Modern Data Stack
Modern Data Stack (MDS) is a collection of Software Tools and Cloud Services that used to Collect, Process, Store, and Analyze data.
You can see the below diagram show a Modern Data Stack Ecosystem that include the Cloud Services more than the Open-Source Stacks.
As such, the definition of a Modern Data Stack cannot be clearly stated since every business tries to adapt modern technologies to their requirements.
However, there are definite features of the modern data stack that identify it:
- It’s Cloud-Based, requires very little maintenance, is easy to install, and can scale quickly with little effort.
- It can be used by Small and Medium-Sized Data Teams, as it has a lot of out-of-the-box functionality and doesn't rely on the number of data professionals.
- It offers a Lot of Integration Opportunities for creating a comprehensive data ecosystem.
Getting Started
Modern Data Stack advocates a lot of changes, but if not done right they can be painful, expensive, and risky. Most often when I talk to data stack owners in the enterprise, the question is not so much how one tool compares to another but whether they can live with the status quo or Have a strong enough desire to change.
The Key Concepts:
- Easy to Try & Deploy
- Massive Scalability; Data, Users, and Use-Cases
- Composable Data Stack
- Flexible Pricing
Modern Data Stack allows you to build on top of the software of giants instead of adopting the "not invented here syndrome". Consider whether the business value from your analytics solution is coming from how well you manage your data pipelines and data infrastructure, versus how well you build analytics and AI products on top of your infrastructure.
Overall, the Modern Data Stack centerpiece is about democratizing data usage: Making data more accessible, covering different dimensions of business, improving analytics capabilities, and simplifying the infrastructure.
If the advantages of Modern Data Stack do not seem convincing enough, let's have a look at how it differs from the Traditional Data Stack.
| Traditional Data Stack | Modern Data Stack |
|---|---|
| Has coupled structure | Has modular structure |
| Complex setup requiring large IT teams | Less time on technical configuration |
| Requires serious technical background | Suitable for users without extensive technical background |
| Contains traditional RDBMS | Works with RDBMS as well as big data, unstructured data |
The Modern Data Stack provides businesses with a bias for action. Creating a Modern Data Stack enables organizations to devote more time to analyzing their data and less time engineering their data processing pipelines.
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