This blog post offers an overview and PDF download of the data stack, thus all tools that might be needed for data collection, processing, storage, analysis and finally integrated business intelligence solutions.
(Web)-Developers are used to stacks, most prominent among them probably the LAMP Stack or more current the MEAN stack. On the other hand, I have not heard too many data scientists talking about so much about data stacks – may it because we think, that in a lot of cases all you need is some python a CSV, pandas, and scikit-learn to do the job.
But when we sat down recently with our team, I realized that we indeed use a myriad of different tools, frameworks, and SaaS solutions. I thought it would be useful to organize them in a meaningful data stack. I have not only included the tools we are using, but I sat down and started researching. It turned out into an extensive list aka. the data stack PDF. This poster will:
- provide an overview of solutions available in the 5 layers (Sources, Processing, Storage, Analysis, Visualization)
- offer you a way to discover new tools and
- offer orientation in a very densely populated area
So without further ado, here is my data stack overview (Click to open PDF). Feel free to share it with your friends too.
Liip data stack version 1.0
Let me lay out some of the questions that guided me in researching each area and throw in my 5 cents while researching each one of them:
Continue reading about The Data Stack – Download the most complete overview of the data centric landscape.
Tags: Machine learning, analytics, data stack, overview, databases, visualization, data sources