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To ensure that data in Power BI reports do not fall into the wrong hands, it is possible to apply Row-Level Security (RLS) to any report within a workspace. RLS in Power BI ensures that for each recipient of the report a difference can be made in what data they can see. It is important that the setup is done accurately and that the members of a workspace are assigned the right role to prevent them from seeing too much information, for example. This RLS layout of the online workspaces in Power BI has changed in the last few months. In this blog, we explain what to pay attention to when setting up a new workspace and setting up the renewed RLS in Power BI.
Are you looking for a new dashboarding or data integration solution? Do you want to compare data science solutions? Or do you want to see Low Coding platforms in action? It’s all possible during the Data & Analytics Line Up 2021! The recordings are now available. Please note most tool sessions where in Dutch
Do you want to know how predictive models can help your company make better decisions? Then watch our webinar “Predict churn with artificial intelligence”. Lots of companies are focusing on getting new customers instead of keeping their existing customer base. Due to these strategies, a lot of customers are hopping from company to company.
There is one thing that’s just as important as finding new clients: keeping your current clients. This one-pager will give you some practical tips to increase your loyal customer group by making use of the science of data!
Data Science, Artificial Intelligence, and Machine Learning are becoming buzzwords more and more. The terms appear to be valuable according to the trendwatchers, but most often people do not even know what the terms mean, let alone that they use them.
We at Rockfeather help people and organizations to understand and retrieve value from the buzzwords.
In collaboration with Finext and The Hague University of Applied Sciences, Rockfeather conducted a survey among our customers and other data enthusiast. The survey consists of twenty questions that investigate the data maturity, the presence of a data-mindset and how they reach and plan to reach their data ambitions and goals.
What is the optimal set of processes to allocate our resources? What process and steps do we have? These questions seem like questions that every company should answer easily. Unfortunately, a lot of companies are not able to do so. Their processes are just too complex because of changing price constraints, or other variables. There is a solution: Process optimization.
This year’s Magic Quadrant for Data Science and Machine Learning Platforms scored six Data Science and Machine Learning (DSML) Platforms as leaders. The amount of leaders has remained the same, compared to last year’s number of leaders. But has the composition of the leading area changed?