision-making process for companies in every industry. With such a big change comes challenges that these companies will face, especially for the data scientists working within these organizations. Here are the top three challenges that your data science team will most likely face in the upcoming years. Read more
Closing the Data Talents Gap – Start Spotting Opportunities Internally
by Robert Monné
The demand for data science talents has exploded. For four consecutive years, LinkedIn listed Statistical Analysis and Data Mining in the top three of skills in demand. The best jobs include positions like data scientists, engineers and analysts. Yet, according to a 2015 MIT Sloan Management Review Survey, 40% of the companies are struggling to find and retain data analytics talent. This alarming outcome is fed by a recent study of the European Commission, in which they indicated we will need another 769.000 skilled data professionals in Europe until 2020 to fill the gap. We all want data talent. Talent that is hard to find. What can your company do to close the data talents gap? Read more
Top 4 Best Practices for Implementing an IBM Chatbot
by Ivo Fugers
So, you have identified how an AI-based chatbot can add value within your organization and you’re finally ready to start implementing it. During a 3-month project for a large insurance company, we realized that building a chatbot is easy, but building a highly-functional chatbot requires dedication, a lot of structure and teamwork, several prototypes, and consistent quality-control. I will walk you through the top 4 lessons we learned during our project, which involved setting-up a proof-of-concept using IBM Watson algorithms. Let’s share some insight on how you – too – can take your chatbot from prototype to production. Read more
Dare to Let Artificial Intelligence Decide
by Patrick Hennen
Artificial intelligence (AI) is wildly popular, and it seems as if it is omnipresent applied. It is the foundation for your social media timeline, and with almost every interaction online follows an AI implementation providing you with more relevant suggestions based on your interaction. But useful applications that go beyond simple recommendations are hard to find. Why is that? Organizations find it scary to rely on AI. Read more
5 Technologies that will Change Our Lives in 5 Years
by Erica D’Acunto
It is very inspiring to see how artificial intelligence (AI) can improve the world and the quality of our life rather than just using the abilities to increase sales or decrease costs. In terms of changes coming to the data science world, I see quantum computers being a huge game-changer for optimization algorithms, and they are already quickly approaching commercialization. Through them, we’ll be able to solve problems currently unsolvable, and can – potentially – become great assets to our company. Read more
…and benefit from the best practices of our experts and companies like yours to boost your data-driven journey.