Just like headhunting, you need to know which data has value and when it is available. Data brokerage for new — monetization — products is upcoming fast. — Understanding which data is available and how it can be of value for e.g. AI, data scientists or new products is not new. The last 5 years, data scientists performed their analysis based on mostly internal data with added value from either open data and/or data from trusted partners.

I believe that combining two existing domains, i.e. user design and data quality, will deliver to the next steps for a new data-for-value strategy chapter. To enable product innovation and marketing. The data domain is still constantly in flux. Where data quality & data management improvement have mostly been focusing…

Data: from nuisance to business value — This article contains 5 important domains to create value out of data. These domains are taking root and will play out over the coming decade. Plan for them. 1. Data, Data, Data Platform and emerging tech like cloud, ecosystems, AI, blockchain, and VR have captured most of our attention over…

In short, a data strategy is a vision for how a company will collect, store, manage, exchange, share and use data. With a general goal to decrease cost, generate business value and / or comply with relevant legislation. …

Combine best of both worlds! — A few years ago most data strategies were focused on 3 pillars: Efficiency, e.g. by robotics for automated data flows or better reporting based on good data quality. Compliance for data-driven regulations, e.g. for financial solvency, privacy and medical devices. Innovation, by monetizing new products based on (analytics) insights. However…

Looking for a key position right in the middle of data, AI, platform economy and software solution? Get ready for data engineering. What is data engineering? A data engineer connects data & AI through capturing, curating and processing data — e.g. for AI. Similar to ETL developers. However, where ETL development focuses on standardized data structures, BI reporting tools and periodical reports & management information, the data engineer develops for a world which is in constant…

Data strategies are booming. And complex. — Data strategies are different things to different companies. However, there are guidelines which will enhance your strategy, working towards results whilst staying in control. This article contains 5 main principles that deliver guidance for data strategies. # 1. Be bold, but treat data as if it is your own Within a strategy it is key to think big and bold. You already have…

Early adopters have used data science — nowadays captured in the umbrella term AI — for multiple purposes. It is used to make life easier (e.g. …

Business and sales really need to understand data & AI to monetize its value. — For most organisations, the last decade has been focused on improving data quality and data integration. And learning from Artificial Intelligence (AI*) pilots. Now is the time to monetize that effort. Yet, both data & AI have remained the domain of specialists. This time, business — mainly products and sales…