Obviously, business processes have come a long way. Just think of the way an accountant’s job has evolved over the past 100 years: from handwritten spreadsheets and mechanical calculators to fully electronic systems on computers. And the next revolution is just about to take place − blockchain systems that verify transactions quickly, securely, and completely autonomously.
Questions this Cheat Sheet seeks to answer: What is NLP? Why does NLP matter? What is the difference NLP can make for your business?
To journalists, a good tip is newsworthy information or documents that are shared exclusively with them. Yet to servers at a restaurant, a good tip is a sum of money given to someone as a reward for their services. This is just one example that shows how different people attach different meanings and context to the same keywords or phrases.
Organizations are only starting to get to the place where they are able to strongly focus on data quality. This evolution is still only at its beginning. Until we harness the power of data quality into the hands of employees, data will struggle to become impactful in organizations.
When digital television was introduced in the United States, networks waited fifteen years to switch off their analog signals. Smartphone applications support generations of operating systems for years. Even leaded gasoline wasn’t phased out overnight.
The rapid growth digital transformation has changed the way companies do business. There are new ways to manage data, harness insights and engage customers are just some of the opportunities that digital transformation provides businesses.
As a customer yourself, you can probably relate to this: A Forrester survey found that customers’ biggest pain points in getting customer service was consistency and lack of agent knowledge. As consumers, we’re acutely aware of those pain points, but what are internal teams doing to solve the issue? 
To buy or build is a question many companies struggle with as they progress their digital transformation. In the past, “out-of-the-box” solutions used to be synonymous with rigid and inflexibility, so the concept of custom-built to exact specifications is enticing.
Data is the gold of the digital transformation – but only if knowledge can be generated from it. This is exactly the task that insight engines were designed to accomplish. Daniel Fallmann, founder and CEO of Mindbreeze, defines the six most important insight engine trends for 2019. 
Digitalization is increasingly impacting the healthcare sector. New products and services are making their way into day-to-day clinical practice or are offered as apps for patients. Dr. Adolf Sonnleitner from Mindbreeze highlights three developments that the industry will be focusing on in 2019.
AI and machine learning can be used to simulate processes and gain new insights into them. The new method of information acquisition and distribution resulting from this leads to real and measurable added value for companies.