Blog and Resources

Part of our Data Science 201 Series. Make sure your models work in production, the way you expect them to based on model training. Why Split …

Three innovations to bring humans back into the loop As organizations made data analytics a strategic priority, demand for data analysis outputs exceeded supply of trained …

Einblick is excited to share that it has been chosen as an IDC Innovator in Business Intelligence and Decisioning Software Solutions. This means that we have …

Move fast and break things — but still be data informed. Startups must tailor their data analytics practices to focus on on delivering strategic insights quickly. …

What is AutoML? How does it work?

Einblick Is a “No Unnecessary Code” Platform Think about how much productive data science time has been lost to making graphs with ggplot or matplotlib! And …

Last week I attended the first Citizen Data Science Summit which MIT hosted. The conference was a great success, with over 850 people participating virtually and …

Einblick, an interactive analytics whiteboard, based on years of research at MIT and Brown University, today announced a new video-based collaboration feature, which enables multi-disciplinary teams …

The Pareto Principle, commonly known as “80 / 20,” suggests that the majority of value is captured in the first small application of effort. Applying that …

Organizations need to deploy AI and machine learning more widely, beyond just data science teams. Yes, sometimes these models will be imperfect, or even result in …

At Einblick, we’ve consistently heard that the availability and scale of data has grown faster than the supply of data scientists available to tackle that data. …

Generating hypotheses about novel data can be tough. Without a top-down approach to explore data, even sophisticated analysts might invest hours “slicing and dicing” in dozens …

As much as we want to believe that companies use live dashboards and sophisticated collaboration tools to share, communicate, and discuss analytical results, the reality is …

As organizations try and empower democratized analytics, they must consciously recognize where advanced tools like AutoML needs to be augmented with human intuition. Data scientists have …

Why have advancements in Machine Learning (ML) imperfectly translated to better data driven decision making? How can business line stakeholders and data scientists bridge the gap …

In this blog, we discuss the collaboration challenges in data science today. Then, we share a case study of how one of our clients implemented live …

Predictive analytics is about what will happen.  Based on past examples and similar situations, an analyst can build models to forecast the current trajectory, or to …

Descriptive analytics is about what happened. All organizations use descriptive analytics in some form. Common outputs of descriptive analysis include pre-configured dashboards, Excel charts, and sometimes …

Prescriptive analytics is about what we should do.  In other words, how can we take the set of constraints that we have, the drivers of performance …

Good analysis is incomplete before it is successfully communicated to decision makers. But many traditional data science tools have inflexible outputs, that are not designed to …

For many, remote work and collaboration has become an integral part of life. With that, the demand for technology that supports teams to jointly perform tasks …

Today we are proud to announce our seed funding and the launch of our Founding Customer Program. The official press release was published on PR Newswire …

Over the last two decades the analytics space has drastically changed. Data has gone from scarce to superabundant and the popularity of  data analytics as a …

Traditional whiteboards are ubiquitous in offices, meeting rooms, classrooms and other work environments. They serve as an interface for thinking — a visual thinking tool, if …