Indubitably, as the year 2020 comes to an end, most organizations recognize that data can be applied to improve decision making, measure progress, and facilitate persuasion. However, without the right tools and platforms to access, analyze, and model data, these teams cannot do their jobs effectively.
Although new techniques enable us to store, collect, and apply AI to high-volume, high-velocity, high-variety datasets; business intelligence (BI) and analytics tools have not really changed – they are still designed to answer the same simple and/or repetitive questions. Solving more complex problems requires expertise in query and/or scripting languages. In addition, BI and analytics tools don’t help users evaluate why things are happening, predict what will happen next, or identify potential solutions.
And they’re slow. Just ask anyone who has waited 20+ minutes for an ODBC dashboard to load before a company sync.
We invested in Einblick because we believe that analysts worldwide deserve something better than spreadsheets and bar charts. According to LinkedIn, there are 5.8M data analysts, most of whom do not have Python or R skills. While some of these analysts can and should learn to code, programming should not be necessary for all business use cases. Non-technical analysts should be able to answer questions more complex than “Is my revenue increasing or decreasing?”
Einbick is different. Einblick (which means “insight” in German; or “one glance” when translated as “ein blick”) enables data teams to answer tougher, more meaningful questions by making advanced analytics and model building more streamlined and accessible. Unlike other BI and analytics tools, Einblick takes a radically new approach to querying, analyzing, modeling, and visualizing complex datasets by providing teams with a visual computing platform. This platform includes the following capabilities:
Einblick is already empowering analysts to make a more profound impact. For example, they’re enabling customers like a large German car manufacturer to do things that weren’t possible before – like identifying root causes for production line quality defects and identifying key drivers of employee productivity.
Building an integrated visual computing environment for descriptive, predictive, and prescriptive analytics is an immense technical challenge. It necessitates unprecedented technical skills in machine learning, data management and human-computer interaction. Einblick, which was developed based on 6 years of research at MIT and Brown University, was founded by a team helmed by Tim Kraska and four graduate student researchers. Tim, who is co-director of the Data Systems and AI Lab (DSAIL) at MIT, is highly esteemed for his achievements in both database and AI research, including his influential publications on learned indexes. Emanuel Zgraggen, Zeyuan Shang, Philipp Eichmann, and Benedetto Buratti are recognized for their research contributions in fields ranging from progressive sequence mining to large-scale metalearning. Fundamentally changing how the world interacts with data will not be easy – but this team is prepared to do it. They’re finally giving data analysts the superpowers they need to make a deep business impact.
We’re so glad to be a part of their journey to enable anyone to understand the past, shape the present, and predict the future.