Podcast - Astrato and Thor featured on Data Skeptic
Modern Data Stacks
Today, we are joined by Alexander Thor (@Thor), Product Director at Vizlib, the creators of Astrato. Astrato is a data analytics and business intelligence tool built on the cloud, for the cloud. Alexander discusses the features and capabilities of Astrato for data professionals.
Alexander explained what analytics is and how his career has evolved over the years. He also discussed how important analytics is in this age. Having established the importance of a smooth data engineering experience, Alexander discussed the major problem Astrato solves in the face of other similar but dated or legacy analytics tools. He explained why in-memory computing is not used in Astrato, despite it being a good option some years back.
Going forward, Alexander explained the difference between a dashboard and a data app. Putting it simply, data apps are applications that rely heavily on data. Yelp is a typical example. Alexander then shared a few real-life scenarios where Astrato is particularly effective. He also spoke about the practical collaboration features on the platform.
Alexander described the typical persona of an Astrato user - the requisite skill and level of experience. With technological innovations and continuous development, the Product Director explained how having data in a data warehouse is the best way to build systems that are resilient to change. Furthermore, he gave an insight into how businesses can best structure their organization to get optimum insights from data. For a beginner, who is yet to master the intricacies of dashboarding, Alexander explained techniques they can deploy to generate quick insights. He also mentioned some tips to create powerful dashboards.
In closing, Alexander touched on a few interesting features that will be launched soon in Astrato. You can stay up-to-speed by signing up on astrato.io which remains free for five users. You can also follow Alexander on Twitter @mindspank.
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Data Skeptic launched as a podcast in 2014. Hundreds of interviews and tens of millions of downloads later, we're a widely recognized authoritative source on data science, artificial intelligence, machine learning, and similar topics.
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